Advice on the use of masks in the context of COVID-19

Interim guidance 5 June 2020

This document is an update of the guidance published on 6 settings, for the general public, and during home care. It will April 2020 and includes updated scientific evidence relevant be revised as more data become available. to the use of masks for preventing transmission of Coronavirus disease 2019 (COVID-19) as well as practical considerations. The main differences from the previous Background version include the following: The use of masks is part of a comprehensive package of the • Updated information on transmission from symptomatic, pre-symptomatic and asymptomatic prevention and control measures that can limit the spread of people infected with COVID-19, as well as an certain respiratory viral diseases, including COVID-19. update of the evidence of all sections of this Masks can be used either for protection of healthy persons document; (worn to protect oneself when in contact with an infected individual) or for source control (worn by an infected • New guidance on the targeted continuous use of individual to prevent onward transmission). medical masks by health workers working in clinical areas in health facilities in geographical areas with However, the use of a mask alone is insufficient to provide an community transmission1 of COVID-19; adequate level of protection or source control, and other • Updated guidance and practical advice for decision- personal and community level measures should also be makers on the use of medical and non-medical adopted to suppress transmission of respiratory viruses. masks by the general public using a risk-based Whether or not masks are used, compliance with hand approach; hygiene, physical distancing and other infection prevention • New guidance on non-medical mask features and and control (IPC) measures are critical to prevent human-to- characteristics, including choice of fabric, number human transmission of COVID-19. and combination of layers, shape, coating and This document provides information and guidance on the use maintenance. of masks in health care settings, for the general public, and

during home care. The World Health Organization (WHO) Guidance and recommendations included in this document has developed specific guidance on IPC strategies for health are based on previous WHO guidelines (in particular the care settings (2), long-term care facilities (LTCF) (3), and WHO Guidelines on infection prevention and control of home care.(4) epidemic- and pandemic-prone acute respiratory infections in health care) (1) and the evaluation of current evidence by the WHO ad hoc COVID-19 IPC Guidance Development Group Transmission of COVID-19 (COVID-19 IPC GDG) that meets at least once a week. The process of interim guidance development during emergencies Knowledge about transmission of the COVID-19 virus is consists of a transparent and robust process of evaluation of accumulating every day. COVID-19 is primarily a respiratory the available evidence on benefits and harms, synthetized disease and the spectrum of infection with this virus can range through expedited systematic reviews and expert consensus- from people with very mild, non-respiratory symptoms to building facilitated by methodologists. This process also severe acute respiratory illness, sepsis with organ dysfunction considers, as much as possible, potential resource and death. Some people infected have reported no symptoms implications, values and preferences, feasibility, equity, at all. ethics and research gaps. According to the current evidence, COVID-19 virus is

primarily transmitted between people via respiratory droplets Purpose of the guidance and contact routes. Droplet transmission occurs when a person is in close contact (within 1 metre) with an infected This document provides guidance to decision makers, public person and exposure to potentially infective respiratory health and IPC professionals, health care managers, and droplets occurs, for example, through coughing, sneezing or health workers on the use of medical and non-medical masks very close personal contact resulting in the inoculation of in health care (including long-term care and residential) entry portals such as the mouth, nose or conjunctivae

1 Defined by WHO as “experiencing larger outbreaks of local surveillance; and/or multiple unrelated clusters in several areas of transmission defined through an assessment of factors including, the country/territory/area” (https://www.who.int/publications- but not limited to: large numbers of cases not linkable to detail/global-surveillance-for-covid-19-caused-by-human- transmission chains; large numbers of cases from sentinel infection-with-covid-19-virus-interim-guidance) -1- Advice on the use of masks in the context of COVID-19: Interim guidance

(eyes).(5-10) Transmission may also occur through fomites in (12%–20%),(25) although most studies included in this the immediate environment around the infected person.(11, review have important limitations of poor reporting of 12) Therefore, transmission of the COVID-19 virus can occur symptoms, or did not properly define which symptoms they directly by contact with infected people, or indirectly by were investigating. Viable virus has been isolated from contact with surfaces in the immediate environment or with specimens of pre-symptomatic and asymptomatic objects used on or by the infected person (e.g., stethoscope or individuals, suggesting, therefore, that people who do not thermometer). have symptoms may be able transmit the virus to others.(26) Comprehensive studies on transmission from asymptomatic In specific circumstances and settings in which procedures individuals are difficult to conduct, but the available evidence that generate aerosols are performed, airborne transmission of from contact tracing reported by Member States suggests that the COVID-19 virus may be possible. The scientific asymptomatically-infected individuals are much less likely to community has been discussing whether the COVID-19 transmit the virus than those who develop symptoms. virus, might also spread through aerosols in the absence of aerosol generating procedures (AGPs). This is an area of Among the available published studies, some have described active research. So far, air sampling in clinical settings where occurrences of transmission from people who did not have AGPs were not performed, found virus RNA in some studies symptoms.(21,25-32) For example, among 63 (13-15) but not in others. (11, 12, 16) However, the presence asymptomatically-infected individuals studied in China, there of viral RNA is not the same as replication- and infection- was evidence that 9 (14%) infected another person.(31) competent (viable) virus that could be transmissible and Furthermore, among two studies which carefully investigated capable of sufficient inoculum to initiate invasive infection. secondary transmission from cases to contacts, one found no Furthermore, a small number of experimental studies secondary transmission among 91 contacts of 9 asymptomatic conducted in aerobiology laboratories have found virus RNA cases,(33) while the other reported that 6.4% of cases were (17) and viable virus (18), but these were experimentally attributable to pre-symptomatic transmission.(32) The induced AGPs where aerosols were generated using high- available data, to date, on onward infection from cases powered jet nebulizers and do not reflect normal human without symptoms comes from a limited number of studies cough conditions. High quality research including with small samples that are subject to possible recall bias and randomized trials in multiple settings are required to address for which fomite transmission cannot be ruled out. many of the acknowledged research gaps related to AGPs and airborne transmission of the COVID-19 virus. Guidance on the use of masks in health care settings Current evidence suggests that most transmission of COVID- (including long-term care and residential facilities) 19 is occurring from symptomatic people to others in close contact, when not wearing appropriate PPE. Among Use of medical masks and respirators to provide care to symptomatic patients, viral RNA can be detected in samples suspected or confirmed COVID-19 patients weeks after the onset of illness, but viable virus was not found This section provides evidence- and consensus-based after day 8 post onset of symptoms (19, 20) for mild patients, guidance on the use of medical masks and respirators by though this may be longer for severely ill patients. Prolonged health workers providing direct care to COVID-19 patients. RNA shedding, however, does not necessarily mean continued infectiousness. Transmissibility of the virus Definitions depends on the amount of viable virus being shed by a person, whether or not they are coughing and expelling more droplets, Medical masks are defined as surgical or procedure masks that the type of contact they have with others, and what IPC are flat or pleated; they are affixed to the head with straps that go measures are in place. Studies that investigate transmission around the ears or head or both. Their performance characteristics are tested according to a set of standardized test methods (ASTM should be interpreted bearing in mind the context in which F2100, EN 14683, or equivalent) that aim to balance high they occurred. filtration, adequate breathability and optionally, fluid penetration There is also the possibility of transmission from people who resistance.(34, 35) are infected and shedding virus but have not yet developed Filtering facepiece respirators (FFR), or respirators, similarly symptoms; this is called pre-symptomatic transmission. The offer a balance of filtration and breathability; however, whereas incubation period for COVID-19, which is the time between medical masks filter 3 micrometre droplets, respirators must filter exposure to the virus and symptom onset, is on average 5-6 more challenging 0.075 micrometre solid particles. European days, but can be as long as 14 days.(21, 22) Additionally, data FFRs, according to standard EN 149, at FFP2 performance filter suggest that some people can test positive for COVID-19, via at least 94% solid NaCl particles and oil droplets, and US N95 FFRs, according to NIOSH 42 CFR Part 84, filter at least 95% polymerase chain reaction (PCR) testing 1-3 days before they NaCl particles. Certified FFRs must also ensure unhindered develop symptoms.(23) Pre-symptomatic transmission is breathing with maximum resistances during inhalation and defined as the transmission of the COVID-19 virus from exhalation. Another important difference is the way filtration is someone infected and shedding virus but who has not yet tested; medical mask filtration tests are performed on a cross- developed symptoms. People who develop symptoms appear section of the masks whereas FFRs are tested for filtration across to have higher viral loads on or just prior to the day of the entire surface. Therefore, the layers of the filtration material symptom onset, relative to later on in their infection.(24) and the FFR shape, ensuring outer edges of the FFR seal around wearer’s face, result in a guaranteed claimed filtration when worn Some people infected with the COVID-19 virus do not ever compared to the open shape, or leaking structure, of medical masks. Other FFR performance requirements include being develop any symptoms, although they can shed virus which within specified parameters for maximum CO2 build up, total may then be transmitted to others. One recent systematic inward leakage and tensile strength of straps.(36, 37) review found that the proportion of asymptomatic cases ranged from 6% to 41%, with a pooled estimate of 16%

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Available evidence workers have strong preferences regarding highest perceived protection possible to prevent COVID-19 infection and, WHO’s guidance on the type of respiratory protection to be therefore, place high value on the potential benefits of worn by health workers providing direct care to COVID-19 respirators in settings without AGPs, despite demonstration patients is based on 1) WHO guidelines recommendations on of equivalence of effectiveness compared to medical masks IPC of epidemic- and pandemic-prone acute respiratory in some studies and low certainty of the evidence suggesting infections in health care;(1) 2) updated systematic reviews of their greater risk reduction in others. randomized controlled trials on the effectiveness of medical masks compared to that of respirators on the risk of: clinical respiratory illness, influenza-like illness (ILI) and laboratory- Definitions confirmed influenza or viral infections. The WHO guidance Universal masking in health facilities is defined as the is similar to recent guidelines of other professional requirement to wear a mask by all health workers and anyone organizations (the European Society of Intensive Care entering the facility, no matter what activities are undertaken Medicine and the Society of Critical Care Medicine, and the (discussed with COVID-19 IPC GDG). Infectious Diseases Society of America).(38, 39) Targeted continuous medical mask use is defined here as the Meta-analyses in systematic literature reviews have reported practice of wearing a medical mask by all health workers and that the use of N95 respirators compared with the use of caregivers working in clinical areas during all routine activities medical masks is not associated with any statistically throughout the entire shift. In this context, masks are only significant lower risk of the clinical respiratory illness changed if they become soiled, wet or damaged, or if the health outcomes or laboratory-confirmed influenza or viral worker/caregiver removes the mask (e.g. for eating or drinking infections.(40, 41) Low-certainty evidence from a systematic or caring for a patient who requires droplet/contact precautions review of observational studies related to the for other reasons) (discussed with COVID-19 IPC GDG). betacoronaviruses that cause severe acute respiratory syndrome (SARS), Middle East respiratory syndrome Health workers are all people primarily engaged in actions with (MERS) and COVID-19 showed that the use of face the primary intent of enhancing health. Examples are: Nursing protection (including respirators and medical masks) results and midwifery professionals, doctors, cleaners, other staff who in a large reduction in risk of infection among health workers; work in health facilities, social workers, and community health N95 or similar respirators might be associated with greater workers, etc. (46) reduction in risk than medical or 12–16-layer cotton masks), but the studies had important limitations (recall bias, limited information about the situations when respirators were used In conclusion, the great majority of the GDG members and about measurement of exposures) and most were confirmed previous recommendations issued by WHO which conducted in settings in which AGPs were performed.(42) include that: • in the absence of AGPs2, WHO recommends that health workers providing direct care to COVID-19 WHO continues gathering scientific data and evidence on the patients, should wear a medical mask (in addition to effectiveness of different masks use and on its potential other PPE that are part of droplet and contact harms, risks and disadvantages, as well as its combination precautions); with hand hygiene, physical distancing and other IPC • in care settings for COVID-19 patients where AGPs measures. are performed (e.g. COVID-19 intensive and semi- intensive care units), WHO recommends that health workers should wear a respirator (N95 or FFP2 or Recommendations FFP3 standard, or equivalent). The WHO COVID-19 IPC GDG considered all available evidence on the COVID-19 virus modes of transmission and Note: Respirators are recommended for settings where AGPs on medical mask versus respirator use to protect health are performed. Based on values and preferences and if widely workers from infection, its level of certainty, as well as the available, they could also be used when providing direct care potential benefits and harms, such as development of facial to COVID-19 patients in other settings. For additional skin lesions, irritant dermatitis or worsening acne, or guidance on PPE, including PPE beyond mask use by health breathing difficulties that are more frequent with workers, see WHO IPC guidance during health care when respirators.(43, 44) COVID-19 infection is suspected (2) and also WHO guidance on the rational use of PPE.(45) The GDG also considered the implications of maintaining or changing the current recommendations, in terms of availability of medical masks versus respirators, cost and procurement implications, feasibility, equity of access to these respiratory protections by health workers around the world. The GDG acknowledged that in general, health

2 The WHO list of AGPs includes: tracheal intubation, non- bronchoscopy, sputum induction induced by using nebulized invasive ventilation, tracheotomy, cardiopulmonary hypertonic saline, and autopsy procedures. resuscitation, manual ventilation before intubation, -3- Advice on the use of masks in the context of COVID-19: Interim guidance

Targeted continuous medical mask use by health workers transmission risk areas including triage, family in areas of known or suspected COVID-19 community physician/GP practices, outpatient departments, transmission emergency rooms, COVID-19 specified units, haematological, cancer, transplant units, long-term This section considers the continuous use of medical masks health and residential facilities; by health workers and caregivers in areas of known or • When using medical masks throughout the entire shift, suspected community transmission regardless of whether health workers should make sure that: direct care to COVID-19 patients is being provided. the medical mask is changed when wet, soiled, or Available evidence ­ damaged; In areas where there is community transmission or large-scale ­ the medical mask is not touched to adjust it or outbreaks of COVID-19, universal masking has been adopted displaced from the face for any reason; if this in many hospitals to reduce the potential of (asymptomatic, happens, the mask should be safely removed and pre-symptomatic and symptomatic) transmission by health replaced; and hand hygiene performed; workers and anyone entering the facility with COVID-19 to ­ the medical mask (as well as other personal other health workers and to patients.(47) protective equipment) is discarded and changed after caring for any patient on contact/droplet precautions There are currently no studies that have evaluated the for other pathogens; effectiveness and potential adverse effects of universal or • targeted continuous mask use by health workers in preventing Staff who do not work in clinical areas do not need to transmission of SARS-CoV-2. Despite the lack of evidence use a medical mask during routine activities (e.g., the great majority of the WHO COVID-19 IPC GDG administrative staff); members supports the practice of health workers and • Masks should not be shared between health workers and caregivers in clinical areas (irrespective of whether there are should be appropriately disposed of whenever removed COVID-19 or other patients in the clinical areas) in and not reused; geographic settings where there is known or suspected • A particulate respirator at least as protective as a US community transmission of COVID-19, to continuously wear National Institute for Occupational Safety and Health- a medical mask throughout their shift, apart from when eating certified N95, N99, US FDA surgical N95, European and drinking or changing the mask after caring for a patient Union standard FFP2 or FFP3, or equivalent, should be requiring droplet/contact precautions for other reasons (e.g., worn in settings for COVID-19 patients where AGPs influenza), to avoid any possibility of cross-transmission. are performed (see WHO recommendations above). In these settings, this includes its continuous use by health This practice reflects the strong preferences and values placed workers throughout the entire shift, when this policy is on preventing potential COVID-19 infections in health implemented. workers and in non-COVID-19 patients; these preferences and values may outweigh both the potential discomfort and To be fully effective, continuous wearing of a medical mask other negative consequences of continuously wearing a by health workers, throughout their entire shift, should be medical mask throughout their shift and the current lack of implemented along with other measures to reinforce frequent evidence. hand hygiene and physical distancing among health workers in shared and crowded places where mask use may be Note: Decision makers should consider the transmission unfeasible such as cafeterias, dressing rooms, etc. intensity in the catchment area of the health facility and the The following potential harms and risks should be carefully feasibility of implementing a policy of continuous mask use taken into account when adopting this approach of targeted for all health workers compared to a policy based on assessed continuous medical mask use, including: or presumed exposure risk. Either way, procurement and costs should be taken into account and planned. When • self-contamination due to the manipulation of the mask planning masks for all health workers, long-term availability by contaminated hands;(48, 49) of medical masks for all workers should be ensured, in • potential self-contamination that can occur if medical particular for those providing care to confirmed or suspected masks are not changed when wet, soiled or damaged; COVID-19 patients. • possible development of facial skin lesions, irritant dermatitis or worsening acne, when used frequently for Guidance long hours(43, 44, 50) • masks may be uncomfortable to wear;(41, 51) In the context of locations/areas with known or suspected • false sense of security, leading to potentially less community transmission or intense outbreaks of COVID-19, adherence to well recognized preventive measures such WHO provides the following guidance: as physical distancing and hand hygiene; • Health workers, including community health workers • risk of droplet transmission and of splashes to the eyes, and caregivers, who work in clinical areas should if mask wearing is not combined with eye protection; continuously wear a medical mask during their routine • disadvantages for or difficulty wearing them by specific activities throughout the entire shift; apart from when vulnerable populations such as those with mental health eating and drinking and changing their medical mask disorders, developmental disabilities, the deaf and hard after caring for a patient who requires droplet/contact of hearing community, and children; precautions for other reasons; • difficulty wearing them in hot and humid environments. • According to expert opinion, it is particularly important to adopt the continuous use of masks in potential higher

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Table 1. Type of mask for use by health workers depending on transmission scenario, setting and activity*

COVID-19 Who Setting Activity What type of mask* Transmission scenario Known or Health worker or Health facility In patient care area – irrespective Medical mask (targeted suspected caregiver (including primary, if patients are COVID-19 continuous medical community secondary, tertiary suspect/confirmed masking) transmission care levels, outpatient care, and LTCF) Personnel (working in Health care facility No routine activities in patient Medical mask not needed. health care facilities but (including primary, areas Medical mask should be not providing care for secondary, tertiary considered only if in patients, e.g. care levels, outpatient contact or within 1m of administrative staff) care, and LTCF) patients, or according to local risk assessment. Health worker Home visit (for When in direct contact or when a Consider using a medical example, for antenatal distance of at least 1m cannot be mask or postnatal care, or maintained. for a chronic condition) Health worker Community Community outreach programs Consider using a medical mask Sporadic Health worker or Health care facility Providing any patient care Medical mask use transmission or caregiver (including primary, according to standard and clusters of COVID- secondary, tertiary transmission-based 19 cases care levels, outpatient precautions (risk care, and LTCF) assessment) Health worker Community Community outreach programs No mask needed Any transmission Health worker or Health care facility When in contact with suspect or Medical mask scenario caregiver (including primary, confirmed COVID-19 patient secondary, tertiary care levels, outpatient care, and LTCF) Health worker Health care facility Performing an AGP on a Respirator (N95 or N99 or (including LTCF), in suspected or confirmed COVID-19 FFP2 or FFP3) settings where patient or providing care in a aerosol generating setting where AGPs are in place procedures (AGP) are for COVID-19 patients. performed Health worker or Home care When in close contact or when a Medical mask caregiver distance of at least 1 m cannot be maintained from a suspect or confirmed COVID-19 patient *This table refers only to the use of medical masks and respirators. The use of medical masks and respirators may need to be combined with other personal protective equipment and other measures as appropriate, and always with hand hygiene.

Alternatives to medical masks in health facilities: Additional considerations for community care settings: Community health workers should use standard precautions In the context of severe medical mask shortage, face shields for all patients at all times, with particular emphasis regarding may be considered as an alternative. The use of cloth masks hand and respiratory hygiene, surface and environmental (referred to as fabric masks in this document) as an alternative cleaning and disinfection, and the appropriate use of personal to medical masks is not considered appropriate for protection protective equipment. Additional IPC measures that are of health workers based on limited available evidence. One needed will depend on the local COVID-19 transmission study that evaluated the use of cloth masks in a health care dynamics and the type of contact required by the health care facility found that health care workers using cotton cloth activity. Furthermore, the community health workforce masks were at increased risk of influenza like illness should ensure that patients and workforce members apply compared with those who wore medical masks.(52) respiratory hygiene, and physical distancing of at least 1

metre (3.3 feet). They also may support set-up, community As for other PPE items, if production of cloth masks for use education and maintenance of hand hygiene stations.(53) in health care settings is proposed locally in situations of When conducting screening activities (e.g., conducting shortage or stock out, a local authority should assess the interviews), no mask is needed if a distance of at least 1 metre proposed PPE according to specific minimum standards and (3.3 feet) can be maintained and there is no direct contact with technical specifications. patients.(42, 53) In the context of known or suspected

-5- Advice on the use of masks in the context of COVID-19: Interim guidance community transmission, consider additional precautions, reported.(64, 65) Older people and including the wearing of a medical mask, when community immunosuppressed patients may present with health workers provide essential routine services (Table 2). atypical symptoms such as fatigue, reduced alertness, reduced mobility, diarrhoea, loss of When a patient is suspected or confirmed to have COVID-19 appetite, delirium, and absence of fever.(26, 66, 67) infection, community health workers should use contact and It is important to note that early symptoms for some droplet precautions. Contact and droplet precautions include people infected with COVID-19 may be very mild the use of a medical mask, gown, gloves and eye and unspecific; protection.(53) • follow instructions on how to put on, take off, and dispose of medical masks and perform hand Guidance on the use of masks for the general public hygiene;(68) • follow all additional measures, in particular Available evidence respiratory hygiene, frequent hand hygiene and Studies of influenza, influenza-like illness, and human maintaining physical distance of at least 1 metre (3.3 coronaviruses (not including COVID-19) provide evidence feet) from other persons.(42) that the use of a medical mask can prevent the spread of infectious droplets from a symptomatic infected person In the context of the COVID-19 pandemic, it is recommended (source control) to someone else and potential contamination that all persons, regardless of whether they are using masks of the environment by these droplets.(54, 55) There is limited or not, should: evidence that wearing a medical mask by healthy individuals • avoid groups of people and crowded spaces (follow in households, in particular those who share a house with a local advice); sick person, or among attendees of mass gatherings may be • maintain physical distance of at least 1 metre (3.3 beneficial as a measure preventing transmission.(41, 56-61) feet) from other persons, especially from those with A recent meta-analysis of these observational studies, with respiratory symptoms (e.g. coughing, sneezing); the intrinsic biases of observational data, showed that either • perform hand hygiene frequently, using an alcohol- disposable surgical masks or reusable 12–16-layer cotton based handrub if hands are not visibly dirty or soap masks were associated with protection of healthy individuals and water; within households and among contacts of cases.(42) • use respiratory hygiene i.e. cover their nose and mouth with a bent elbow or paper tissue when This could be considered to be indirect evidence for the use coughing or sneezing, dispose of the tissue of masks (medical or other) by healthy individuals in the immediately after use, and perform hand hygiene; wider community; however, these studies suggest that such • refrain from touching their mouth, nose, and eyes. individuals would need to be in close proximity to an infected person in a household or at a mass gathering where physical 2) Advice to decision makers on the use of masks for the distancing cannot be achieved, to become infected with the general public virus. Many countries have recommended the use of fabric Results from cluster randomized controlled trials on the use masks/face coverings for the general public. At the present of masks among young adults living in university residences time, the widespread use of masks by healthy people in the in the United States of America indicate that face masks may community setting is not yet supported by high quality or reduce the rate of influenza-like illness, but showed no impact direct scientific evidence and there are potential benefits and on risk of laboratory-confirmed influenza.(62, 63) At harms to consider (see below). present, there is no direct evidence (from studies on COVID- 19 and in healthy people in the community) on the However, taking into account the available studies evaluating effectiveness of universal masking of healthy people in the pre- and asymptomatic transmission, a growing compendium community to prevent infection with respiratory viruses, of observational evidence on the use of masks by the general including COVID-19. public in several countries, individual values and preferences, as well as the difficulty of physical distancing in many WHO regularly monitors all emerging evidence about this contexts, WHO has updated its guidance to advise that to important topic and will provide updates as more information prevent COVID-19 transmission effectively in areas of becomes available. community transmission, governments should encourage the general public to wear masks in specific situations and Guidance settings as part of a comprehensive approach to suppress 1) WHO recommends that persons with any symptoms SARS-CoV-2 transmission (Table 2). suggestive of COVID-19 should (1, 2): • wear a medical mask, self-isolate, and seek medical WHO advises decision makers to apply a risk-based approach advice as soon as they start to feel unwell with focusing on the following criteria when considering or potential symptoms of COVID-19, even if encouraging the use of masks for the general public: symptoms are mild. Symptoms can include: fever, cough, fatigue, loss of appetite, shortness of breath 1. Purpose of mask use: if the intention is preventing the and muscle pain. Other non-specific symptoms such infected wearer transmitting the virus to others (that is, as sore throat, nasal congestion, headache, source control) and/or to offer protection to the healthy diarrhoea, nausea and vomiting, have also been wearer against infection (that is, prevention). reported. Loss of smell and taste preceding the onset of respiratory symptoms have also been

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where individuals are unable to keep a physical distance 2. Risk of exposure to the COVID-19 virus of at least 1 metre (3.3 feet) (e.g. public transportation). ­ due to epidemiology and intensity of transmission in 5. Feasibility: availability and costs of masks, access to the population: if there is community transmission clean water to wash non-medical masks, and ability of and there is limited or no capacity to implement mask wearers to tolerate adverse effects of wearing a other containment measures such as contact tracing, mask. ability to carry out testing and isolate and care for 6. Type of mask: medical mask versus non-medical mask suspected and confirmed cases. ­ depending on occupation: e.g., individuals working Based on these criteria, Table 2 provides practical examples in close contact with the public (e.g., social workers, of situations where the general public should be encouraged personal support workers, cashiers). to wear a mask and it indicates specific target populations and 3. Vulnerability of the mask wearer/population: for the type of mask to be used according to its purpose. The example, medical masks could be used by older people, decision of governments and local jurisdictions whether to immunocompromised patients and people with recommend or make mandatory the use of masks should be comorbidities, such as cardiovascular disease or diabetes based on the above criteria, and on the local context, culture, mellitus, chronic lung disease, cancer and availability of masks, resources required, and preferences of cerebrovascular disease.(69) the population. 4. Setting in which the population lives: settings with high population density (e.g. refugee camps, camp-like settings, those living in cramped conditions) and settings

Table 2. Examples of where the general public should be encouraged to use medical and non-medical masks in areas with known or suspected community transmission

Situations/settings Population Purpose of Type of mask to consider mask use wearing if recommended locally Areas with known or suspected General population in public settings, such Potential Non-medical mask widespread transmission and limited or as grocery stores, at work, social benefit for no capacity to implement other gatherings, mass gatherings, closed source control containment measures such as settings, including schools, churches, physical distancing, contact tracing, mosques, etc. appropriate testing, isolation and care for suspected and confirmed cases. Settings with high population density People living in cramped conditions, and Potential Non-medical mask where physical distancing cannot be specific settings such as refugee camps, benefit for achieved; surveillance and testing camp-like settings, slums source control capacity, and isolation and quarantine facilities are limited Settings where a physical distancing General public on transportation (e.g., on a Potential Non-medical mask cannot be achieved (close contact) bus, plane, trains) benefit for source control Specific working conditions which places the employee in close contact or potential close contact with others e.g., social workers, cashiers, servers Settings where physical distancing Vulnerable populations: Protection Medical mask cannot be achieved and increased risk • of infection and/or negative outcomes People aged ≥60 years • People with underlying comorbidities, such as cardiovascular disease or diabetes mellitus, chronic lung disease, cancer, cerebrovascular disease, immunosuppression Any setting in the community* Persons with any symptoms suggestive of Source control Medical mask COVID-19 *This applies to any transmission scenario

Potential benefits/advantages • reduced potential stigmatization of individuals wearing masks to prevent infecting others (source control) or of The likely advantages of the use of masks by healthy people people caring for COVID-19 patients in non-clinical in the general public include: settings;(70) • reduced potential exposure risk from infected persons • making people feel they can play a role in contributing to before they develop symptoms; stopping spread of the virus;

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• reminding people to be compliant with other measures • consider the feasibility of use, supply/access issues, (e.g., hand hygiene, not touching nose and mouth). social and psychological acceptance (of both wearing However, this can also have the reverse effect (see and not wearing different types of masks in different below); contexts); • potential social and economic benefits. Amidst the • continue gathering scientific data and evidence on the global shortage of surgical masks and PPE, encouraging effectiveness of mask use (including different types and the public to create their own fabric masks may promote makes as well as other face covers such as scarves) in individual enterprise and community integration. non-health care settings; Moreover, the production of non-medical masks may • evaluate the impact (positive, neutral or negative) of offer a source of income for those able to manufacture using masks in the general population (including masks within their communities. Fabric masks can also behavioral and social sciences). be a form of cultural expression, encouraging public acceptance of protection measures in general. The safe re-use of fabric masks will also reduce costs and waste WHO encourages countries and community adopting policies and contribute to sustainability. on masks use in the general public to conduct good quality research to assess the effectiveness of this intervention to prevent and control transmission. Potential harms/disadvantages 3) Types of mask to consider The likely disadvantages of the use of mask by healthy people in the general public include: Medical mask Medical masks should be certified according to international • potential increased risk of self-contamination due to the or national standards to ensure they offer predictable product manipulation of a face mask and subsequently touching performance when used by health workers, according to the eyes with contaminated hands;(48, 49) risk and type of procedure performed in a health care setting. • potential self-contamination that can occur if non- Designed for single use, a medical mask’s initial filtration (at medical masks are not changed when wet or soiled. This least 95% droplet filtration), breathability and, if required, can create favourable conditions for microorganism to fluid resistance are attributed to the type (e.g. spunbond or amplify; meltblown) and layers of manufactured non-woven materials • potential headache and/or breathing difficulties, (e.g. polypropylene, polyethylene or cellulose). Medical depending on type of mask used; masks are rectangular in shape and comprise three or four • potential development of facial skin lesions, irritant layers. Each layer consists of fine to very fine fibres. These dermatitis or worsening acne, when used frequently for masks are tested for their ability to block droplets (3 long hours;(50) micrometres in size; EN 14683 and ASTM F2100 standards) • difficulty with communicating clearly; and particles (0.1 micrometre in size; ASTM F2100 standard

• potential discomfort;(41, 51) only). The masks must block droplets and particles while at • a false sense of security, leading to potentially lower the same time they must also be breathable by allowing air to adherence to other critical preventive measures such as pass. Medical masks are regulated medical devices and physical distancing and hand hygiene; categorized as PPE. • poor compliance with mask wearing, in particular by young children; The use of medical masks in the community may divert this critical resource from the health workers and others who need • waste management issues; improper mask disposal leading to increased litter in public places, risk of them the most. In settings where medical masks are in short supply, contamination to street cleaners and environment hazard; medical masks should be reserved for health workers and at-risk individuals when indicated. • difficulty communicating for deaf persons who rely on lip reading; • disadvantages for or difficulty wearing them, especially Non-medical mask for children, developmentally challenged persons, those with mental illness, elderly persons with cognitive Non-medical (also referred to as “fabric” in this document) impairment, those with asthma or chronic respiratory or masks are made from a variety of woven and non-woven breathing problems, those who have had facial trauma or fabrics, such as polypropylene. Non-medical masks may be recent oral maxillofacial surgery, and those living in hot made of different combinations of fabrics, layering sequences and humid environments. and available in diverse shapes. Few of these combinations have been systematically evaluated and there is no single If masks are recommended for the general public, the design, choice of material, layering or shape among the non- decision-maker should: medical masks that are available. The unlimited combination • clearly communicate the purpose of wearing a mask, of fabrics and materials results in variable filtration and where, when, how and what type of mask should be worn. breathability. Explain what wearing a mask may achieve and what it A non-medical mask is neither a medical device nor personal will not achieve, and communicate clearly that this is one protective equipment. However, a non-medical mask part of a package of measures along with hand hygiene, standard has been developed by the French Standardization physical distancing and other measures that are all Association (AFNOR Group) to define minimum necessary and all reinforce each other; performance in terms of filtration (minimum 70% solid • inform/train people on when and how to use masks safely particle filtration or droplet filtration) and breathability (see mask management and maintenance sections), i.e. (maximum pressure difference of 0.6 mbar/cm2 or maximum put on, wear, remove, clean and dispose;

-8- Advice on the use of masks in the context of COVID-19: Interim guidance inhalation resistance of 2.4 mbar and maximum exhalation cloth fabrics and masks has been shown to vary between 0.7% resistance of 3 mbar).(71) and 60%.(73, 74) The higher the filtration efficiency the more of a barrier provided by the fabric. The lower filtration and breathability standardized requirements, and overall expected performance, indicate that Breathability is the ability to breathe through the material of the use of non-medical masks, made of woven fabrics such as the mask. Breathability is the difference in pressure across the cloth, and/or non-woven fabrics, should only be considered mask and is reported in millibars (mbar) or Pascals (Pa) or, for source control (used by infected persons) in community for an area of mask, over a square centimeter (mbar/cm2 or settings and not for prevention. They can be used ad-hoc for Pa/cm2). Acceptable breathability of a medical mask should specific activities (e.g., while on public transport when be below 49 Pa/cm2. For non-medical masks, an acceptable physical distancing cannot be maintained), and their use pressure difference, over the whole mask, should be below should always be accompanied by frequent hand hygiene and 100 Pa.(73) physical distancing. Depending on fabric used, filtration efficiency and Decision makers advising on type of non-medical mask breathability can complement or work against one another. should take into consideration the following features of non- Recent data indicate that two non-woven spunbond layers, the medical masks: filtration efficiency (FE), or filtration, same material used for the external layers of disposable breathability, number and combination of material used, medical masks, offer adequate filtration and breathability. shape, coating and maintenance. Commercial cotton fabric masks are in general very breathable but offer lower filtration.(75) The filter quality a) Type of materials: filtration efficiency (FE), factor known as “Q” is a commonly used filtration quality breathability of single layers of materials, filter factor; it is a function of filtration efficiency (filtration) and quality factor breathability, with higher values indicating better overall The selection of material is an important first step as the efficiency.(76) Table 3 shows FE, breathability and the filter filtration (barrier) and breathability varies depending on the quality factor, Q, of several fabrics and non-medial fabric. Filtration efficiency is dependent on the tightness of masks.(73, 77) According to expert consensus three (3) is the the weave, fibre or thread diameter, and, in the case of non- minimum Q factor recommended. This ranking serves as an woven materials, the manufacturing process (spunbond, initial guide only. meltblown, electrostatic charging).(49, 72) The filtration of

Table 3. Non-medical mask filtration efficiency, pressure drop and filter quality factor*

Filter quality Initial Filtration Initial Pressure Material Source Structure factor, Q ** Efficiency (%) drop (Pa) (kPa-1) Interfacing material, Spunbond Polypropylene 6 1.6 16.9 purchased as-is (Nonwoven) Cotton 1 Clothing (T-shirt) Woven 5 4.5 5.4 Cotton 2 Clothing (T-shirt) Knit 21 14.5 7.4 Cotton 3 Clothing (Sweater) Knit 26 17 7.6 Polyester Clothing (Toddler wrap) Knit 17 12.3 6.8 Cellulose Tissue paper Bonded 20 19 5.1 Cellulose Paper towel Bonded 10 11 4.3 Silk Napkin Woven 4 7.3 2.8 Cotton, gauze N/A Woven 0.7 6.5 0.47 Cotton, handkerchief N/A Woven 1.1 9.8 0.48 Nylon Clothing (Exercise pants) Woven 23 244 0.4 * This table refers only to materials reported in experimental peer-reviewed studies. The filtration efficiency, pressure drop and Q factor are dependent on flow rate. ** According to expert consensus, three (3) is the minimum Q factor recommended.

It is preferable not to select elastic material for making masks; Fabric cloths (e.g., nylon blends and 100% polyester) when during wear, the mask material may be stretched over the folded into two layers, provides 2-5 times increased filtration face, resulting in increased pore size and lower filtration efficiency compared to a single layer of the same cloth, and efficiency throughout use. Also, elastic materials may filtration efficiency increases 2-7 times if it is folded into 4 degrade over time and are sensitive to washing at high layers.(75) Masks made of cotton handkerchiefs alone should temperatures. consist of at least 4 layers, but have achieved only 13% filtration efficiency.(73) Very porous materials, such as b) Number of layers gauze, even with multiple layers will not provide sufficient A minimum of three layers is required for non-medical filtration; only 3% filtration efficiency. (73) masks, depending on the fabric used. The innermost layer of the mask is in contact with the wearer’s face. The outermost It is important to note that with more tightly woven materials, layer is exposed to the environment.(78) as the number of layers increases, the breathability may be

-9- Advice on the use of masks in the context of COVID-19: Interim guidance reduced. A quick check for breathability may be performed Non-medical masks should be washed frequently and handled by attempting to breathe, through the mouth, and through the carefully, so as not to contaminate other items. multiple layers. If the layers of fabrics look noticeably worn out, discard the c) Combination of material used mask. The ideal combination of material for non-medical masks Clothing fabrics used to make masks should be checked for should include three layers as follows: 1) an innermost layer the highest permitted washing temperature. If instructions for of a hydrophilic material (e.g. cotton or cotton blends); 2), an washing are indicated on the clothing label, verify if washing outermost layer made of hydrophobic material (e.g., in warm or hot water is tolerated. Select washable fabrics that polypropylene, polyester, or their blends) which may limit can be washed. Wash in warm hot water, 60°C, with soap or external contamination from penetration through to the laundry detergent. Non-woven polypropylene (PP) spunbond wearer’s nose and mouth; 3) a middle hydrophobic layer of may be washed at high temperatures, up to 125°C.(72) synthetic non-woven material such as polyproplylene or a Natural fibres may resist high temperature washes and cotton layer which may enhance filtration or retain droplets. ironing. Wash the mask delicately (without too much friction, d) Mask shape stretching or wringing) if nonwoven materials (e.g. Mask shapes include flat-fold or duckbill and are designed to spunbond) are used. The combination of non-woven PP fit closely over the nose, cheeks and chin of the wearer. When spunbond and cotton can tolerate high temperatures; masks the edges of the mask are not close to the face and shift, for made of these combinations may be steamed or boiled. example, when speaking, internal/external air penetrates Where hot water is not available, wash mask with through the edges of the mask rather than being filtered soap/detergent at room temperature water, followed by either through the fabric. Leaks where unfiltered air moves in and i) boiling mask for one minute OR ii) soak mask in 0.1% out of the mask may be attributed to the size and shape of the chlorine for one minute then thoroughly rinse mask with mask.(79) room temperature water, to avoid any toxic residual of It is important to ensure that the mask can be held in place chlorine. comfortably with little adjustment using elastic bands or ties. WHO is collaborating with research and development e) Coating of fabric partners and the scientific community engaged in textile Coating the fabric with compounds like wax may increase the engineering and fabric design to facilitate a better barrier and render the mask fluid resistant; however, such understanding of the effectiveness and efficiency of non- coatings may inadvertently completely block the pores and medical masks. WHO urges countries that have issued make the mask difficult to breathe through. In addition to recommendations on the use of both medical and non-medical decreased breathability unfiltered air may more likely escape masks by healthy people in community settings to conduct the sides of the mask upon exhalation. Coating is therefore research on this important topic. Such research needs to look not recommended. at whether SARS-CoV-2 particles can be expelled through non-medical masks of poor quality worn by a person with f) Mask maintenance symptoms of COVID-19 while that person is coughing, Masks should only be used by one person and should not sneezing or speaking. Research is also needed on non- be shared. medical mask use by children and other medically All masks should be changed if wet or visibly soiled; a wet challenging persons and settings as mentioned above. mask should not be worn for an extended period of time. Remove the mask without touching the front of the mask, do Table 4 provides a summary of guidance and practical not touch the eyes or mouth after mask removal. Either considerations on the composition, construction and discard the mask or place it in a sealable bag where it is kept management of non-medical masks. until it can be washed and cleaned. Perform hand hygiene immediately afterwards.

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Table 4. Summary guidance and practical considerations for non-medical mask production and management

Guidance and practical considerations Fabric selection: Choose materials that capture particles and droplets but remain easy to breathe through. Avoid stretchy material for making masks as they provide lower filtration efficiency during use and are sensitive to washing at high temperatures. Fabrics that can support high temperatures (60° or more) are preferable. Construction: A minimum of three layers is required, depending on the fabric used: an inner layer touching the mouth and an outer layer that is exposed to the environment. Choose water-absorbing (hydrophilic) materials or fabrics for the internal layers, to readily absorb droplets, combined with an external synthetic material that does not easily absorb liquid (hydrophobic). Mask management: Masks should only be used by one person. All masks should be changed if soiled or wet; a soiled or wet mask should not be worn for an extended period of time. Non-medical masks should be washed frequently and handled carefully, so as not to contaminate other items. Clothing fabrics used to make masks should be checked for the highest permitted washing temperature, which is indicated on the clothing label. Non-woven polypropylene (PP) spunbond may be washed at high temperature, up to 140°C. The combination of non-woven PP spunbond and cotton can tolerate high temperatures; masks made of these combinations may be steamed or boiled. Where hot water is not available, wash mask with soap/detergent at room temperature water, followed by either i) boiling mask for one minute OR ii) soak mask in 0.1% chlorine for one minute then thoroughly rinse mask with room temperature water, to avoid any toxic residual of chlorine.

3. Alternatives to non-medical masks for the general Persons with suspected COVID-19 or mild COVID-19 public symptoms and no risk factors should: In the context of non-medical mask shortage, face shields • may be considered as an alternative noting that they are be isolated in a medical facility if confirmed, or self- inferior to mask with respect to prevention of droplet isolate at home if isolation in a medical or other transmission. If face shields are to be used, ensure proper designated facility is not indicated or not possible; design to cover the sides of the face and below the chin. In • perform hand and respiratory hygiene frequently; addition, they may be easier to wear for individuals with • keep a distance of at least 1 metre (3.3 feet) from other limited compliance with medical masks (such as those with people; mental health disorders, developmental disabilities, deaf and • wear a medical mask as much as possible; the mask hard of hearing community and children). should be changed at least once daily. Persons who cannot tolerate a medical mask should rigorously apply respiratory hygiene (i.e. cover mouth and nose with a disposable paper tissue when coughing or sneezing and Guidance on the use of medical masks for the care of dispose of it immediately after use or use a bent elbow COVID-19 patients at home procedure and then perform hand hygiene); • limit movement and minimize shared space; WHO provides guidance on how to care for patients with • avoid contaminating surfaces with saliva, sputum or confirmed and suspected COVID-19 at home when care in a respiratory secretions; health facility or other residential setting is not possible.(4) • improve airflow and ventilation in their living space by Home care may be considered when inpatient care or opening windows and doors as much as possible; isolation in non-traditional settings is unavailable or unsafe • ensure adequate cleaning and disinfection of touch (e.g. capacity is limited and resources are unable to meet the surfaces, near where the patient is being cared for, such demand for care services). If feasible, a trained health worker as bedside tables, bedframes, and other bedroom should conduct an assessment to verify whether the patient furniture; electronic touchscreens, keyboards, and and the family are able to comply with recommended controls; and bathroom fixtures. measures for home-care isolation (e.g. hand hygiene, respiratory hygiene, environmental cleaning, limitations on Caregivers or those sharing living space with people with movement around or from the house) and to address safety suspected COVID-19 or with mild COVID-19 symptoms concerns (e.g. accidental ingestion of and fire hazards should: associated with using alcohol-based handrubs). Specific IPC guidance for home care should be followed. (4) • perform hand hygiene according to the 5 Moments of Hand Hygiene,(80) using an alcohol-based handrub if hands are not visibly dirty or soap and water when hands are visibly dirty;

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• keep a distance of at least 1 m from the affected person 3. Infection prevention and control for long-term care when possible; facilities in the context of COVID-19: interim guidance. • wear a medical mask when in the same room as the Geneva: World Health Organization; 2020 affected person; (https://www.who.int/publications-detail/infection- • dispose of any material contaminated with respiratory prevention-and-control-for-long-term-care-facilities-in-the- secretions (disposable tissues) immediately after use and context-of-covid-19, accessed 4 June 2020). then perform hand hygiene; 4. Home care for patients with COVID-19 presenting • improve airflow and ventilation in the living space by with mild symptoms and management of contacts: interim opening windows as much as possible; guidance. Geneva: World Health Organization; 2020 • ensure adequate cleaning and disinfection of touch (https://apps.who.int/iris/handle/10665/331133, accessed 4 surfaces in the patient’s room, such as bedside tables, June 2020). bedframes and other bedroom furniture; electronic touchscreens, keyboards, and controls; and bathroom 5. Liu J, Liao X, Qian S, Yuan J, Wang F, Liu Y, et al. fixtures. Community Transmission of Severe Acute Respiratory Syndrome Coronavirus 2, Shenzhen, China, 2020. Emerg Infect Dis. 2020;26(6):1320-3. Guidance on mask management 6. Chan JF, Yuan S, Kok KH, To KK, Chu H, Yang J, et For any type of mask, appropriate use and disposal are al. A familial cluster of pneumonia associated with the 2019 essential to ensure that they are as effective as possible and to novel coronavirus indicating person-to-person transmission: avoid any increase in transmission. a study of a family cluster. Lancet. 2020;395(10223):514- 23. WHO offers the following guidance on the correct use of masks, derived from best practices in health care settings: 7. Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early Transmission Dynamics in Wuhan, China, of Novel • perform hand hygiene before putting on the mask; Coronavirus-Infected Pneumonia. N Engl J Med. • place the mask carefully, ensuring it covers the mouth 2020;382(13):1199-207. and nose, adjust to the nose bridge, and tie it securely to minimize any gaps between the face and the mask; 8. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. • avoid touching the mask while wearing it; Clinical features of patients infected with 2019 novel • remove the mask using the appropriate technique: do not coronavirus in Wuhan, China. Lancet. touch the front of the mask but untie it from behind. 2020;395(10223):497-506. • after removal or whenever a used mask is inadvertently 9. Burke RM, Midgley CM, Dratch A, Fenstersheib M, touched, clean hands with an alcohol-based handrub, or Haupt T, Holshue M, et al. Active Monitoring of Persons soap and water if hands are visibly dirty; Exposed to Patients with Confirmed COVID-19 - United • replace masks as soon as they become damp with a new States, January-February 2020. MMWR Morb Mortal Wkly clean, dry mask; Rep. 2020;69(9):245-6. • do not re-use single-use masks; • discard single-use masks after each use and dispose of 10. Coronavirus disease 2019 (COVID-19) Situation them immediately upon removal. Report – 73. Geneva: World Health Organization; 2020 (https://www.who.int/docs/default- source/coronaviruse/situation-reports/20200402-sitrep-73- WHO continues to monitor the situation closely for any covid-19.pdf?sfvrsn=5ae25bc7_6, accessed 4 June 2020). changes that may affect this interim guidance. Should any 11. Cheng VCC, Wong SC, Chen JHK, Yip CCY, Chuang factors change, WHO will issue a further update. Otherwise, VWM, Tsang OTY, et al. Escalating infection control this interim guidance document will expire 2 years after the response to the rapidly evolving epidemiology of the date of publication. coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 in Hong Kong. Infect Control Hosp Epidemiol. 2020;41(5):493-8. References 12. Ong SWX, Tan YK, Chia PY, Lee TH, Ng OT, Wong 1. Infection prevention and control of epidemic and MSY, et al. Air, Surface Environmental, and Personal pandemic-prone respiratory infections in health care. Protective Equipment Contamination by Severe Acute Geneva: World Health Organization; 2014 Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) From (https://www.who.int/csr/bioriskreduction/infection_control/ a Symptomatic Patient. JAMA. 2020. publication/en/, accessed 13 May 2020). 13. Guo ZD, Wang ZY, Zhang SF, Li X, Li L, Li C, et al. 2. Infection prevention and control during health care Aerosol and Surface Distribution of Severe Acute when COVID-19 is suspected: interim guidance. Geneva: Respiratory Syndrome Coronavirus 2 in Hospital Wards, World Health Organization; 2020 Wuhan, China, 2020. Emerg Infect Dis. 2020;26(7). (https://www.who.int/publications-detail/infection- prevention-and-control-during-health-care-when-novel- 14. Chia PY, Coleman KK, Tan YK, Ong SWX, Gum M, coronavirus-(ncov)-infection-is-suspected-20200125, Lau SK, et al. Detection of air and surface contamination by accessed 4 June 2020). SARS-CoV-2 in hospital rooms of infected patients. Nat Commun. 2020;11(1):2800.

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SPEC S76-001: Masque barrière. alphabetical order): Guide d’exigence minimales, de méthode d’essais, de confection et d’usage. (https://masques- Jameela Alsalman, Ministry of Health, Bahrain; Anucha barrieres.afnor.org/home/telechargement, accessed 4 June Apisarnthanarak, Thammsat University Hospital, Thailand; 2020). Baba Aye, Public Services International, France; Gregory Built, UNICEF, United States of America (USA); Roger 72. Liao L, Xiao W, Zhao M, Yu X, Wang H, Wang Q, et Chou, Oregon Health Science University, USA; May Chu, al. Can N95 Respirators Be Reused after Disinfection? How Colorado School of Public Health, USA; John Conly, Alberta Many Times? ACS Nano. 2020;14(5):6348-56. Health Services, Canada; Barry Cookson, University College 73. Jung, H., Kim, J.K., Lee, S., Lee, J., Kim, J., Tsai, P., London, United Kingdom; Nizam Damani, Southern Health et al., 2014. Comparison of Filtration Efficiency and & Social Care Trust, United Kingdom; Dale Fisher, Goarn, Pressure Drop in Anti-Yellow Sand Masks, Quarantine Singapore; Joost Hopman, Radboud University Medical Masks, Medical Masks, General Masks, and Handkerchiefs. Center, The Netherlands; Mushtuq Husain, Institute of Aerosol Air Qual. Res. 14, 991–1002. Epidemiology, Disease Control & Research, Bangladesh; (https://doi.org/10.4209/aaqr.2013.06.0201, accessed 4 June Kushlani Jayatilleke, Sri Jayewardenapura General Hospital, 2020). Sri Lanka; Seto Wing Jong, School of Public Health, Hong 74. Rengasamy S, Eimer B, Shaffer RE. Simple respiratory Kong SAR, China; Souha Kanj, American University of protection--evaluation of the filtration performance of cloth Beirut Medical Center, Lebanon; Daniele Lantagne, Tufts masks and common fabric materials against 20-1000 nm University, USA; Fernanda Lessa, Centers for Disease size particles. Ann Occup Hyg. 2010;54(7):789-98. Control and Prevention, USA; Anna Levin, University of São 75. Jang JY, Kim, S.W., . Evaluation of Filtration Paulo, Brazil; Ling Moi Lin, Sing Health, Singapore; Caline Performance Efficiency of Commercial Cloth Masks Journal Mattar, World Health Professions Alliance, USA; Mary- Louise McLaws, University of New South Wales, Australia; of Environmental Health Sciences (한국환경보건학회지) Geeta Mehta, Journal of Patient Safety and Infection Control, Volume 41 Issue 3 / Pages203-215 / 2015. 2015. India; Shaheen Mehtar, Infection Control Africa Network, South Africa; Ziad Memish, Ministry of Health, Saudi Arabia; Babacar Ndoye, Infection Control Africa Network, Senegal; Fernando Otaiza, Ministry of Health, Chile; Diamantis

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Plachouras, European Centre for Disease Prevention and Spallanzani, Italy; Marimuthu Kalisvar, Tan Tock Seng Control, Sweden; Maria Clara Padoveze, School of Nursing, Hospital, Singapore; Dan Lebowitz, Hopitaux Universitaires University of São Paulo, Brazil; Mathias Pletz, Jena de Geneve, Switzerland; Outi Lyytikainen, Finland; Trish University, Germany; Marina Salvadori, Public Health Perl, UT Southwestern, USA; F. Mauro Orsini, Ministry of Agency of Canada, Canada; Mitchell Schwaber, Ministry of Health, Santiago, Chile; Didier Pittet, University of Geneva Health, Israel; Nandini Shetty, Public Health England, United Hospitals, and Faculty of Medicine, Geneva, Switzerland; Kingdom; Mark Sobsey, University of North Carolina, USA; Benjamin Park, Centers for Disease Control and Prevention, Paul Ananth Tambyah, National University Hospital, USA; Amy Price, Stanford University School of Medicine, Singapore; Andreas Voss, Canisus-Wilhelmina Ziekenhuis, USA; Supriya Sharma, Public Health Canada; Nalini Singh, The Netherlands; Walter Zingg, University of Geneva The George Washington University, USA; Rachel Smith, Hospitals, Switzerland; Centers for Disease Control and Prevention, USA; Jorgen Stassinjns, Médecins Sans Frontières, The Netherlands; Sara 2) the WHO Health Emergencies Programme (WHE) Ad- Tomczyk, Robert Koch Institute, Germany. hoc Experts Advisory Panel for Infection Prevention and Control (IPC) Preparedness, Readiness and Response to COVID-19, and other international experts including (in alphabetical order): The WHO Secretariat: Benedetta Allegranzi, Gertrude Avortri, Mekdim Ayana, Hanan Balkhy, April Baller, Mardjan Arvand, Robert Koch Institute Nordufer, Denmark; Elizabeth Barrera-Cancedda, Anjana Bhushan, Sylvie Briand, Elizabeth Bancroft, Centers for Disease Control and Alessandro Cassini, Giorgio Cometto, Ana Paula Coutinho Prevention, USA; Gail Carson, ISARIC Global Support Rehse, Carmem Da Silva, Nino Dal Dayanguirang, Sophie Centre, United Kingdom; Larry Chu, Stanford University Harriet Dennis, Sergey Eremin, Dennis Nathan Ford, Jonas School of Medicine, USA; Shan-Chwen Chang, National Gonseth-Garcia, Rebeca Grant, Tom Grein, Ivan Ivanov, Taiwan University, Taiwan, Feng-Yee Chang, National Landry Kabego, Pierre Claver Kariyo, Ying Ling Lin, Ornella Defense Medical Center, Taiwan, Steven Chu, Stanford Lincetto, Madison Moon, Takeshi Nishijima, Kevin Babila University, USA; Yi Cui, Stanford University, USA; Jane Ousman, Pillar Ramon-Pardo, Paul Rogers, Nahoko Shindo, Davies, Médecins Sans Frontières, The Netherlands; Alice Simniceanu, Valeska Stempliuk, Maha Talaat Ismail, Katherine Defalco, Public Health Agency of Canada, Canada; Joao Paulo Toledo, Anthony Twywan, Maria Van Kerkhove, Kathleen Dunn, Public Health Agency of Canada; Janine Vicky Willet, Masahiro Zakoji, Bassim Zayed. Goss, Public Health England, United Kingdom; Alison Holmes, Imperial College, United Kingdom; Paul Hunter, University of East Anglia, United Kingdom; Giuseppe Ippolito, Instituto Nazionale per le Malattie Infettive Lazzaro

© World Health Organization 2020. Some rights reserved. This work is available under the CC BY-NC-SA 3.0 IGO licence.

WHO reference number: WHO/2019-nCov/IPC_Masks/2020.4

-16- Journal of Infection 81 (2020) 107–114

Contents lists available at ScienceDirect

Journal of Infection

journal homepage: www.elsevier.com/locate/jinf

The role of community-wide wearing of face mask for control of coronavirus disease 2019 (COVID-19) epidemic due to SARS-CoV-2

Vincent Chi-Chung Cheng a,b, Shuk-Ching Wong b, Vivien Wai-Man Chuang c,

Simon Yung-Chun So a, Jonathan Hon-Kwan Chen a, Siddharth Sridhar d,

Kelvin Kai-Wang To d, Jasper Fuk-Woo Chan d, Ivan Fan-Ngai Hung e, Pak-Leung Ho d, ∗ Kwok-Yung Yuen d, a Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China b Infection Control Team, Queen Mary Hospital, Hong Kong West Cluster, Hong Kong Special Administrative Region, China c Quality & Safety Division (Infection, Emergency, and Contingency), Hospital Authority, Hong Kong Special Administrative Region, China d Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China e Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China

a r t i c l e i n f o s u m m a r y

Article history: Background: Face mask usage by the healthy population in the community to reduce risk of transmission Accepted 17 April 2020 of respiratory viruses remains controversial. We assessed the effect of community-wide mask usage to

Available online 23 April 2020 control coronavirus disease 2019 (COVID-19) in Hong Kong Special Administrative Region (HKSAR).

Keywords: Methods: Patients presenting with respiratory symptoms at outpatient clinics or hospital wards were

Face mask screened for COVID-19 per protocol. Epidemiological analysis was performed for confirmed cases, espe- Community cially persons acquiring COVID-19 during mask-off and mask-on settings. The incidence of COVID-19 per Coronavirus million population in HKSAR with community-wide masking was compared to that of non-mask-wearing COVID-19 countries which are comparable with HKSAR in terms of population density, healthcare system, BCG vac- SARS-COV-2 cination and social distancing measures but not community-wide masking. Compliance of face mask us-

Epidemic age in the HKSAR community was monitored. Findings: Within first 100 days (31 December 2019 to 8 April 2020), 961 COVID-19 patients were diag- nosed in HKSAR. The COVID-19 incidence in HKSAR (129.0 per million population) was significantly lower ( p < 0.001) than that of Spain (2983.2), Italy (2250.8), Germany (1241.5), France (1151.6), U.S. (1102.8), U.K. (831.5), Singapore (259.8), and South Korea (200.5). The compliance of face mask usage by HKSAR gen- eral public was 96.6% (range: 95.7% to 97.2%). We observed 11 COVID-19 clusters in recreational ‘mask-off’ settings compared to only 3 in workplace ‘mask-on’ settings ( p = 0.036 by Chi square test of goodness-of- fit). Conclusion: Community-wide mask wearing may contribute to the control of COVID-19 by reducing the amount of emission of infected saliva and respiratory droplets from individuals with subclinical or mild COVID-19. ©2020 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

Introduction clared COVID-19 to be a pandemic on 11 March 2020, 2 which is 72 days after the first official announcement of clusters of patients Coronavirus disease 2019 (COVID-19) due to severe acute respi- with community-acquired pneumonia in Wuhan, Hubei Province of ratory syndrome coronavirus 2 (SARS-CoV-2), which is closely re- China on 31 December 2019 (day 1). 3 As of 8 April 2020 (day 100), lated to bat SARS related coronaviruses, 1 is the second pandemic over 1.35 million people have been infected worldwide with nearly of the 21st century following the influenza A H1N1 pandemic of 80,0 0 0 deaths. 4 In response, proactive infection control measures 2009. With the rapidly galloping epidemic due to globalization have been implemented in hospital settings. 5 , 6 In addition, non- and international travel, World Health Organization (WHO) de- pharmaceutical public health interventions including border con- trol or closure, quarantine and testing of all incoming travelers or returnees, massive reverse-transcription polymerase chain reaction ∗ Corresponding author. (RT-PCR) testing for case detection, rapid contact tracing and quar- E-mail address: [email protected] (K.-Y. Yuen). antine, frequent hand hygiene, and later social distancing measures https://doi.org/10.1016/j.jinf.2020.04.024 0163-4453/© 2020 The British Infection Association. Published by Elsevier Ltd. All rights reserved. 108 V.C.-C. Cheng, S.-C. Wong and V.W.-M. Chuang et al. / Journal of Infection 81 (2020) 107–114 including school closure, home office, cancelation of all mass gath- Comparing the epidemiology of COVID-19 in HKSAR and other parts erings, later stay-at-home order, and cessation of all socioeconomic of the world activities except essential services, were also adopted to various degrees and at different time points in different geographical ar- The epidemiology of COVID-19 of HKSAR was compared to that eas to reduce the risk of community transmission. Many of these of the representative countries in North America, Europe, and Asia measures had been used for the control of community transmis- using publicly accessible information from the website of WHO to sion of severe acute respiratory syndrome (SARS) in 2003 and pan- understand the overall effect of our control measures used in HK- demic influenza A H1N1 in 2009 in Hong Kong Special Adminis- SAR. Countries with well-established healthcare system, where face trative Region of China (HKSAR) and other parts of the world. 7 , 8 mask usage was not universally adopted in the community, and However, the efficacy of community-wide masking of the popu- having over 100 confirmed cases at day 72 when WHO declared a lation during these past epidemics or the present COVID-19 pan- pandemic were selected for comparison. demic has not been clearly investigated. Unlike 2003 SARS which was generally manifested with high fever and progressive pneumo- Laboratory diagnosis of SARS-CoV-2 nia with a mortality of about 10%, COVID-19 can be associated with very mild symptoms and a mortality of less than 4%. Thus sub- Clinical specimens including nasopharyngeal aspirates, na- clinical or asymptomatic SARS-CoV-2 shedders may play an impor- sopharyngeal swabs, throat swab, saliva, sputum, endotracheal as- tant role in perpetuating the pandemic. 9 , 10 We hypothesized that pirates, or bronchoalveolar lavage were subjected to nucleic acid community-wide masking in HKSAR may break the chain of trans- extraction by the eMAG extraction system (bioMérieux, Marcy- mission of SARS-CoV-2 by reducing the infectiousness of the sub- l’Étoile France) as we previously described. 5 , 6 The presence of clinical virus shedders while also offering some protection to the SARS-CoV-2 RNA in specimens was first determined by the Light- susceptible population. Mix Modular SebeccoV E-gene commercial kit (TIB Molbiol, Berlin, In HKSAR, community-wide masking was practiced by the gen- Germany) at all public hospitals under the Hospital Authority and eral population at an early stage of the local COVID-19 epidemic. the Public Health Laboratory Service of the Department of Health, Here, we described the comparative epidemiology of COVID-19 and further confirmed by in-house real-time RT-PCR assay target- during the first 100 days. We also analyzed the incidence of ing the SARS-CoV-2 RNA-dependent RNA polymerase/helicase gene COVID-19 in geographical areas with or without community-wide as described. 11 masking for most individuals, and also the number of COVID-19 clusters of COVID-19 in relation to workplace (mask-on setting) or Statistical analysis non-workplace recreational settings (mask-off setting) of HKSAR. Incidence rates were compared using the exact Poisson test us- ing R software. Proportions were compared using the chi-squared Methods test. A p value of < 0.05 was considered statistically significant. Community control measures against COVID-19 in HKSAR Results HKSAR is a cosmopolitan city of 7.45 million people in Southern Community response to COVID-19 in HKSAR China. Occupying only 1104 square-kilometers, it is the third most densely populated area in the world with around 6700 people per Due to the prior experience of the SARS outbreak in 2003, the square-kilometer. Soon after the official announcement of a cluster general public of HKSAR was on high alert after the official an- of patients with community-acquired pneumonia in Wuhan by the nouncement of a cluster of pneumonia cases of unknown etiology National Health Commission of the People’s Republic of China, on in Wuhan on 31 December 2019 (day 1), because a total of 1755 in- 31 December 2019 (day 1), the center for Health Protection (CHP) fected persons with 299 (17.0%) deaths over 133 days (11 February of the Department of Health, the HKSAR government alerted mem- 2003 to 23 June 2003) was recorded during this past SARS epi- bers of the public to maintain good personal and environmental demic. When the causative agent of COVID-19 was identified on hygiene, with specific emphasis on hand hygiene, refraining from 9 January 2020 (day 10), and named as SARS-CoV-2 on 12 Febru- work or attending class at school, avoiding crowded places, seek ary 2020 (day 44), this emerging pathogen was perceived to be medical advice promptly and wear a surgical mask if they develop as detrimental as 2003 SARS-CoV by the HKSAR general public. respiratory symptoms. 3 Step-wise introduction of other commu- Even though initially HKSAR government only advocated people nity interventions later to control the spread of COVID-19 was de- with respiratory symptoms to wear a surgical mask according to scribed. As an objective parameter of community-wide prepared- the recommendations of WHO and Centers for Disease Control and ness, compliance of face mask usage by the general public moni- Prevention (CDC) of the United States, the general public volun- tored by staff working in Infection Control Unit, and Department of teered to wear face mask quite compliantly from the pre-pandemic Microbiology, Queen Mary Hospital for three consecutive days from to pandemic phase of COVID-19. 6 April to 8 April 2020 (day 98 to day 100). Each staff member Sixty-seven staff members (9 from Infection Control Unit, and would count the number of persons not wearing a mask among 58 from Department of Microbiology), residing in all 18 admin- the first 50 persons encountered in the street during their morn- istrative districts in HKSAR, recorded the number of persons not ing commute. The residential district of the staff was recorded. wearing face mask among the first 50 people they encountered during their morning commute to Queen Mary Hospital (located Epidemiology of COVID-19 in HKSAR in Southern district) between 7:00am to 9:00am over three con- secutive days from 6 April to 8 April 2020 (day 98 to day 100). A multi-pronged screening strategy to identify patients infected A total of 10,050 persons were observed. Only 337 (3.4%) persons with SARS-CoV-2 was implemented. 5 , 6 The epidemiology of newly did not wear face mask. The daily compliance of face mask usage confirmed cases was announced in the daily press conference was 97.2%, 97.1%, and 95.7% over three consecutive days in all 18 jointly held by CHP and Hospital Authority. Major clusters aris- administrative districts in HKSAR. ing from mask-on (workplace) and mask-off (recreational) settings Besides proactive infection control measures implemented by were analyzed to evaluate the efficacy of wearing face masks. public hospitals under the governance of Hospital Authority, 5 , 6 V.C.-C. Cheng, S.-C. Wong and V.W.-M. Chuang et al. / Journal of Infection 81 (2020) 107–114 109

Fig. 1. Evolving epidemic of coronavirus disease 2019 (COVID-19) in Hong Kong (from day 1 to 100). Note. #including their close contacts COVID-19, coronavirus disease 2019; DTS, deep throat saliva; WHO, World Health Organization. step-wise introduction of epidemiological measures by the HKSAR tings than might be expected assuming that the null hypothesis of government were enforced. They included border controls to re- equal number of clusters involving mask-on and mask-off settings duce imported SARS-CoV-2 cases from mainland China on 4 Febru- was true ( p = 0.036). ary 2020 (day 36). This was followed by imposing home quaran- tine order for 14 days to all entrees from mainland China on 8 Comparing the epidemic progression of COVID-19 in HKSAR with February 2020 (day 40). Subsequently, the quarantine order was other parts of the world progressively imposed to all entrees into HKSAR on and after 19 March 2020 (day 80) ( Fig. 1 ). All entrees were compulsorily tested The incidence and cumulative number of COVID-19 cases in for SARS-CoV-2 by collecting their posterior oropharyngeal saliva HKSAR and the representative countries or areas since the first with effect from 8 April 2020 (day 100). As in other localities, iso- laboratory-confirmed case of SARS-CoV-2 are illustrated in Fig. 2a & lation of confirmed case, contact tracing and quarantine, closure of 2b . The incidence of COVID-19 in HKSAR was significantly less affected or high risk premises, and social distancing measures such than that of the selected countries (with well-established health- as home-office and school closure were instituted. care system and having over 100 confirmed cases at day 72 when WHO declared a pandemic) in Asia, Europe, and North America, Epidemiology of COVID-19 in HKSAR where face mask usage was not universally adopted in the com- munity ( Table 1 ). Singapore’s land area and population density are Up to day 100 of the epidemic, a total of 961 cases of COVID-19 comparable to HKSAR. 4 On day 100 (8 April 2020), the incidence were confirmed in HKSAR. Transmission of COVID-19 was divisible of COVID-19 per million population in Singapore was significantly into four phases: phase 0 (from day 1 to 21) with no confirmed higher than that in HKSAR (259.8 per million population vs 129.0 cases of COVID-19 in HKSAR; phase 1 (from day 22 to 30) with 10 per million population, p < 0.001) ( Table 2 ). In South Korea, the imported cases; phase 2 (from day 31 to 71) with 111 cases (pre- number of molecular diagnostic tests per million population was dominantly local cases) and; phase 3 (from day 72, WHO declared comparable to HKSAR. The proportion of local cases in South Korea COVID-19 pandemic, onwards) with 840 cases (predominantly im- related to mask-off settings was significantly higher than that in ported cases with local clusters of cases) ( Fig. 1 ). Among the 961 HKSAR [5150/10,384 (49.6%) vs 113 / 961 (11.8%), p < 0.001] because confirmed cases, there were 11 clusters of 113 persons that were of super-spreading events at a church which was also a mask-off directly engaged in mask-off activities such as dining and drink- setting ( Table 2 ). ing in restaurant or bar, singing at karaoke, and exercise in fit- ness clubs. There were only three clusters involving 11 persons en- Discussion gaged in mask-on settings at the workplace. Using the chi-square test of goodness-of-fit with Williams’ continuity correction, there Evidence for using face masks to prevent transmission of res- were significantly more COVID-19 clusters involving mask-off set- piratory viruses in the community remains limited to a few stud- 110 V.C.-C. Cheng, S.-C. Wong and V.W.-M. Chuang et al. / Journal of Infection 81 (2020) 107–114

Fig. 2a. Cumulative number of COVID-19 in representative countries or areas with or without community-wide wearing of face mask Note. The x-axis denotes the number of days since the first laboratory-confirmed case in the representative countries or areas. The date of first laboratory-confirmed case in Hong Kong (21 January 2020), Singapore (24 January 2020), South Korea (21 January 2020), Spain (1 February 2020), Switzerland (26 February 2020), Italy (31 January 2020), Belgium (06 February 2020), Austria (27 February 2020), Germany (28 January 2020), France (25 January 2020), Netherlands (28 February 2020), Norway (27 February 2020), Denmark (27 February 2020), The United Kingdom (1 February 2020), Sweden (01 February 2020) and United States of America (23 January 2020). ies conducted in the household setting. 12 , 13 Although there is no nity service providers and those who are working indoors. Since expert consensus on this issue, universal masking is voluntar- the supply of face mask was tight in the community as well as ily adopted by people in our HKSAR community soon after the in the healthcare setting, it is the practice of our general public first imported case of COVID-19 was reported. This public action not to use more than one face mask per person per day. We ob- was linked to the painful experience of the 2003 SARS outbreak served that the overall compliance of face mask usage was 97% in (1755 cases with 299 deaths in 6.73 million population) when HK- all administrative districts in the morning. Thus we have the rea- SAR people adopted universal masking in addition to other non- son to believe that their compliance to face mask usage would re- pharmaceutical interventions such as hand hygiene, social distanc- main high throughout the day at the workplace. It is therefore not ing and school closure. 7 These community hygienic measures dur- surprising that the number of COVID-19 clusters was significantly ing the SARS outbreak resulted in a significant reduction of pos- higher in the mask-off recreational settings in HKSAR. itive specimens of all circulating respiratory viruses including in- Universal masking in the community may mitigate the extent of fluenza viruses in 2003 compared with preceding periods. 14 In a transmission of COVID-19 and may be a necessary adjunctive pub- case-control study conducted in Beijing during 2003 SARS, consis- lic health measure in a densely populated city like HKSAR, with tent wearing of a face mask outdoors was associated with a 70% an average of 170,0 0 0 people entering HKSAR from Mainland and risk reduction, compared to those not wearing a face mask. 15 overseas per day. 18 Our incidence of COVID-19 was also lower than HKSAR is the only area practicing universal masking despite the that of other areas with local transmission, vindicating this ap- recommendation of WHO and CDC that mask should be reserved proach. In particular, our incidence of COVID-19 was significantly for those with symptoms and in healthcare settings. We therefore lower than that of Singapore, a city comparable with HKSAR in compared the number of COVID-19 clusters in mask-on settings at terms of area, population density, healthcare infrastructure, BCG workplace with that of the mask-off settings such as dining and vaccination, 19 as well as adopting social distancing strategies and drinking in restaurant or bar, singing at karaoke, and exercising in SARS-CoV-2 testing infrastructure. 20 Besides a lower ambient tem- gymnasium, where there was a large gathering of people sharing perature and a higher risk of importation of COVID-19 cases from food, drinks, and instruments. In effect, these mask-off settings al- the mainland which are factors promoting COVID-19 transmission lowed the sharing of their saliva and respiratory droplets, which in HKSAR, the most important difference between the two cities is may contain a viral load of 100 million per ml, directly or indi- the community-wide usage of face masks in HKSAR but not in Sin- rectly. 16 , 17 In HKSAR hospitals, wearing face masks is mandatory gapore. Moreover, 50% of local transmission of COVID-19 in South during the pandemic. It is also the practice among many commu- Korea was attributed to religious activities where face mask usage V.C.-C. Cheng, S.-C. Wong and V.W.-M. Chuang et al. / Journal of Infection 81 (2020) 107–114 111

Fig. 2b. Cumulative number of COVID-19 per million population in representative countries or areas with or without community-wide wearing of face mask Note. The x-axis denotes the number of day since the first laboratory-confirmed case in the representative countries or areas. The date of first laboratory-confirmed case in Hong Kong (21 January 2020), Singapore (24 January 2020), South Korea (21 January 2020), Spain (1 February 2020), Switzerland (26 February 2020), Italy (31 January 2020), Belgium (06 February 2020), Austria (27 February 2020), Germany (28 January 2020), France (25 January 2020), Netherlands (28 February 2020), Norway (27 February 2020), Denmark (27 February 2020), The United Kingdom (1 February 2020), Sweden (01 February 2020) and United States of America (23 January 2020). was discouraged. Mask-off activities clearly have potential implica- oned this measure for the control of community transmission of tions for COVID-19 transmission in the community. COVID-19. 28 Masking is a continuous form of protection to stop the However, the use of face mask in the community remains con- spreading of saliva and respiratory droplets to others or from oth- troversial. 21 , 22 WHO issued an interim guideline regarding the use ers, and to the environment or from the environment to the sus- of masks in the context of COVID-19 on 6 April 2020, stating no ceptible by hands through touching of nose, mouth and eye. Touch- evidence that wearing a mask by healthy persons in the wider ing nose and mouth is a subconscious behavior. 29 Hand hygiene community setting can prevent acquisition of COVID-19. 23 Euro- is always the cornerstone to prevent transmission of COVID-19 pean Centre for Disease Prevention and Control issued a techni- but it is a one-off discontinuous process where hand contamina- cal report on 8 April 2020 that the use of face masks in the com- tion may occur easily between each alcoholic handrubbing or hand munity could be considered, especially when visiting busy, closed washing. Although we have successfully implemented directly ob- spaces, despite not knowing how much the use of masks in the served hand hygiene (DOHH) by regular delivery of alcohol-based community can contribute to a decrease in transmission in addi- hand rub to conscious hospitalized patients and persons in res- tion to the other counter measures. 24 On 3 April 2020, CDC rec- idential care homes for the elderly before meal and medication ommended the use of cloth face coverings, especially in areas of rounds, 30–32 it may be difficult to practice DOHH in the commu- significant community-based transmission. 25 The shift of paradigm nity. Studies have also shown that wearing a mask with frequent from not recommending to promoting the use of face masks was hand hygiene significantly reduced transmission of seasonal in- based on the rationale of pre-symptomatic shedding of SARS-Cov- fluenza virus in the community setting. But once the effect of the 2 and presence of asymptomatic patients with high viral load in use of surgical mask was removed, the effect of hand hygiene be- the community. 9 , 26 The use of face mask may serve as source came insignificant. 33 With the understanding that the supply of control by preventing dispersal of droplets during talking, sneez- face masks should primarily be reserved for usage in healthcare ing, and coughing, 27 and also reduce the risk of environmental settings, we believe that it is still advisable to encourage people contamination by SARS-CoV-2. Despite some supporters of WHO to wear face masks in the public based on the precautionary prin- recommendation speaking against universal masking in our local ciples. 34 Moreover, wearing a cloth mask with less filtration effi- medical community, most opinion leaders in the clinical microbi- ciency may still be better than no mask at all in communities of ology and infectious disease specialties of HKSAR openly champi- high transmission. 112 V.C.-C. Cheng, S.-C. Wong and V.W.-M. Chuang et al. / Journal of Infection 81 (2020) 107–114

Table 1 Incidence of coronavirus disease 2019 (COVID-19) infection in Hong Kong Special Administrative Region (HKSAR) as compared with that of selected countries as of 8 April

2020 (at day 100 after official announcement of pneumonia outbreak in Wuhan, Hubei Province, China) a.

Countries or city Population Cumulative number Number (percentage) Incidence per P value (incidence Population density:

(million) b of confirmed case c of death million population d compared with population per km 2

HKSAR) (rank in the world) e

Hong Kong SAR f 7.45 961 4 (0.4%) 129.0 Not applicable 6782 (3 rd) Western Pacific Region

Singapore 5.70 1,481 6 (0.4%) 259.8 P < 0.001 7894 (2 nd)

South Korea 51.78 10,384 200 (1.9%) 200.5 P < 0.001 517 (13 th) European Region

Spain 47.10 140,510 13,798 (9.8%) 2,983.2 P < 0.001 93 (89 th)

Switzerland 8.59 22,164 641 (2.9%) 2,580.2 P < 0.001 208 (48 th)

Italy 60.24 135,586 17,129 (12.6%) 2,250.8 P < 0.001 200 (51 st)

Belgium 11.52 22,194 2,035 (9.2%) 1,926.6 P < 0.001 376 (22 nd)

Austria 8.90 12,640 243 (1.9%) 1,420.2 P < 0.001 106 (76 th)

Germany 83.15 103,228 1,861 (1.8%) 1,241.5 P < 0.001 233 (41 st)

France 67.06 77,226 10,313 (13.4%) 1,151.6 P < 0.001 123 (68 th)

Netherlands 17.44 19,580 2,101 (10.7%) 1,122.7 P < 0.001 420 (16 th)

Norway 5.37 5,863 69 (1.7%) 1,091.8 P < 0.001 17 (171 st)

Denmark 5.82 5,071 203 (4.0%) 871.3 P < 0.001 135 (64 th)

The United Kingdom 66.44 55,246 6,159 (11.1%) 831.5 P < 0.001 274 (32 nd)

Sweden 10.33 7,693 591 (7.7%) 744.7 P < 0.001 23 (159 th) Region of Americas

United States of 329.45 363,321 10,845 (3.0%) 1,102.8 P < 0.001 34 (145 th) America

a Developed countries with well-established healthcare system and reached more than 100 confirmed cases at day 72 (WHO declare pandemic COVID-19) were selected for comparison.

b The population of country or city were retrieved from the website of World Health Organization.

c Infection retrieved from situation report - 79 of World Health Organization issued on 8 April 2020 (day 100 after the official announcement of clusters of community- acquired pneumonia in Wuhan, Hubei Province, China.

d The sequence of countries was listed as descending order in accordance with the incidence of COVID-19 per million population.

e Information retrieved from Wikipedia - List of countries and dependencies by population density. https://en.wikipedia.org/wiki/List _of _countries _and _dependencies _by _ population _density (Accessed 12 April 2020).

f The number of confirmed case was based on the official announcement daily by HKSAR, China.

Table 2 Comparison of the epidemiology and community responses against coronavirus disease 2019 (COVID-19) in Hong Kong SAR, Singapore, and South Korea.

Epidemiology parameter as of 8 April 2020 Hong Kong SAR Singapore South Korea Total number of confirmed case 961 1,481 10,384

Number of imported cases 517 (53.8%) 567 (38.3%) a NM

Number of RT-PCR performed per million population ∼15,000 ∼12,800 b ∼9,900 c

Number of local cases related to mask-off setting (i.e. religious activities, dining and drinking in 113 (11.8%) NM 5150 (49.6%) c ,d restaurant or bar, singing at karaoke, and exercise in gymnasium) Number of local cases related to family (other than mask-off setting described above) 41 (4.3%) NM NM Number of local cases related to mask-on setting (i.e. workplace) 11 (1.4%) NM NM

Date of border restrictions 25 March 2020 e 23 March 2020, 2359 f 1 April 2020 g

Average of ambient temperature range in the first 100 days of COVID-19 transmission 18 °C to 22 °C h 24 °C to 31 °C i 1 °C to 9 °C j

Routine childhood BCG immunization program k Yes Yes Yes

Note. NM, not mentioned.

a Daily report on COVID-19. Minister of Health, Singapore. https://www.moh.gov.sg/docs/librariesprovider5/local- situation- report/situation- report- 1- apr- 2020.pdf . Ac- cessed 12 April 2020.

b Information obtained from Minister of Health, Singapore. https://www.moh.gov.sg/covid-19 . Accessed 12 April 2020.

c Information obtained from Coronavirus Disease-19, Republic of Korea. http://ncov.mohw.go.kr/en/ . Accessed 12 April 2020.

d These patients were all related to a cohort of participants involving in religious activities - wearing face masks was discouraged. These were the believer of Olive Tree, a Christian new religious movement, originally known as Jesus Christ Congregation Revival Association of Korea, founded in Republic of Korea by Park Tae Son. https://en.wikipedia.org/wiki/Olive _Tree _ (religious_movement). Accessed 12 April 2020.

e Deny entry of non-Hong Kong resident.

f All short-term visitors (from anywhere in the world) will not be allowed to enter or transit through Singapore.

g All passengers are subject to mandatory self-quarantine for 14 days, except for airline crew. https://en.wikipedia.org/wiki/Travel _restrictions _ related _ to _the _2019%E2% 80%9320 _ coronavirus _ pandemic . Accessed 12 April 2020.

h https://www.hko.gov.hk/en/wxinfo/pastwx/mws/mws.htm . Accessed 12 April 2020.

i https://www.climatestotravel.com/climate/singapore . Accessed 12 April 2020.

j https://www.climatestotravel.com/climate/south-korea . Accessed 12 April 2020.

k There is postulation of countries with BCG vaccination program tends to have lower incidence and death due to COVID-19 19 .

SARS-CoV-2 is a highly transmissible respiratory virus which turn leads to a higher level of viral replication than that by the causes upper and lower respiratory tract infection leading to a high 2003 SARS-CoV in an ex vivo lung tissue explant model. 10 These viral load in respiratory secretions and saliva as shown in clinical ex vivo findings supported the suggestion that an important pro- studies and transmission studies by close contact in animal mod- portion of COVID-19 patients may be pre-symptomatic or mildly els. 35 Moreover, SARS-CoV-2 can suppress the host innate immune symptomatic virus shedders. These groups of patients are unlikely response in terms of interferon and cytokine response which in to be tested or isolated and may contribute to the perpetuation of V.C.-C. Cheng, S.-C. Wong and V.W.-M. Chuang et al. / Journal of Infection 81 (2020) 107–114 113 the pandemic. Therefore community-wide mask usage irrespective 6. Cheng VCC , Wong SC , Chen JHK , Yip CCY , Chuang VWM , Tsang OTY , et al. Es- of symptoms may reduce the infectivity of these silent COVID-19 calating infection control response to the rapidly evolving epidemiology of the coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 in Hong Kong. Infect cases to the susceptible individuals. Control Hosp Epidemiol 2020:1–6 . There are several limitations in our study. First, we did not 7. Cheng VC , Lau SK , Woo PC , Yuen KY . Severe acute respiratory syndrome coro- analyze the mask-off settings in the family because the modes navirus as an agent of emerging and reemerging infection. Clin Microbiol Rev

2007;20:660–94. of transmission among close household contacts can be more di- 8. Cheng VC , To KK , Tse H , Hung IF , Yuen KY . Two years after pandemic influenza verse. If the 15 family clusters were also counted within the A/2009/H1N1: what have we learned? Clin Microbiol Rev 2012; 25 :223–63 . mask-off settings, the difference would be even more significant 9. Chan JF , Yuan S , Kok KH , To KK , Chu H , Yang J , et al. A familial cluster of pneu-

( p < 0.001). Second, the type of mask used in the community can- monia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet 2020; 395 :514–23 . not be controlled. The compliance of wearing face mask in terms 10. Chu H , Chan JF , Wang Y , Yuen TT , Chai Y , Hou Y , et al. Comparative replication of not touching the external surface of mask or face, and hand hy- and immune activation profiles of SARS-CoV-2 and SARS-CoV in human lungs: giene before or after touching the mask cannot be assessed. Third, an ex vivo study with implications for the pathogenesis of COVID-19. Clin Infect Dis 2020 . we cannot count the mask compliance directly for every com- 11. Chan JF , Yip CC , To KK , Tang TH , Wong SC , Leung KH , et al. Improved munity settings. Nevertheless, in the absence of effective antivi- molecular diagnosis of COVID-19 by the novel, highly sensitive and specific ral and vaccines, the pandemic spread COVID-19 to many coun- COVID-19-RdRp/Hel real-time reverse transcription-polymerase chain reaction assay validated in vitro and with clinical specimens. J Clin Microbiol 2020 . tries provide an unique opportunity to study the effectiveness of 12. MacIntyre CR , Cauchemez S , Dwyer DE , Seale H , Cheung P , Browne G , et al. Face this non-pharmaceutical control measures. As of 27 February 2020 mask use and control of respiratory virus transmission in households. Emerg (day 38 since the first reported case in South Korea), South Ko- Infect Dis 2009; 15 :233–41 . 13. Cowling BJ , Chan KH , Fang VJ , Cheng CK , Fung RO , Wai W , et al. Facemasks rea government has started to distribute face masks to the pub- and hand hygiene to prevent influenza transmission in households: a cluster 36 lic amid the outbreak of the COVID-19, which was associated randomized trial. Ann Intern Med 2009; 151 :437–46 . with a flattening of the epidemic curve. As of 14 April 2020 (day 14. Lo JY , Tsang TH , Leung YH , Yeung EY , Wu T , Lim WW . Respiratory infections

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By Wei Lyu and George L. Wehby doi: 10.1377/hlthaff.2020.00818 HEALTH AFFAIRS 39, NO. 8 (2020): 1–7 Community Use Of Face Masks ©2020 Project HOPE— The People-to-People Health And COVID-19: Evidence From Foundation, Inc. A Natural Experiment Of State Mandates In The US

Wei Lyu is a research ABSTRACT State policies mandating public or community use of face associate in the Department masks or covers in mitigating novel coronavirus disease (COVID-19) of Health Management and Policy, College of Public spread are hotly contested. This study provides evidence from a natural Health, University of Iowa, in experiment on effects of state government mandates in the US for face Iowa City, Iowa.

mask use in public issued by 15 states plus DC between April 8 and May George L. Wehby (george- 15. The research design is an event study examining changes in the daily [email protected]) is a professor in the Department county-level COVID-19 growth rates between March 31, 2020 and May 22, of Health Management and Policy, College of Public 2020. Mandating face mask use in public is associated with a decline in Health, University of Iowa, the daily COVID-19 growth rate by 0.9, 1.1, 1.4, 1.7, and 2.0 percentage- and a research associate at – – – – the National Bureau of points in 1 5, 6 10, 11 15, 16 20, and 21+ days after signing, respectively. Economic Research. Estimates suggest as many as 230,000–450,000 COVID-19 cases possibly averted By May 22, 2020 by these mandates. The findings suggest that requiring face mask use in public might help in mitigating COVID-19 spread. [Editor’s Note: This Fast Track Ahead Of Print article is the accepted version of the peer-reviewed manuscript. The final edited version will appear in an upcoming issue of Health Affairs.]

ne of the most contentious issues COVID-19 mitigation (i.e. everyone without being debated worldwide in the symptoms should use a face mask outside of their response to the novel coronavirus home), such as the World Health Organization, disease (COVID-19) pandemic is strongly recommend that symptomatic individ- the value of wearing masks or uals wear them.5 Since mask wearing by infected Ofacial coverings in public settings.1 A key factor individuals can reduce transmission risk, and fueling the debate is the limited direct evidence because of the high proportion of asymptomatic thus far on how much widespread community infected individuals and transmissions, there use would affect COVID-19 spread. However, appears to be a strong case for the effectiveness there is now substantial evidence of asymptom- of widespread use of face masks in reducing the atic transmission of COVID-19.2,3 For example, a spread of COVID-19. However, there is no direct recent study of antibodies in a sample of custom- evidence thus far on the magnitude of such ef- ers in grocery stores in New York State reported fects, especially at a population level. an infection rate of 14% by March 29 (projected Researchers have been reviewing evidence to represent nearly 2.1 million cases), which sub- from previous randomized controlled trials for stantially exceeds the number of confirmed other respiratory illnesses examining mask use COVID-19 cases.4 Moreover, all public health and types among individuals at higher risk of authorities call on symptomatic individuals to contracting infections (such as health care work- wear masks to reduce transmission risk. Even ers or individuals in infected households). Sys- organizations that have not yet recommended tematic reviews and meta-analyses of such stud- widespread community use of facial masks for ies have provided suggestive, although generally

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weak, evidence.6 The estimates from the meta- settings, as opposed to community-wide man- analyses based on the randomized controlled dates. This evidence is critical as states and coun- trials suggest declines in transmission risk of tries worldwide begin to shift to “reopening” influenza or influenza-like illnesses to mask their economies and as foot traffic increases. wearers, although estimates are mostly statisti- Mandating public use of masks has become a cally insignificant possibly due to small sample socially and politically contentious issue, with sizes or design limitations especially related to multiple protests and even acts of violence di- assessing compliance.7–9 There is also a relation- rected against masked employees and those ask- ship between increased adherence to mask use ing customers to wear face masks.17 Face cover specifically and effectiveness of reducing trans- recommendations and mandates are part of the mission to mask wearers; in one randomized current set of measures, following earlier social study of influenza transmission in infected distancing measures such as school and non- households in Australia, transmission risk for essential business closures, bans on large gath- mask wearers was lower with greater adher- erings, and shelter-in-place orders being consid- ence.10 Further, the evidence is mixed from ran- ered by states and local governments, especially domized studies on types of masks and risk of as regions of the country reopen. For example, influenza-like illnesses transmission to mask most recently, Virginia started its phase one re- wearers; for example, a recent systematic review opening on May 22, 2020 and required everyone and meta-analysis comparing N95 respirators in the state to wear face masks in public where versus surgical masks found a statistically insig- people congregate.18 Therefore, it is critical to nificant decline in influenza risk with the N95- provide direct evidence on this question not only respirators.11 for public health authorities and governments Positions on widespread facial mask use have but also for educating the public. differed worldwide but are changing over time. In the US, public health authorities did not rec- ommend widespread facial mask use in public Study Data And Methods at the start of the pandemic. The initially limited Data We collect information on statewide face evidence on asymptomatic transmission and covering mandate orders from public datasets on concern about mask shortages for health care such policies and from searching and reviewing workforce and individuals caring for patients all state orders issued between April 1 and May contributed to that initial decision. On April 3, 21, 2020. Our study focuses on state executive 2020, the Centers for Disease Control and Pre- orders or directives signed by state governors vention (CDC) issued new guidance advising all that mandate use. Recommendations or guide- individuals to wear cloth facial covers in public lines from state departments of public health are areas where close contact with others is unavoid- not included as these largely follow the CDC able, citing new evidence on virus transmission guideline and may not necessarily add further from asymptomatic or pre-symptomatic individ- information or impact. See online appendix A uals.12 Guidelines differ between countries, and for more detailed description of the data sources some including Germany, France, Italy, Spain, and measuring the mandates.19 China, and South Korea have mandated use of States differ in whether they require their citi- face masks in public.13–16 zens to wear face masks (covers) to limit COVID- This study adds complementary evidence to 19 spread or not. Between April 8 and May 15, the literature on impacts of widespread commu- governors of 15 states and the mayor of the Dis- nity use of face masks on COVID-19 spread from a trict of Columbia (DC) have signed orders man- natural experiment based on whether states in dating all individuals who can medically tolerate the US have mandated the use of face masks in the wearing of a face mask do so in public set- public for COVID-19 mitigation or not. Specifi- tings (e.g., public transportation, grocery stores, cally, we identify the effects of mandating face pharmacies, or other retail stores) where main- mask use in public on daily COVID-19 growth taining 6-feet of “social distance” may not always rates based on differences in the timing and is- be practicable; these 15 states also have specific suance of state mandates. mandates requiring employees in certain profes- In the US, 15 states plus DC have issued man- sions to wear masks at all times while working. dates for face mask use in public between April 8 Besides these 15 states and DC, 20 additional and May 15.We examine the effects of state man- states have employee-only mandates (but no dates for use of face masks in public on the daily community-wide mandate) requiring that some COVID-19 growth rate using an event study that employees (e.g., close-contact services providers examines the effects over different periods. We like barber shops and nail salons) wear a face also consider the impact of mandates for mask mask at all times while providing services. The use targeted only to employees in some work face mask defined in these orders primarily re-

2 Health Affairs August 2020 39:8 Downloaded from HealthAffairs.org on June 23, 2020. Copyright Project HOPE—The People-to-People Health Foundation, Inc. For personal use only. All rights reserved. Reuse permissions at HealthAffairs.org. fers to cloth face covering or non-medical masks. date) through May 22. The models are estimated The state orders strongly discourage the use of by least squares weighted by the county 2019 any medical/surgical masks and N95 respira- population with heteroscedasticity-robust and tors, which should be reserved for health care state-clustered standard errors. workers and first responders. The orders also As noted above, all of the 15 states plus DC that clearly specify that the face masks are not a re- mandate facial cover use in public also mandated placement for any other social distancing proto- employee mask use. To assess the effects of em- cols. Fifteen states have yet not issued public ployee face cover mandates, we estimate another or employee mandates. Further information on event-study model that focuses on the employee dates is in appendix exhibit A1. Links to these face cover mandate as the policy intervention. In state orders are in appendixes D and E.19 this analysis, we exclude the 15 states plus DC The main model uses publicly available daily with both public and employee face cover man- county-level data of confirmed COVID-19 cases dates and focus on the 20 states with employee starting on March 25 through May 21.20 The data only mandate and the 15 states without an em- covers all states plus DC, and the analytical sam- ployee mandate. ple includes 2,930 unique counties plus New Limitations We are unable to measure facial York City (five boroughs combined). See appen- cover use in the community (i.e. compliance with dix A for more detailed description of COVID-19 the mandate). As such, the estimates represent data.19 the intent-to-treat effects of these mandates, i.e. Statistical Analysis We employ an event their effects as passed, and not the individual- study, which is generally similar to a differ- level effect of wearing a face mask in public on ence-in-differences design, to examine whether own COVID-19 risk. Related, we do not measure statewide mandates to wear face masks in public enforcement of the mandates, which might af- affect the spread of COVID-19 based on the state fect compliance. We also do not have data on variations noted above. This design allows us to county-level mandates for wearing public- estimate the effects in the context of a natural face masks. In some states without state-level experiment: comparing the pre-post mandate mandates such as California,22 Texas,23 and changes in COVID-19 spread in the states with Colorado,24 multiple counties have enacted such mandates to the states that did not pass these mandates. These county-level mandates do not mandates over time. The model tests whether bias the intent-to-treat estimates of effects of states issuing these mandates had differential state-level mandates as actually passed, but they pre-trends in COVID-19 rates before they were do add local-level heterogeneity not directly ac- issued. This is a critical assumption of the validi- counted for in the model. We do examine the ty of an event study that must be upheld under robustness of estimates to excluding some of testing. In addition, the model allows us to con- these states. Finally, we are able to examine only trol for a wide range of time-invariant differences confirmed COVID-19 cases. However, there is between states and counties such as population evidence of a higher infection rate in the com- density and socioeconomic and demographic munity than confirmed cases.25 factors, plus time-variant differences between states and counties such as other mitigation and social distancing policies in addition to Study Results state-level COVID-19 tests. EffectsOfMandatesForFaceCoveringIn We estimate the effects of face cover mandates Public Supplemental exhibit 1 in the online ap- on the daily county-level COVID-19 growth rate, pendix19 plots the event study estimates of effects which is the difference in the natural log of cu- of state mandates for face covering in public on mulative COVID-19 cases on a given day minus the county-level daily growth rate of COVID-19 the natural log of cumulative cases in the prior cases with their 95% CIs, obtained from the day, multiplied by 100.21 This measure gives the main regression model (in appendix B) using daily growth rate in percentage points. county-level daily data from March 31 through The reference period for estimating the face May 22;19 appendix exhibit C1 (column 1) reports cover mandate effects is 1–5 days before signing the exact estimates.19 The effects are shown over the order. We examine how effects change over five periods after signing the orders, relative to five post-periods: 1–5 days, 6–10 days, 11–15 the five days before signing (reference period). days, 16–20 days, and 21+ days. The model also Also shown are estimated differences in daily tests for pre-trends over 6–10 days, 11–15 days, COVID-19 growth rates between states with and and 16+ days before signing the mandate. For all without the mandates over three periods before counties in the analytical sample, the main mod- the reference period. el includes daily data from March 31 (7 days There is a significant decline in daily COVID-19 before the first state signed a face cover man- growth rate after mandating facial covers in pub-

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lic, with the effect increasing over time after sign- estimates of changes in county-level daily ing the order. Specifically, the daily case rate COVID-19 growth rates with the employee only declines by 0.9, 1.1, 1.4, 1.7, and 2.0 percent- face cover mandates and their 95% CIs. All pre- age-points within 1–5, 6–10, 11–15, and 16–20, and post-mandate estimates are small and insig- and 21+ days after signing, respectively. All nificant. Overall, these results indicate no evi- of these declines are statistically significant dence of declines in daily COVID-19 growth rates (p<0:05, or less). In contrast, the pre-trends with the employee-only mandates. in COVID-19 case growth rates are small and statistically insignificant. We also project the number of averted COVID- Discussion 19 cases with the mandates for face mask use in Around the world, governments have been fight- public by comparing actual cumulative daily ing COVID-19 spread through a mix of policies cases to daily cases predicted by the model if and mitigation measures such as school and non- none of the states had enacted the public face essential business closures and shelter-in-place cover mandate at the time they did (see details in orders. Some countries have also recommended appendix B).19 The main model estimates suggest or mandated widespread community use of facial that as many as 230,000–450,000 cases may masks as a mitigation measure. However, the have been averted due to these mandates by effectiveness of this measure is highly debated. May 22. Estimates of averted cases should be The debate and uncertainty are fueled by the viewed cautiously and only as general approxi- limited direct empirical evidence on the magni- mations. tude of effects of widespread face mask use in Robustness Checks We estimate multiple ex- public on COVID-19 mitigation. There is a critical tensions of the main event study model to assess need for empirical evidence on the magnitude the robustness of estimates to different model of these effects from natural experiments.8 This specifications and sample choices. These checks evidence is especially relevant as governments start the event study on March 26, add flexible reopen their economies and loosen social dis- controls for social distancing and state reopen- tancing restrictions at times while new infec- ing measures, employee face mask use man- tions continue without a vaccine or widely acces- dates, and county-specific time trends, and allow sible and effective treatments in sight. time trends to vary by sociodemographic indica- The study provides direct evidence on the ef- tors. Other checks use the mandate effective date fectiveness of widespread community use of face instead of signing date; use hyperbolic sine masks from a natural experiment that evaluates transformation to account for 0 cases; include effects of state government mandates in the US states as the unit instead of counties; include for face mask use in public on COVID-19 spread. only urban counties; exclude some states with- Fifteen states plus DC in the US have mandated out state-level mandates but multiple counties this use between April 8 and May 5. Using an having local mandates. The detailed description event study that examines daily changes in coun- and results of these robustness checks are listed ty-level COVID-19 growth rates, the study finds in appendix C.19 The results are robust across that mandating public use of face masks is asso- these checks; effects are smaller when using ciated with a reduction in the COVID-19 daily the effective date instead of the signing date, growth rate. Specifically, we find that the average which differ by about 2–3 days on average sug- daily county-level growth rate decreases by 0.9, gesting earlier compliance, and when using 1.1, 1.4, 1.7, and 2.0 percentage-points in 1–5, states as the unit of analysis. But the estimates 6–10, 11–15, 16–20, and 21+ days after signing, remain meaningful and statistically significant respectively. in all checks. These estimates are not small and represent EffectsOfEmployeeOnlyFaceCovering nearly 16–19% of the effects of other social dis- Mandates As noted above, we also directly as- tancing measures (school closures, bans on large sess the effects of states mandating only that gatherings, shelter-in-place orders, and closures certain employees wear face masks. Twenty of restaurants, bars, and entertainment venues) states issued employee only mandates but did after similar periods from their enactment.21 not issue public use mandates. We re-estimate The estimates suggest increasing effectiveness the event-study model described above for and benefits from these mandates over time. this employee-only mandate including those By May 22, the estimates suggest that as many 20 states (issued between April 17 and May 9) as 230,000–450,000 COVID-19 cases may have and the 15 states without mandates and exclud- been averted based on when states passed these ing the 15 states plus DC that issued the public mandates. Again, the estimates of averted cases use mandates (plus the employee use mandates). should be viewed cautiously as these are sensitive Supplemental exhibit 219 plots the event study to assumptions and different approaches for

4 Health Affairs August 2020 39:8 Downloaded from HealthAffairs.org on June 23, 2020. Copyright Project HOPE—The People-to-People Health Foundation, Inc. For personal use only. All rights reserved. Reuse permissions at HealthAffairs.org. transforming the changes in the daily growth penalties for non-compliance also vary. In some rate estimates to cases. states such as Delaware, Hawaii, Maryland, and The early declines in the daily growth rate over Massachusetts, the face mask orders state that 5 days after signing the order are broadly consis- they have the force and effect of law, with a willful tent with timing of effects of other social distanc- violation subject to a criminal offense with pen- ing measures such as business closures.21 While alties. For example, the order in Maryland states the median incubation period is estimated to be that “a person who knowingly and willfully around 5 days,26 there is a wide range from 2.2 violates this order is guilty of a misdemeanor (2.5th percentile) days to 11.5 days (97.5th per- and on conviction is subject to imprisonment centile) suggesting that for many individuals not exceeding one year or a fine not exceeding symptoms may appear relatively early. Further, $5,000 or both”.29 In contrast, the orders of some individuals may become aware of the mandates other states such as Connecticut, Maine, and early through the governors’ briefings and relat- Pennsylvania, while clearly mandating the wear- ed media reports or may be anticipating them. ing of a face mask in public, do not appear to There is no evidence of differential pre-man- clearly specify that violations of the order are date COVID-19 trends with respect to issuing subject to criminal offense or penalties. Future these mandates. The estimates represent the in- work should examine if and how differences in tent-to-treat effects of the statewide face cover strictness and enforcement modify the effects of mandates as passed, conditional on other na- these mandates. tional and local measures. In that way, the effects Compliance and enforcement may also differ are independent of the CDC national guidance to across contextual factors (such as other social wear facial masks issued on April 3. These effects distancing measures, workforce distribution, are robust to several model checks. The study population demographic, socioeconomic, and provides evidence from a natural experiment cultural factors). In that regard, it is important on effectiveness of mandating public use of face to clarify that the suggested benefits from man- masks in mitigating COVID-19 spread.We find no dating face mask use are not substitutes for other evidence for effects of states mandating employ- social distancing measures; the effects are con- ee face mask use, perhaps because many busi- ditional on the other enacted social distancing nesses themselves have been requiring their measures and how communities are complying employees to wear masks.27,28 In that sense, man- with them. It is also important to extend the dating employee mask use may be reinforcing evidence into additional measures of exposure what many businesses are already choosing to to the virus in the community as data become do on their own. available such as from serological testing for While the intent-to-treat estimates are of inter- antibodies. Finally, future work can examine ef- est for understanding the effectiveness of these fects on deaths, which lag cases and change not policies in limiting COVID-19 spread at the com- only with number of cases but also with case munity and population level, understanding severity. how their effects change with compliance and enforcement strategies is important for design- ing effective policies. Our study builds the first Conclusion step in estimating the overall effect of these poli- The study provides evidence that states in the US cies as enacted. However, these policies vary in mandating use of face masks in public had a their strictness and consequences of noncompli- greater decline in daily COVID-19 growth rates ance. The mandates generally require wearing after issuing these mandates compared to states a face mask in public whenever the social dis- that did not issue mandates. These effects are tance cannot be maintained. Some states (such observed conditional on other existing social as Delaware, Maryland, Massachusetts, and distancing measures and are independent of Maine) clarify what “public” areas are, for exam- the CDC recommendation to wear facial covers ple indoor space in retail establishments, out- issued on April 3. As countries worldwide and door space in busy parking lots and waiting areas states begin to relax social distancing restric- for take-out services, semi-enclosed areas, such tions and considering the high likelihood of a as in public transportation stops, and enclosed second COVID-19 wave in the fall/winter,30 re- space, such as in taxis and other public transpor- quiring use of face masks in public might help in tation means. The language on enforcement and reducing COVID-19 spread. ▪

[Published online June 16, 2020.]

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NOTES

1 Feng S, Shen C, Xia N, Song W, Fan households. Emerg Infect Dis. 2009; from: https://www.governor M, Cowling BJ. Rational use of face 15(2):233–41. .virginia.gov/media/governor masks in the COVID-19 pandemic. 11 Long Y, Hu T, Liu L, Chen R, Guo Q, virginiagov/executive-actions/EO- Lancet Respir Med. 2020;8(5): Yang L, Cheng Y, et al. Effectiveness 63-and-Order-Of-Public-Health- 434–6. of N95 respirators versus surgical Emergency-Five---Requirement-To- 2 Furukawa NW, Brooks JT, Sobel J. masks against influenza: A system- Wear-Face-Covering-While-Inside- Evidence Supporting Transmission atic review and meta-analysis. J Evid Buildings.pdf of Severe Acute Respiratory Syn- Based Med. 2020;13(2):93–101. 19 To access the appendix, click on the drome Coronavirus 2 While Pre- 12 Centers for Disease Control and Details tab of the article online. symptomatic or Asymptomatic. Prevention. Recommendation re- 20 Github. An ongoing repository of Emerg Infect Dis. 2020;26(7). garding the use of cloth face cover- data on coronavirus cases and deaths 3 Mizumoto K, Kagaya K, Zarebski A, ings, especially in areas of signifi- in the U.S. (New York Times). Chowell G. Estimating the asymp- cant community-based transmission Github [serial on the Internet]. 2020 tomatic proportion of coronavirus [Internet]. Atlanta (GA): CDC; [page [cited 2020 Apr 28]. Available from: disease 2019 (COVID-19) cases on last reviewed 2020 Apr 3; cited 2020 https://github.com/nytimes/covid- board the Diamond Princess cruise Jun 9]. Available from: https:// 19-data ship, Yokohama, Japan, 2020. www.cdc.gov/coronavirus/2019- 21 Courtemanche C, Garuccio J, Le A, Eurosurveillance. 2020;25(10): ncov/prevent-getting-sick/cloth- Pinkston J, Yelowitz A. Strong Social 2000180. face-cover.html Distancing Measures In The United 4 Rosenberg ES, Tesoriero JM, 13 Pleitgen F, Schmidt N. Germans face States Reduced The COVID-19 Rosenthal EM, Chung R, Barranco fines of up to $5,000 as wearing a Growth Rate. Health Aff (Millwood). MA, Styer LH, et al. Cumulative in- face mask becomes mandatory. CNN 2020 May 14. [Epub ahead of print]. cidence and diagnosis of SARS-CoV- [serial on the internet]. [Updated 22 Face Masks to Become Part of Life in 2 infection in New York. MedRxiv 2020 Apr 27; cited 2020 Jun 9]. California, but the Rules Vary. NBC [serial on the Internet]. 2020 May Available from: https://www.cnn Los Angeles [serial on the Internet]. 29 [cited 2020 Jun 9]. Available .com/2020/04/27/europe/ 2020 May 8 [cited 2020 Jun 9]. from: https://www.medrxiv.org/ germany-face-mask-mandatory-grm- Available from: https://www.nbc content/medrxiv/early/2020/05/ intl/index.html losangeles.com/news/local/ 29/2020.05.25.20113050.full.pdf 14 Bostock B. France has made wearing california-face-mask-rules-corona 5 World Health Organization. Advice face masks compulsory in public, virus-covid-19/2359246/ on the use of masks in the context of while maintaining a controversial 23 Nix MG, Huebinger J, Segura O Jr. COVID-19: interim guidance [Inter- ban on burqas and niqabs. Business Face Covering Guidelines for Busi- net]. Geneva: World Health Organi- Insider [serial on the internet]. 2020 nesses Operating in Texas. Holland zation; 2020 Apr 6 [cited 2020 Jun May 11 [cited 2020 Jun 9]. Available & Knight Law Firm Alerts [serial on 9]. Available from: https://apps from: https://www.businessinsider the Internet]. 2020 Apr 30 [cited .who.int/iris/handle/10665/331693 .com/france-face-masks- 2020 Jun 9]. Available from: https:// 6 Greenhalgh T, Schmid MB, compulsory-burqas-niqabs-banned- www.hklaw.com/en/insights/ Czypionka T, Bassler D, Gruer L. criticism-muslims-2020-5 publications/2020/04/face- Face masks for the public during the 15 Duncan C. Coronavirus: Spain makes covering-guidelines-for-businesses- covid-19 crisis. BMJ. 2020;369: face masks compulsory on public operating-in-texas m1435. transport as country begins to ease 24 Sebastian M. These Colorado cities 7 Brainard JS, Jones N, Lake I, Hooper strict lockdown. The Independent and counties require masks be worn L, Hunter P. Facemasks and similar [serial on the internet]. 2020 May 2 in public places. Denver Post [serial barriers to prevent respiratory ill- [cited 2020 Jun 9]. Available from: on the Internet]. 2020 May 4 [cited ness such as COVID-19: A rapid sys- https://www.independent.co.uk/ 2020 May 31]. Available from: tematic review. MedRxiv [serial on news/world/europe/coronavirus- https://www.denverpost.com/ the Internet]. 2020 Apr 6 [cited face-masks-spain-public-transport- 2020/05/04/colorado-denver-mask- 2020 Jun 9]. Available from: https:// lockdown-pedro-sanchez-a9496031 required-orders/ www.medrxiv.org/content/10.1101/ .html 25 Bendavid E, Mulaney B, Sood N, 2020.04.01.20049528v1 16 Which countries have made wearing Shah S, Ling L, Bromley-Dulfano R, 8 Jefferson T, Jones M, Al Ansari LA, face masks compulsory? Al Jazeera et al. COVID-19 Antibody Seroprev- Bawazeer G, Beller E, Clark J, et al. News [serial on the Internet]. [Up- alence in Santa Clara County, Physical interventions to interrupt dated 2020 May 29; cited 2020 May California. MedRxiv [serial on the or reduce the spread of respiratory 31]. Available from: https://www Internet]. 2020 Apr 14 [cited 2020 viruses. Part 1—Face masks, eye .aljazeera.com/news/2020/04/ May 31]. Available from: https:// protection and person distancing: countries-wearing-face-masks- www.medrxiv.org/content/10.1101/ systematic review and meta-analysis. compulsory-200423094510867.html 2020.04.14.20062463v2 MedRxiv [serial on the Internet]. 17 Morning Briefing. Tensions Over 26 Lauer SA, Grantz KH, Bi Q, Jones 2020 Mar 30 [cited 2020 May 31]. Masks, Social Distancing Lead To FK, Zheng Q, Meredith HR, et al. Available from: https://www Violent Altercations, Shooting The Incubation Period of Coronavi- .medrxiv.org/content/10.1101/ Death, Pipe Bomb Threats. Kaiser rus Disease 2019 (COVID-19) From 2020.03.30.20047217v2. Health News [serial on the Internet]. Publicly Reported Confirmed Cases: 9 Xiao J, Shiu EYC, Gao H, Wong JY, 2020 May 5 [cited 31 Jun 9]. Avail- Estimation and Application. Ann Fong MW, Ryu S, et al. Nonphar- able from: https://khn.org/ Intern Med. 2020;172(9):577–82. maceutical measures for pandemic morning-breakout/tensions-over- 27 Peterson H. Walmart is now requir- influenza in nonhealthcare settings— masks-social-distancing-lead-to- ing all US employees to wear face personal protective and environ- violent-altercations-shooting-death- masks and will encourage customers mental measures. Emerg Infect Dis. pipe-bomb-threats/ to wear them while shopping. 2020;26(5):967–75. 18 Commonwealth of Virginia. Office of Business Insider [serial on the In- 10 MacIntyre CR, Cauchemez S, Dwyer the Governor, Executive Order ternet]. 2020 April 17 [cited 2020 DE, Seale H, Cheung P, Browne G, Number 63 (2020) [Internet]. Jun 9]. Available from: https:// et al. Face mask use and control of Richmond (VA): The Office; 2020 www.businessinsider.com/ respiratory virus transmission in May 26 [cited 2020 Jun 9]. Available walmart-requires-face-masks-

6 Health Affairs August 2020 39:8 Downloaded from HealthAffairs.org on June 23, 2020. Copyright Project HOPE—The People-to-People Health Foundation, Inc. For personal use only. All rights reserved. Reuse permissions at HealthAffairs.org. workers-urges-shoppers-to-wear- 3055849001/ 30 Sun LH. CDC director warns second them-2020-4 29 State of Maryland, Executive De- wave of coronavirus is likely to be 28 Rice B. Costco, Delta, United: List of partment. Order of The Governor of even more devastating. Washington businesses requiring employees or The State of Maryland Number 20- Post [serial on the Internet]. 2020 customers to wear face masks. En- 04-15-01 [Internet]. Annapolis Apr 21 [cited 2020 Jun 9]. Available quirer [serial on the Internet]. 2020 (MD): State of Maryland; 2020 Apr from: https://www May 1 [cited 2020 May 27]. Available 15 [cited 2020 Jun 9]. Available .washingtonpost.com/health/2020/ from: https://www.cincinnati.com/ from: https://governor 04/21/coronavirus-secondwave- story/news/2020/05/01/face- .maryland.gov/wp-content/uploads/ cdcdirector/ masks-chipotle-walmart-sams-club- 2020/04/Masks-and-Physical- among-businesses-requiring/ Distancing-4.15.20.pdf

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Asymptomatic cases in CT images, and a positive result areas of ground-glass opacities and a family cluster with on qRT-PCR. By contrast, the other consolidation (appendix). Two sets two family members—a 33-year- of nasopharyngeal swab samples SARS-CoV-2 infection old woman (patient 2) and a from patient 1 tested positive for 3-year-old boy (patient 3)—were SARS-CoV-2 on qRT-PCR. Published Online Since December, 2019, an out­ both asymptomatic, with normal Patients 2 and 3 had no signs or February 19, 2020 break of pneumonia caused by a lymphocyte counts and chest CT clinical symptoms during the same https://doi.org/10.1016/ S1473-3099(20)30114-6 novel coronavirus, severe acute images but positive qRT-PCR results observation period (Jan 27–29), respiratory syndrome coronavirus (figure). with no decreases in white blood cell 2 (SARS-CoV-2), has led to a serious On Jan 22, 2020, patient 1 travelled or lymphocyte counts (appendix). epidemic in China and other from Wuhan (Hubei, China) to Chest CT images taken from these countries, resulting in worldwide Guangzhou (Guangdong, China) two patients on Jan 28 did not show concern.1 Family clusters of infected with his wife (patient 2) and son significant abnormalities. However, individuals have been reported, and (patient 3) by high-speed rail. On two sets of nasopharyngeal swab this phenomenon could present a Jan 26, patient 1 developed a fever samples, taken at the same time as serious threat to public health if not of 37·5°C, which lasted for 1 day. those from patient 1, tested positive strictly controlled. In a previously The next day, the patient presented for SARS-CoV-2 on qRT-PCR. All three reported family cluster, most infected to the Third Affiliated Hospital of family members were diagnosed with individuals had clinical symptoms, Guangzhou Medical University SARS-CoV-2 infection and were thus decreased lymphocyte counts, and with a body temperature of 37·4°C, transferred to the Infectious Diseases abnormal chest CT images, and were and on the same day developed Unit of the Eighth People’s Hospital positive for the virus on quantitative a sore throat, arthralgia, and of Guangzhou for isolation and RT-PCR (qRT-PCR) analysis.2,3 myalgia, without chills or headache. treatment. However, some of the family Patient 1 was observed from In this family cluster, although members had abnormal chest CT Jan 27 to Jan 29, during which time all individuals tested positive for images and positive qRT-PCR results his body temperature normalised. SARS-CoV-2 infection on qRT-PCR, without any clinical symptoms.3 Here, On Jan 27, routine blood tests only patient 1 showed clinical we report the clinical characteristics showed normal white blood cell and symptoms, decreased lymphocyte of a family cluster of SARS-CoV-2 lymphocyte counts, but decreased count, and abnormal chest CT images See Online for appendix infection. In this family of three, lymphocyte percentage (appendix). (figure). However, any of the three one 35-year-old man (patient 1) Chest CT scans taken 2 days after individuals could have been the first had clinical symptoms, a decreased symptom onset showed bilateral one to become infected and thus lymphocyte count, abnormal chest multiple lobular and subsegmental transmitted the virus to the other two family members. Importantly,

Patient 1 Symptoms asymptomatic patients (such as (father) patients 2 and 3) might be unaware of CT and qRT-PCR their disease and therefore not isolate positive themselves or seek treatment, or they might be overlooked by health-care Patient 2 No symptoms professionals and thus unknowingly (mother) qRT-PCR positive transmit the virus to others. To prevent and control this highly infectious disease as early as possible, Patient 3 No symptoms (son) people with family members with qRT-PCR positive SARS-CoV-2 infection should be closely monitored and examined to rule out infection, even if they do not have any symptoms. In the case of Jan 22 Jan 23 Jan 24 Jan 25 Jan 26 Jan 27 Jan 28 Jan 29 2020 this family, since the time between presentation and identification of Wuhan Guangzhou SARS-CoV-2 infection was short, more studies are needed to observe the Figure: Chronology of symptom onset and identification of positive SARS-CoV-2 findings on qRT-PCR and CT among the family cluster symptoms and test results of infected qRT-PCR=quantitative RT-PCR. individuals in greater detail.

410 www.thelancet.com/infection Vol 20 April 2020 Correspondence

We declare no competing interests. XP and DC N-gene-specific quantitative RT-PCR We also studied respiratory samples contributed equally to this work. Patient consent assay, as described elsewhere.3 The (nasal [n=1] and throat swabs [n=67], was obtained. viral loads in throat swab and sputum and sputum [n=42]) collected from Published Online *Xingfei Pan, Dexiong Chen, Yong Xia, samples peaked at around 5–6 days 80 individuals at different stages of February 24, 2020 Xinwei Wu, Tangsheng Li, Xueting Ou, https://doi.org/10.1016/ after symptom onset, ranging from infection. The viral loads ranged from S1473-3099(20)30113-4 Liyang Zhou, *Jing Liu around 10⁴ to 10⁷ copies per mL during 641 copies per mL to 1·34 × 10¹¹ copies [email protected] or this time (figure A, B). This pattern per mL, with a median of 7·99 × 10⁴ [email protected] of changes in viral load is distinct in throat samples and 7·52 × 10⁵ in Department of Infectious Diseases (XP, XO, LZ), from the one observed in patients sputum samples (figureC). The only Emergency Department (DC), Department of with SARS, which normally peaked at nasal swab tested in this study (taken Clinical Laboratory (YX), and Department of 4 Radiology (TL), Third Affiliated Hospital of around 10 days after onset. Sputum on day 3 post-onset) showed a viral Guangzhou Medical University, Guangzhou, samples generally showed higher load of 1·69 × 10⁵ copies per mL. Guangdong 510150, China; Department of viral loads than throat swab samples. Overall, the viral load early after onset Microbiology, Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, No viral RNA was detected in urine or was high (>1 × 10⁶ copies per mL). China (XW); Department of Gastroenterology, stool samples from these two patients. However, a sputum sample collected Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, China (JL); and Hubei Clinical Center and Key Laboratory of Intestinal and Colorectal Diseases, Wuhan, Hubei, China (JL) A Patient 1 B Patient 2 1 Zhu N, Zhang D, Wang W, et al. A novel 8 Throat swab 8 coronavirus from patients with pneumonia in Sputum 7 China, 2019. N Engl J Med 2020; published 7 online Jan 24. DOI:10.1056/NEJMoa2001017. 6 2 Huang C, Wang Y, Li X, et al. Clinical features of 6 patients infected with 2019 novel coronavirus 5 in Wuhan, China. Lancet 2020; 395: 497–506. 5

3 Chan JF-W, Yuan S, Kok K-H, et al. A familial copies per mL) 4 copies per mL)

10 4 cluster of pneumonia associated with the 2019 10 novel coronavirus indicating person-to-person 3 3 transmission: a study of a family cluster. Lancet 2020; 395: 514–23. 2 2 Viral load (log Viral load (log

1 1

Viral load of SARS-CoV-2 0 0 021 3456789101112 0 1 2345678910 11 12 13 14 15 in clinical samples Days after onset Days after onset An outbreak caused by a novel C D human coronavirus, severe 12 Throat swab 12 acute respiratory syndrome Sputum coronavirus 2 (SARS-CoV-2) was 11 10 first detected in Wuhan in December 10 1 9 2019, and has since spread within 8

China and to other countries. Real- copies per mL) 8 10 time RT-PCR assays are recommended copies per mL) 7 10 6 for diagnosis of SARS-CoV-2 6 2 infection. However, viral dynamics 4 5 Days after onset in infected patients are still yet to –1 to 0 (n =7) Viral load (log 4 1 to 3 (n=10) be fully determined. Here, we report 2 4 to 7 (n=9) Viral load in sputum (log 3 our findings from different types of 8 to 14 (n=4) clinical specimens collected from 0 2 82 infected individuals. -1 012345678910 11 12 13 14 15 246810 12 Days after onset Viral load in throat swab (log copies per mL) Serial samples (throat swabs, 10 Days after onset –1 0 1 2 3 4 5 6 7 8 11 13 15 sputum, urine, and stool) from Throat swab, n 1 10 12 4 12 12 3 4 2 4 1 1 1 two patients in Beijing were collected Sputum, n 1 9 4 3 5 9 0 3 2 4 0 2 0 daily after their hospitalisation (patient 1, days 3–12 post-onset; Figure: Viral dynamics of SARS-CoV-2 in infected patients Viral load (mean [SD]) from serial throat swab and sputum samples in patient 1 (A) and patient 2 (B). (C) Viral load (median [IQR]) patient 2, days 4–15 post-onset). in throat and sputum samples collected from 80 patients at different stages after disease onset. (D) Correlation between viral load in throat These samples were examined by an swab samples and viral load in sputum samples.

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Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis

Derek K Chu, Elie A Akl, Stephanie Duda, Karla Solo, Sally Yaacoub, Holger J Schünemann, on behalf of the COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors*

Summary Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and is spread person- Published Online to-person through close contact. We aimed to investigate the effects of physical distance, face masks, and eye June 1, 2020 https://doi.org/10.1016/ protection on virus transmission in health-care and non-health-care (eg, community) settings. S0140-6736(20)31142-9 See Online/Comment Methods We did a systematic review and meta-analysis to investigate the optimum distance for avoiding person-to- https://doi.org/10.1016/ person virus transmission and to assess the use of face masks and eye protection to prevent transmission of viruses. S0140-6736(20)31183-1 We obtained data for SARS-CoV-2 and the betacoronaviruses that cause severe acute respiratory syndrome, and *Study authors are listed in the Middle East respiratory syndrome from 21 standard WHO-specific and COVID-19-specific sources. We searched appendix and at the end of the these data sources from database inception to May 3, 2020, with no restriction by language, for comparative studies Article and for contextual factors of acceptability, feasibility, resource use, and equity. We screened records, extracted data, Department of Health Research Methods, Evidence and Impact and assessed risk of bias in duplicate. We did frequentist and Bayesian meta-analyses and random-effects meta- (D K Chu MD, S Duda MSc, regressions. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. This study K Solo MSc, Prof E A Akl MD, is registered with PROSPERO, CRD42020177047. Prof H J Schünemann MD), and Department of Medicine (D K Chu, Prof H J Schünemann), Findings Our search identified 172 observational studies across 16 countries and six continents, with no randomised McMaster University, controlled trials and 44 relevant comparative studies in health-care and non-health-care settings (n=25 697 patients). Hamilton, ON, Canada; Transmission of viruses was lower with physical distancing of 1 m or more, compared with a distance of less than 1 m The Research Institute of (n=10 736, pooled adjusted odds ratio [aOR] 0·18, 95% CI 0·09 to 0·38; risk difference [RD] –10·2%, 95% CI St Joe’s Hamilton, Hamilton, ON, Canada (D K Chu); –11·5 to –7·5; moderate certainty); protection was increased as distance was lengthened (change in relative risk Department of Internal

[RR] 2·02 per m; pinteraction=0·041; moderate certainty). Face mask use could result in a large reduction in risk of Medicine (Prof E A Akl), and infection (n=2647; aOR 0·15, 95% CI 0·07 to 0·34, RD –14·3%, –15·9 to –10·7; low certainty), with stronger Clinical Research Institute associations with N95 or similar respirators compared with disposable surgical masks or similar (eg, reusable (Prof E A Akl, S Yaacoub MPH), American University of Beirut, 12–16-layer cotton masks; pinteraction=0·090; posterior probability >95%, low certainty). Eye protection also was associated Beirut, Lebanon; and with less infection (n=3713; aOR 0·22, 95% CI 0·12 to 0·39, RD –10·6%, 95% CI –12·5 to –7·7; low certainty). Michael G DeGroote Cochrane Unadjusted studies and subgroup and sensitivity analyses showed similar findings. Canada and GRADE Centres, Hamilton, ON, Canada (Prof H J Schünemann) Interpretation The findings of this systematic review and meta-analysis support physical distancing of 1 m or more Correspondence to: and provide quantitative estimates for models and contact tracing to inform policy. Optimum use of face masks, Prof Holger J Schünemann, respirators, and eye protection in public and health-care settings should be informed by these findings and contextual Michael G DeGroote Cochrane factors. Robust randomised trials are needed to better inform the evidence for these interventions, but this systematic Canada and McMaster GRADE appraisal of currently best available evidence might inform interim guidance. Centres, McMaster University, Hamilton, ON L8N 3Z5, Canada [email protected] Funding World Health Organization. See Online for appendix

Copyright © 2020 World Health Organization. Published by Elsevier Ltd. This is an Open Access article published under the CC BY 3.0 IGO license which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In any use of this article, there should be no suggestion that WHO endorses any specific organisation, products or services. The use of the WHO logo is not permitted. This notice should be preserved along with the article’s original URL.

Introduction throughout societies and by individuals. With no effective As of May 28, 2020, severe acute respiratory syndrome pharmacological interventions or vaccine available in coronavirus 2 (SARS-CoV-2) has infected more than the imminent future, reducing the rate of infection 5·85 million individuals worldwide and caused more than (ie, flattening the curve) is a priority, and prevention of 359 000 deaths.1 Emergency lockdowns have been initiated infection is the best approach to achieve this aim. in countries across the globe, and the effect on health, SARS-CoV-2 spreads person-to-person through close wellbeing, business, and other aspects of daily life are felt contact and causes COVID-19. It has not been solved if www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 1 Articles

Research in context Evidence before this study personal protection strategies acceptable, feasible, and reassuring We searched 21 databases and resources from inception to but noted harms and contextual challenges, including frequent May 3, 2020, with no restriction by language, for studies of any discomfort and facial skin breakdown, high resource use linked design evaluating physical distancing, face masks, and eye with the potential to decrease equity, increased difficulty protection to prevent transmission of the viruses that cause communicating clearly, and perceived reduced empathy of care COVID-19 and related diseases (eg, severe acute respiratory providers by those they were caring for. syndrome [SARS] and Middle East respiratory syndrome Implications of all the available evidence [MERS]) between infected individuals and people close to them In view of inconsistent guidelines by various organisations (eg, household members, caregivers, and health-care workers). based on limited information, our findings provide some Previous related meta-analyses have focused on randomised clarification and have implications for multiple stakeholders. trials and reported imprecise data for common respiratory The risk for infection is highly dependent on distance to the viruses such as seasonal influenza, rather than the pandemic and individual infected and the type of face mask and eye epidemic betacoronaviruses causative of COVID-19 (severe protection worn. From a policy and public health perspective, acute respiratory syndrome coronavirus 2 [SARS-CoV-2]), current policies of at least 1 m physical distancing seem to be SARS (SARS-CoV), or MERS (MERS-CoV). Other meta-analyses strongly associated with a large protective effect, and distances have focused on interventions in the health-care setting and of 2 m could be more effective. These data could also facilitate have not included non-health-care (eg, community) settings. harmonisation of the definition of exposed (eg, within 2 m), Our search did not retrieve any systematic review of information which has implications for contact tracing. The quantitative on physical distancing, face masks, or eye protection to prevent estimates provided here should inform disease-modelling transmission of SARS-CoV-2, SARS-CoV, and MERS-CoV. studies, which are important for planning pandemic response Added value of this study efforts. Policy makers around the world should strive to We did a systematic review of 172 observational studies in promptly and adequately address equity implications for health-care and non-health-care settings across 16 countries and groups with currently limited access to face masks and eye six continents; 44 comparative studies were included in a protection. For health-care workers and administrators, meta-analysis, including 25 697 patients with COVID-19, SARS, our findings suggest that N95 respirators might be more or MERS. Our findings are, to the best of our knowledge, the first strongly associated with protection from viral transmission to rapidly synthesise all direct information on COVID-19 and, than surgical masks. Both N95 and surgical masks have a therefore, provide the best available evidence to inform optimum stronger association with protection compared with use of three common and simple interventions to help reduce the single-layer masks. Eye protection might also add substantial rate of infection and inform non-pharmaceutical interventions, protection. For the general public, evidence shows that physical including pandemic mitigation in non-health-care settings. distancing of more than 1 m is highly effective and that face Physical distancing of 1 m or more was associated with a much masks are associated with protection, even in non-health-care lower risk of infection, as was use of face masks (including settings, with either disposable surgical masks or reusable N95 respirators or similar and surgical or similar masks 12–16-layer cotton ones, although much of this evidence was [eg, 12–16-layer cotton or gauze masks]) and eye protection on mask use within households and among contacts of cases. (eg, goggles or face shields). Added benefits are likely with even Eye protection is typically underconsidered and can be effective larger physical distances (eg, 2 m or more based on modelling) in community settings. However, no intervention, even when and might be present with N95 or similar respirators versus properly used, was associated with complete protection from medical masks or similar. Across 24 studies in health-care and infection. Other basic measures (eg, hand hygiene) are still non-health-care settings of contextual factors to consider when needed in addition to physical distancing and use of face masks formulating recommendations, most stakeholders found these and eye protection.

SARS-CoV-2 might spread through aerosols from Thus, quantitative assessment of physical distancing is respiratory droplets; so far, air sampling has found virus relevant to inform safe interaction and care of patients RNA in some studies2–4 but not in others.5–8 However, with SARS-CoV-2 in both health-care and non-health-care finding RNA virus is not necessarily indicative of repli­ settings. The definition of close contact or potentially cation-competent and infection-competent (viable) virus exposed helps to risk stratify, contact trace, and develop that could be transmissible. The distance from a patient guidance docu­ments, but these definitions differ around that the virus is infective, and the optimum person-to- the globe. person physical distance, is uncertain. For the currently To contain widespread infection and to reduce foreseeable future (ie, until a safe and effective vaccine or morbidity and mortality among health-care workers treatment becomes available),­ COVID-19 prevention will and others in contact with potentially infected people, con­tinue to rely on non-pharmaceutical interventions, jurisdictions have issued conflicting advice about including pandemic mitigation in community settings.9 physical or social distancing. Use of face masks with or

2 www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 Articles

without eye protection to achieve additional protection is papers, and relevant systematic reviews.19,20 We hand­ debated in the mainstream media and by public health searched (up to May 3, 2020) preprint servers (bioRxiv, authorities, in particular the use of face masks for the medRxiv, and Social Science Research Network First general population;10 moreover, optimum use of face Look) and coronavirus resource centres of The Lancet, masks in health-care settings, which have been used for JAMA, and N Engl J Med (appendix pp 3–5). We did not decades for infection prevention, is facing challenges limit our search by language. We initially could not obtain amid personal protective equipment (PPE) shortages.11 three full texts for evaluation, but we obtained them Any recommendations about social or physical through interlibrary loan or contacting a study author. We distancing, and the use of face masks, should be based on did not restrict our search to any quantitative cutoff for the best available evidence. Evidence has been reviewed distance. for other respiratory viral infections, mainly seasonal influenza,12,13 but no comprehensive review is available of Data collection information on SARS-CoV-2 or related betacoronaviruses We screened titles and abstracts, reviewed full texts, that have caused epidemics, such as severe acute extracted data, and assessed risk of bias by two authors respiratory syndrome (SARS) or Middle East respiratory and independently, using standardised prepiloted forms syndrome (MERS). We, therefore, systematically reviewed (Covidence; Veritas Health Innovation, Melbourne, VIC, the effect of physical distance, face masks, and eye Australia), and we cross-checked screening results using protection on transmission of SARS-CoV-2, SARS-CoV, artificial intelligence (Evidence Prime, Hamilton, ON, and MERS-CoV. Canada). We resolved disagreements by consensus. We extracted data for study identifier, study design, setting, Methods population characteristics, intervention and comparator Search strategy and selection criteria characteristics, quantitative outcomes, source of funding To inform WHO guidance documents, on March 25, 2020, we did a rapid systematic review.14 We created a large 17 678 records identified through traditional 10 222 records identified through additional sources international collaborative and we used Cochrane meth­ database searching 8859 COVID-19 specific databases ods15 and the GRADE approach.16 We prospectively sub­ 3314 MEDLINE 870 clinical trials registries 975 PubMed 9 hand-searching mitted the systematic review protocol for registration 11 115 Embase 4 screening references of included studies on PROSPERO (CRD42020177047; appendix pp 23–29). 567 CINAHL 480 other We have followed PRISMA17 and MOOSE18 reporting 43 Cochrane Library 1664 Chinese databases guidelines (appendix pp 30–33). From database inception to May 3, 2020, we searched for studies of any design and in any setting that included patients with WHO-defined confirmed or probable 20 013 records after duplicates removed COVID-19, SARS, or MERS, and people in close contact with them, comparing distances between people and 20 013 records screened against title and abstract COVID-19 infected patients of 1 m or larger with smaller distances, with or without a face mask on the patient, or with or without a face mask, eye protection, or both on 19 409 records excluded the exposed individual. The aim of our systematic review was for quantitative assessment to ascertain the physical 604 full-text articles assessed for eligibility distance associated with reduced risk of acquiring infection when caring for an individual infected with SARS-CoV-2, SARS-CoV, or MERS-CoV. Our definition of 432 studies excluded 166 wrong study design (eg, editorial, face masks included surgical masks and N95 respirators, narrative review, guideline, among others; eye protection included visors, faceshields, commentary, letter, modelling and goggles, among others. without primary clinical data) 118 wrong outcomes We searched (up to March 26, 2020) MEDLINE (using 88 wrong or no intervention the Ovid platform), PubMed, Embase, CINAHL (using 52 wrong patient population 6 duplicates the Ovid platform), the Cochrane Library, COVID-19 Open 2 news articles Research Dataset Challenge, COVID-19 Research Database (WHO), Epistemonikos (for relevant systematic reviews addressing MERS and SARS, and its COVID-19 172 studies included in systematic review Living Overview of the Evidence platform), EPPI Centre living systematic map of the evidence, ClinicalTrials.gov, 44 comparative studies included in WHO International Clinical Trials Registry Platform, meta-analysis relevant documents on the websites of governmental and other relevant organisations, reference lists of included Figure 1: Study selection www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 3 Articles

Population Country Setting Disease Case definition Adjusted Risk of bias* size (n) caused by (WHO) estimates virus

Alraddadi et al (2016)34 283 Saudi Arabia Health care MERS Confirmed Yes ∗∗∗∗∗∗∗∗ Arwady et al (2016)35 79 Saudi Arabia Non-health care MERS Confirmed No ∗∗∗∗∗∗ (household and family contacts) Bai et al (2020)36 118 China Health care COVID-19 Confirmed No ∗∗∗∗∗ Burke et al (2020)37 338 USA Health care and COVID-19 Confirmed No ∗∗∗∗ non-health care (including household and community) Caputo et al (2006)38 33 Canada Health care SARS Confirmed No ∗∗∗∗∗ Chen et al (2009)39 758 China Health care SARS Confirmed Yes ∗∗∗∗∗∗∗ Cheng et al (2020)40 226 China Non-health care COVID-19 Confirmed No ∗∗∗∗∗∗ (household and family contacts) Ha et al (2004)42 117 Vietnam Health care SARS Confirmed No ∗∗ Hall et al (2014)43 48 Saudi Arabia Health care MERS Confirmed No ∗∗∗ Heinzerling et al (2020)44 37 USA Health care COVID-19 Confirmed No ∗∗∗∗ Ho et al (2004)45 372 Taiwan Health care SARS Confirmed No ∗∗∗∗∗∗∗∗ Ki et al (2019)47 446 South Korea Health care MERS Confirmed No ∗∗∗∗∗∗ Kim et al (2016)48 9 South Korea Health care MERS Confirmed No ∗∗∗∗∗ Kim et al (2016)49 1169 South Korea Health care MERS Confirmed No ∗∗∗∗∗∗ Lau et al (2004)50 2270 China Non-health care SARS Probable Yes ∗∗∗∗∗∗ (households) Liu et al (2009)51 477 China Health care SARS Confirmed Yes ∗∗∗∗∗ Liu et al (2020)52 20 China Non-health care (close COVID-19 Confirmed No ∗∗∗∗∗∗∗ contacts) Loeb et al (2004)53 43 Canada Health care SARS Confirmed No ∗∗ Ma et al (2004)54 426 China Health care SARS Confirmed Yes ∗∗∗∗∗∗∗∗∗ Nishiura et al (2005)55 115 Vietnam Health care SARS Confirmed Yes ∗∗∗∗∗∗∗∗ Nishiyama et al (2008)56 146 Vietnam Health care SARS Confirmed Yes ∗∗∗∗∗∗ Olsen et al (2003)57 304 China Non-health care SARS Confirmed No ∗∗∗∗∗∗ (airplane) Park et al (2004)58 110 USA Health care SARS Confirmed No ∗∗∗∗∗∗∗∗∗∗ Park et al (2016)59 80 South Korea Health care MERS Confirmed and No ∗∗∗ probable Peck et al (2004)60 26 USA Health care SARS Confirmed No ∗∗∗∗∗∗∗∗∗ Pei et al (2006)61 443 China Health care SARS Confirmed No ∗∗∗∗∗∗∗∗ Rea et al (2007)62 8662 Canada Non-health care SARS Probable No ∗∗∗∗ (community contacts) Reuss et al (2014)63 81 Germany Health care MERS Confirmed No ∗∗∗∗∗ Reynolds et al (2006)64 153 Vietnam Health care SARS Confirmed No ∗∗∗ Ryu et al (2019)65 34 South Korea Health care MERS Confirmed No ∗∗∗∗∗∗ Scales et al (2003)66 69 Canada Health care SARS Probable No ∗∗ Seto et al (2003)67 254 China Health care SARS Confirmed Yes ∗∗∗∗∗∗∗∗ Teleman et al (2004)68 86 Singapore Health care SARS Confirmed Yes ∗∗∗∗∗∗∗∗ Tuan et al (2007)69 212 Vietnam Non-health care SARS Confirmed Yes ∗∗∗∗∗∗ (household and community contacts) Van Kerkhove et al 828 Saudi Arabia Non-health care MERS Confirmed Yes ∗∗∗∗∗∗∗∗ (2019)46 (dormitory) Wang et al (2020)41 493 China Health care COVID-19 Confirmed Yes ∗∗∗∗ (Table 1 continues on next page)

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n Country Setting Disease Case definition Adjusted Risk of bias* caused by (WHO) estimates virus (Continued from previous page) Wang et al (2020)70 5442 China Health care COVID-19 Confirmed No ∗∗∗∗∗ Wiboonchutikul et al 38 Thailand Health care MERS Confirmed No ∗∗∗∗∗ (2016)71 Wilder-Smith et al 80 Singapore Health care SARS Confirmed No ∗∗∗∗∗∗∗∗ (2005)72 Wong et al (2004)73 66 China Health care SARS Confirmed No ∗∗∗∗∗ Wu et al (2004)74 375 China Non-health care SARS Confirmed Yes ∗∗∗∗∗∗∗∗ (community) Yin et al (2004)75 257 China Health care SARS Confirmed Yes ∗∗∗∗∗∗ Yu et al (2005)76 74 China Health care SARS Confirmed No ∗∗∗∗∗∗∗ Yu et al (2007)77 124 wards China Health care SARS Confirmed Yes ∗∗∗∗∗∗∗

Across studies, mean age was 30–60 years. SARS=severe acute respiratory syndrome. MERS=Middle East respiratory syndrome. *The Newcastle-Ottawa Scale was used for the risk of bias assessment, with more stars equalling lower risk.

Table 1: Characteristics of included comparative studies and reported conflicts of interests, ethics approval, study to every study’s design (cohort or case-control).23,24 We limitations, and other important comments. planned to use the Cochrane Risk of Bias tool 2.0 for randomised trials,25 but our search did not identify any Outcomes eligible randomised trials. We synthesised data in both Outcomes of interest were risk of transmission (ie, WHO- narrative and tabular formats. We graded the certainty of defined confirmed or probable COVID-19, SARS, or evidence using the GRADE approach. We used the MERS) to people in health-care or non-health-care settings GRADEpro app to rate evidence and present it in GRADE For more on the GRADEpro app by those infected; hospitalisation; intensive care unit evidence profiles and summary of findings tables26,27 see https://www.gradepro.org admission; death; time to recovery; adverse effects of using standardised terms.28,29 interventions; and contextual factors such as acceptability, We analysed data for subgroup effects by virus type, feasibility, effect on equity, and resource considerations intervention (different distances or face mask types), and related to the interventions of interest. However, data setting (health care vs non-health care). Among the studies were only available to analyse intervention effects for assessing physical distancing measures to prevent viral transmission and con­textual factors. Consistent with transmission, the intervention varied (eg, direct physical WHO, studies generally defined confirmed cases with contact [0 m], 1 m, or 2 m). We, therefore, analysed laboratory confirmation (with or without symptoms) and the effect of distance on the size of the associ­ations probable cases with clinical evidence of the respective by random-effects univariate meta-regressions, using infection (ie, suspected to be infected) but for whom restricted maximum likelihood, and we present mean confirmatory testing either had not yet been done for any effects and 95% CIs. We calculated tests for interaction reason or was inconclusive. using a minimum of 10 000 Monte Carlo random permutations to avoid spurious findings.30 We formally Data analysis assessed the credibility of potential effect-modifiers using Our search did not identify any randomised trials of GRADE guidance.21 We did two sensitivity analyses to test COVID-19, SARS, or MERS. We did a meta-analysis of the robustness of our findings. First, we used Bayesian associations by pooling risk ratios (RRs) or adjusted odds meta-analyses to reinterpret the included studies ratios (aORs) depending on availability of these data from considering priors derived from the effect point estimate observational studies, using DerSimonian and Laird ran­ and variance from a meta-analysis of ten randomised dom-effects models. We adjusted for variables including trials evaluating face mask use versus no face mask use to age, sex, and severity of source case; these variables were prevent influenza-like illness in health-care workers.31 not the same across studies. Because between-study Second, we used Bayesian meta-analyses to reinterpret heterogeneity can be misleadingly large when quantified the efficacy of N95 respirators versus medical masks by I² during meta-analysis of observational­ studies,21,22 on preventing influenza-like illness after seasonal viral we used GRADE guidance to assess between-study hetero­ (mostly influenza) infection.13 For these sensitivity geneity.21 Throughout, we present RRs as unadjusted analyses, we used hybrid Metropolis-Hastings and Gibbs estimates and aORs as adjusted estimates. sampling, a 10 000 sample burn-in, 40 000 Markov chain We used the Newcastle-Ottawa scale to rate risk of bias Monte Carlo samples, and we tested non-informative for comparative non-randomised studies corresponding and sceptical priors (eg, four time variance)32,33 to inform www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 5 Articles

Country Respirator Distance Events, further Events, shorter RR (95% CI) % weight (0=no) (m) distance (n/N) distance (n/N) (random)

MERS Van Kerkhove et al (2019)46 Saudi Arabia 0 0 8/774 11/54 0·05 (0·02–0·12) 5·5 Arwady et al (2016)35 Saudi Arabia 0 1 1/10 8/20 0·25 (0·04–1·73) 2·6 Ki et al (2019)47 South Korea 1 2 2/29 4/42 0·72 (0·14–3·70) 3·2 Park et al (2016)59 South Korea 0 2 0/3 5/25 0·59 (0·04–8·77) 1·6 Hall et al (2014)43 Saudi Arabia 1 1 0/5 0/43 (Not calculable) 0 Wiboonchutikul et al (2019)71 Thailand 1 1 0/16 0/22 (Not calculable) 0 Reuss et al (2014)63 Germany 1 2 0/12 0/69 (Not calculable) 0 Ryu et al (2019)65 South Korea 1 2 0/7 0/27 (Not calculable) 0 Random, subtotal (I2=75%) 11/856 28/302 0·23 (0·04–1·20) 12·9

SARS Scales et al (2003)66 Canada 0 0 1/12 6/19 0·35 (0·05–2·57) 2·6 Ma et al (2004)54 China 1 0* 4/149 43/294 0·18 (0·07–0·50) 5·0 Nishiyama et al (2008)56 Vietnam 0 0 1/12 26/73 0·23 (0·03–1·57) 2·7 Tuan et al (2007)69 Vietnam 0 0 3/123 6/57 0·23 (0·06–0·89) 3·9 Rea et al (2007)62 Canada 0 1 18/3493 41/647 0·08 (0·05–0·14) 6·6 Chen et al (2009)39 China 0 1* 28/314 63/445 0·63 (0·41–0·96) 6·9 Lau et al (2004)50 China 0 1 39/965 136/1124 0·33 (0·24–0·47) 7·1 Liu et al (2009)51 China 0 0 14/133 39/341 0·92 (0·52–1·64) 6·5 Pei et al (2006)61 China 0 1 8/61 139/382 0·36 (0·19–0·70) 6·2 Wong et al (2004)73 China 0 1 0/4 3/3 0·11 (0·01–1·63) 1·7 Teleman et al (2004)68 Singapore 1 1 4/9 32/77 1·07 (0·49–2·33) 5·8 Reynolds et al (2006)64 Vietnam 0 1 5/38 17/29 0·22 (0·09–0·54) 5·5 Olsen et al (2003)57 China 0 1·5 9/84 11/35 0·34 (0·16–0·75) 5·8 Wong et al (2004)73 China 0 2 0/4 4/8 0·20 (0·01–3·00) 1·6 Loeb et al (2004)53 Canada 1 2* 0/11 8/40 0·20 (0·01–3·24) 1·6 Yu et al (2005)76 China 1 2 17/54 13/20 0·48 (0·29–0·81) 6·6 Peck et al (2004)60 USA 1 1 0/3 0/38 (Not calculable) 0 Random, subtotal (I2=75%) 151/5469 587/3632 0·35 (0·23–0·52) 76·1

COVID-19 Bai et al (2020)36 China 1 0 0/76 12/42 0·02 (0·001–0·37) 1·5 Burke et al (2020)37 USA 0 0 0/13 2/2 0·04 (0·003–0·68) 1·6 Liu et al (2020)52 China 0 1 0/17 2/3 0·04 (0·003–0·76) 1·5 Cheng et al (2020)40 Taiwan 0 1* 5/47 7/36 0·55 (0·19–1·58) 4·8 Heinzerling et al (2020)44 USA 0 1·8 0/4 3/33 0·97 (0·06–16·14) 1·5 Burke et al (2020)37 USA 1 0 0/50 0/76 (Not calculable) 0 Burke et al (2020)37 USA 0 2 0/41 0/37 (Not calculable) 0 Random, subtotal (I2=59%) 5/248 26/229 0·15 (0·03–0·73) 10·9

Unadjusted estimates, overall (I2=73%) 167/6573 641/4163 0·30 (0·20–0·44) 100·0 Adjusted estimates, overall (1 MERS, 8 SARS) aOR 0·18 (0·09–0·38) aRR 0·20 (0·10–0·41) Interaction by type of virus p=0·49 0·1 0·5 12 10

Favours further distance Favours shorter distance

Figure 2: Forest plot showing the association of COVID-19, SARS, or MERS exposure proximity with infection SARS=severe acute respiratory syndrome. MERS=Middle East respiratory syndrome. RR=relative risk. aOR=adjusted odds ratio. aRR=adjusted relative risk. *Estimated values; sensitivity analyses excluding these values did not meaningfully alter findings.

mean estimates of effect, 95% credibility intervals (CrIs), Role of the funding source and posterior distri­butions. We used non-informative The funder contributed to defining the scope of the hyperpriors to estimate­­ statistical heterogeneity. Model review but otherwise had no role in study design and convergence was confirmed in all cases with good mixing data collection. Data were interpreted and the report in visual inspection of trace plots, autocorrelation plots, drafted and submitted without funder input, but histo­grams, and kernel density estimates in all scenarios. according to contractual agreement, the funder provided Parameters were blocked, leading to acceptance of review at the time of final publication. The corresponding approximately 50% and efficiency greater than 1% in all author had full access to all data in the study and had cases (typically about 40%). We did analyses using Stata final responsibility for the decision to submit for version 14.3. publication.

6 www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 Articles

Studies and Relative effect Anticipated absolute effect (95% CI), Difference Certainty* What happens (standardised GRADE participants (95% CI) eg, chance of viral infection or (95% CI) terminology)29 transmission Comparison Intervention group group Physical distance Nine adjusted studies aOR 0·18 (0·09 to 0·38); Shorter distance, Further distance, –10·2% Moderate† A physical distance of more than 1 m ≥1 m vs <1 m (n=7782); 29 unadjusted unadjusted RR 0·30 12·8% 2·6% (1·3 to 5·3) (–11·5 to –7·5) probably results in a large reduction in studies (n=10 736) (95% CI 0·20 to 0·44) virus infection; for every 1 m further away in distancing, the relative effect might increase 2·02 times Face mask vs no face Ten adjusted studies aOR 0·15 (0·07 to 0·34); No face mask, Face mask, –14·3% Low‡ Medical or surgical face masks might mask (n=2647); 29 unadjusted unadjusted RR 0·34 17·4% 3·1% (1·5 to 6·7) (–15·9 to –10·7) result in a large reduction in virus studies (n=10 170) (95% CI 0·26 to 0·45) infection; N95 respirators might be associated with a larger reduction in risk compared with surgical or similar masks§ Eye protection 13 unadjusted studies Unadjusted RR 0·34 No eye Eye protection, –10·6% Low|| Eye protection might result in a large (faceshield, goggles) (n=3713) (0·22 to 0·52)¶ protection, 5·5% (3·6 to 8·5) (–12·5 to –7·7) reduction in virus infection vs no eye protection 16·0%

Table based on GRADE approach.26–29 Population comprised people possibly exposed to individuals infected with SARS-CoV-2, SARS-CoV, or MERS-CoV. Setting was any health-care or non-health-care setting. Outcomes were infection (laboratory-confirmed or probable) and contextual factors. Risk (95% CI) in intervention group is based on assumed risk in comparison group and relative effect (95% CI) of the intervention. All studies were non-randomised and evaluated using the Newcastle-Ottawa Scale; some studies had a higher risk of bias than did others but no important difference was noted in sensitivity analyses excluding studies at higher risk of bias; we did not further rate down for risk of bias. Although there was a high I2 value (which can be exaggerated in non-randomised studies)21 and no overlapping CIs, point estimates generally exceeded the thresholds for large effects and we did not rate down for inconsistency. We did not rate down for indirectness for the association between distance and infection because SARS-CoV-2, SARS-CoV, and MERS-CoV all belong to the same family and have each caused epidemics with sufficient similarity; there was also no convincing statistical evidence of effect-modification across viruses; some studies also used bundled interventions but the studies include only those that provide adjusted estimates. aOR=adjusted odds ratio. RR=relative risk. SARS-CoV-2=severe acute respiratory syndrome coronavirus 2. SARS-CoV=severe acute respiratory syndrome coronavirus. MERS-CoV=Middle East respiratory syndrome coronavirus. *GRADE category of evidence; high certainty (we are very confident that the true effect lies close to that of the estimate of the effect); moderate certainty (we are moderately confident in the effect estimate; the true effect is probably close to the estimate, but it is possibly substantially different); low certainty (our confidence in the effect estimate is limited; the true effect could be substantially different from the estimate of the effect); very low certainty (we have very little confidence in the effect estimate; the true effect is likely to be substantially different from the estimate of effect). †The effect is very large considering the thresholds set by GRADE, particularly at plausible levels of baseline risk, which also mitigated concerns about risk of bias; data also suggest a dose–response gradient, with associations increasing from smaller distances to 2 m and beyond, by meta-regression; we did not rate up for this domain alone but it further supports the decision to rate up in combination with the large effects. ‡The effect was very large, and the certainty of evidence could be rated up, but we made a conservative decision not to because of some inconsistency and risk of bias; hence, although the effect is qualitatively highly certain, the precise quantitative effect is low certainty. §In a subgroup analysis comparing N95 respirators with surgical or similar masks (eg, 12–16-layer cotton), the association was more pronounced in the N95 group (aOR 0·04, 95% CI 0·004–0·30) compared with other masks (0·33, 54,75 0·17–0·61; pinteraction=0·090); there was also support for effect-modification by formal analysis of subgroup credibility. ¶Two studies provided adjusted estimates with n=295 in the eye protection group and n=406 in the group not wearing eye protection; results were similar to the unadjusted estimate (aOR 0·22, 95% CI 0·12–0·39). ||The effect is large considering the thresholds set by GRADE assuming that ORs translate into similar magnitudes of RR estimates; this mitigates concerns about risk of bias, but we conservatively decided not to rate up for large or very large effects.

Table 2: GRADE summary of findings

Results design),36,37,40,41,44,52,70 but most studies reported on SARS We identified 172 studies for our systematic review from (n=55) or MERS (n=25; appendix pp 6–12). Of the 16 countries across six continents (figure 1; appendix 44 comparative studies, 40 included WHO-defined pp 6–14, 41–47). Studies were all observational in nature; confirmed cases, one included both confirmed and no randomised trials were identified of any interventions probable cases, and the remaining three studies included that directly addressed the included study populations. Of probable cases. There was no effect-modification by case- the 172 studies, 66 focused on how far a virus can travel by definition (distance interactionp =0·41; mask pinteraction=0·46; all comparing the association of different distances on virus cases for eye protection were confirmed). Most studies transmission to people (appendix pp 42–44). Of these reported on bundled interven­tions, including different 66 studies, five were mechanistic, assessing viral RNA, components of PPE and distancing, which was usually virions, or both cultured from the environment of an addressed by statistical adjustment. The included studies infec­ted patient (appendix p 45). all occurred during recurrent or novel outbreak settings of 44 studies were comparative34–77 and fulfilled criteria for COVID-19, SARS, or MERS. our meta-analysis (n=25 697; figure 1; table 1). We used Risk of bias was generally low-to-moderate after these studies rather than case series and qualitative con­sidering the observational designs (table 1), but both studies (appendix pp 41–47) to inform estimates of effect. within studies and across studies the overall findings 30 studies34,37,41–45,47–51,53–56,58–61,64–70,72,74,75 focused on the asso­ were similar between adjusted and unadjusted estimates. ciation between use of various types of face masks and We did not detect strong evidence of publication bias respirators by health-care workers, patients, or both with in the body of evidence for any intervention (appendix virus transmission. 13 studies34,37–39,47,49,51,54,58,60,61,65,75 addressed pp 15–18). As we did not use case series data to inform the association of eye protection with virus transmission. estimates of effect of each intervention, we did not Some direct evidence was available for COVID-19 systematically rate risk of bias of these data. Therefore, we (64 studies, of which seven were comparative in report further only those studies with comparative data. www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 7 Articles

A association was larger with increasing distance (2·02 change in RR per m, 95% CI 1·08 to 3·76; pinteraction=0·041; 0 moderate credibility sub­group effect; figure 3A; table 2). AR values with increasing distance given different degrees of baseline risk are shown in figure 3B, with –1 potential values at 3 m also shown. Across 29 unadjusted studies and ten adjusted studies,34,37,41–45,47–51,53–56,58–61,64–70,72,74,75 the use of both N95 or similar respirators or face masks (eg, disposable surgical –2 masks or similar reusable 12–16-layer cotton masks) by

Log risk ratio those exposed to infected individuals was associated with a large reduction in risk of infection (unadjusted 95% CI –3 n=10 170, RR 0·34, 95% CI 0·26 to 0·45; adjusted studies Regression slope Study n=2647, aOR 0·15, 95% CI 0·07 to 0·34; AR 3·1% with face mask vs 17·4% with no face mask, RD –14·3%, exp(b)=2·02 per m, 95% CI 1·08–3·76; p=0·041 95% CI –15·9 to –10·7; low certainty; figure 4; table 2; –4 0 0·5 1·0 1·5 2·0 appendix pp 16, 18) with stronger associ­ations in health- Distance (m) care settings (RR 0·30, 95% CI 0·22 to 0·41) compared with non-health-care settings (RR 0·56, 95% CI B 0·40 to 0·79; pinteraction=0·049; low-to-moderate credibility 15 95% CI Cut points, mean for subgroup effect; figure 4; appendix p 19). When Out of sample predictions differential N95 or similar respirator use, which was more frequent in health-care settings than in non- High baseline risk for infection (eg, 50%) Intermediate baseline risk for infection (eg, 10%) health-care settings, was adjusted for the possibility that Low baseline risk for infection (eg, 1%) face masks were less effective in non-health-care 10 settings, the subgroup effect was slightly less credible

(pinteraction=0·11, adjusted for differential respirator use; figure 4). Indeed, the association with protection from infection was more pronounced with N95 or similar Absolute risk (%) 5 respirators (aOR 0·04, 95% CI 0·004 to 0·30) compared with other masks (aOR 0·33, 95% CI 0·17 to 0·61;

pinteraction=0·090; moderate credibility subgroup effect; figure 5). The interaction was also seen when addit­ 1 ionally adjusting for three studies that clearly reported

0 aerosol-generating procedures (pinteraction=0·048; figure 5). 0 1 2 3 Supportive evidence for this interaction was also seen in Distance (m) within-study comparisons (eg, N95 had a stronger Figure 3: Change in relative risk with increasing distance and absolute risk with increasing distance protective association compared with surgical masks or Meta-regression of change in relative risk with increasing distance from an infected individual (A). Absolute risk of 12–16-layer cotton masks); both N95 and surgical masks transmission from an individual infected with SARS-CoV-2, SARS-CoV, or MERS-CoV with varying baseline risk and also had a stronger association with protection versus increasing distance (B). SARS-CoV-2=severe acute respiratory syndrome coronavirus 2. SARS-CoV=severe acute 38,39,51,53,54,61,66,67,75 respiratory syndrome coronavirus. MERS-CoV=Middle East respiratory syndrome coronavirus. single-layer masks. We did a sensitivity analysis to test the robustness of Across 29 unadjusted and nine adjusted our findings and to integrate all available information studies,35–37,39,40,43,44,46,47,50–54,56,57,59–66,68,69,71,73,76 a strong association on face mask treatment effects for protection from was found of proximity of the exposed individual with COVID-19. We reconsidered our findings using ran­ the risk of infection (unadjusted n=10 736, RR 0·30, dom-effects Bayesian meta-analysis. Although non- 95% CI 0·20 to 0·44; adjusted n=7782, aOR 0·18, 95% CI informative priors showed similar results to frequentist 0·09 to 0·38; absolute risk [AR] 12·8% with shorter approaches (aOR 0·16, 95% CrI 0·04–0·40), even using distance vs 2·6% with further distance, risk difference­­ informative priors from the most recent meta-analysis [RD] –10·2%, 95% CI –11·5 to –7·5; moderate certainty; on the effectiveness of masks versus no masks to figure 2; table 2; appendix p 16). Although there were prevent influenza-like illness (RR 0·93, 95% CI six studies on COVID-19, the association was seen 0·83–1·05)31 yielded a significant association with

irrespective of causative virus (pinteraction=0·49), health-care protection from COVID-19 (aOR 0·40, 95% CrI

setting versus non-health-care setting (pinteraction=0·14), 0·16–0·97; posterior probability for RR <1, 98%).

and by type of face mask (pinteraction=0·95; appendix pp 17, 19). Minimally informing (25% influence with or without However, different studies used different distances for four-fold smaller mean effect size) the most recent and the intervention. By meta-regression, the strength of rigorous meta-analysis of the effectiveness of N95

8 www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 Articles

Country Respirator Infection Events, Events, no RR (95% CI) % weight (0=no) face mask face mask (random) (n/N) (n/N)

Health-care setting Scales et al (2003)66 Canada 0 SARS 3/16 4/15 0·70 (0·19–2·63) 3·2 Liu et al (2009)51 China 0 SARS 8/123 43/354 0·54 (0·26–1·11) 6·7 Pei et al (2006)61 China 0 SARS 11/98 61/115 0·21 (0·12–0·38) 7·9 Yin et al (2004)75 China 0 SARS 46/202 31/55 0·40 (0·29–0·57) 10·3 Park et al (2016)59 South Korea 0 MERS 3/24 2/4 0·25 (0·06–1·06) 2·8 Kim et al (2016)48 South Korea 0 MERS 0/7 1/2 0·13 (0·01–2·30) 0·8 Heinzerling et al (2020)44 USA 0 COVID-19 0/31 3/6 0·03 (0·002–0·54) 0·9 Nishiura et al (2005)55 Vietnam 0 SARS 8/43 17/72 0·79 (0·37–1·67) 6·5 Nishiyama et al (2008)56 Vietnam 0 SARS 17/61 14/18 0·36 (0·22–0·58) 9·0 Reynolds et al (2006)64 Vietnam 0 SARS 8/42 14/25 0·34 (0·17–0·69) 6·7 Loeb et al (2004)53 Canada 1 SARS 3/23 5/9 0·23 (0·07–0·78) 3·6 Wang et al (2020)41 China 1 COVID-19 0/278 10/215 0·04 (0·002–0·63) 0·9 Seto et al (2003)67 China 1 SARS 0/51 13/203 0·15 (0·01–2·40) 0·9 Wang et al (2020)70 China 1 COVID-19 1/1286 119/4036 0·03 (0·004–0·19) 1·7 Alraddadi et al (2016)34 Saudi Arabia 1 MERS 6/116 12/101 0·44 (0·17–1·12) 5·0 Ho et al (2004)45 Singapore 1 SARS 2/62 2/10 0·16 (0·03–1·02) 1·9 Teleman et al (2004)68 Singapore 1 SARS 3/26 33/60 0·21 (0·07–0·62) 4·2 Wilder-Smith et al (2005)72 Singapore 1 SARS 6/27 39/71 0·40 (0·19–0·84) 6·5 Ki et al (2019)47 South Korea 1 MERS 0/218 6/230 0·08 (0·005–1·43) 0·8 Kim et al (2016)49 South Korea 1 MERS 1/444 16/308 0·04 (0·01–0·33) 1·6 Hall et al (2014)43 Saudi Arabia 1 MERS 0/42 0/6 (Not calculable) 0 Ryu et al (2019)65 South Korea 1 MERS 0/24 0/10 (Not calculable) 0 Park et al (2004)58 USA 1 SARS 0/60 0/45 (Not calculable) 0 Peck et al (2004)60 USA 1 SARS 0/13 0/19 (Not calculable) 0 Burke et al (2020)37 USA 1 COVID-19 0/64 0/13 (Not calculable) 0 Ha et al (2004)42 Vietnam 1 SARS 0/61 0/1 (Not calculable) 0 Random subtotal (I2=50%) 126/3442 445/6003 0·30 (0·22–0·41) 81·9

Non-health-care setting Lau et al (2004)50 China 0 SARS 12/89 25/98 0·53 (0·28–0·99) 7·5 Wu et al (2004)74 China 0 SARS 25/146 69/229 0·57 (0·38–0·85) 9·7 Tuan et al (2007)69 Vietnam 0 SARS 0/9 7/154 1·03 (0·06–16·83) 0·9 Random subtotal (I2=0%) 37/244 101/481 0·56 (0·40–0·79) 18·1

Unadjusted estimates, overall (I2=48%) 163/3686 546/6484 0·34 (0·26–0·45) 100·0 Adjusted estimates, overall (1 COVID-19, 1 MERS, 8 SARS) aOR 0·15 (0·07–0·34) aRR 0·18 (0·08–0·38) Interaction by setting, p=0·049; adjusted for N95 and distance, p=0·11 0·1 0·5 1 2 10

Favours face mask Favours no face mask

Figure 4: Forest plot showing unadjusted estimates for the association of face mask use with viral infection causing COVID-19, SARS, or MERS SARS=severe acute respiratory syndrome. MERS=Middle East respiratory syndrome. RR=relative risk. aOR=adjusted odds ratio. aRR=adjusted relative risk. respirators versus medical masks in randomised 95% CI 0·12 to 0·39; low certainty; figure 6; table 2; trials (OR 0·76, 95% CI 0·54–1·06)13 with the effect- appendix pp 16–17). modification seen in this meta-analysis on COVID-19 Across 24 studies in health-care and non-health-care (ratio of aORs 0·14, 95% CI 0·02–1·05) continued to settings during the current pandemic of COVID-19, support a stronger association of protection from previous epidemics of SARS and MERS, or in general COVID-19, SARS, or MERS with N95 or similar respi­ use, looking at contextual factors to consider in rators versus other face masks (posterior probability­ for recom­mendations, most stakeholders found physical RR <1, 100% and 95%, respectively). distancing and use of face masks and eye protection In 13 unadjusted studies and two adjusted acceptable, feasible, and reassuring (appendix pp 20–22). studies,34,37-39,47,49,51,54,58,60,61,65,75 eye protection was associated However, challenges included frequent discomfort, with lower risk of infection (unadjusted n=3713, high resource use linked with potentially decreased RR 0·34, 95% CI 0·22 to 0·52; AR 5·5% with eye equity, less clear communi­cation, and perceived protection vs 16·0% with no eye protection, RD –10·6%, reduced empathy of care providers by those they were 95% CI –12·5 to –7·7; adjusted n=701, aOR 0·22, caring for. www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 9 Articles

Country Virus Setting aOR (95% CI) % weight (random)

N95 respirator or similar vs no face mask Seto et al (2003)67 China SARS Health care 0·08 (0·02–0·34) 9·0 Ma et al* (2004)54 China SARS Health care 0·01 (0·003–0·06) 8·9 Wang et al (2020)41 China COVID-19 Health care 0·002 (0·000–0·02) 6·2 Alraddadi et al* (2016)34 Saudi Arabia MERS Health care 0·41 (0·13–1·26) 10·4 Random subtotal (I2=87%) 0·04 (0·004–0·30) 34·5

Surgical face mask or similar (eg, 12–16-layer cotton) vs no face mask Wu et al (2004)74 China SARS Non-health care 0·30 (0·12–0·73) 11·2 Lau et al (2004)50 China SARS Non-health care 0·32 (0·17–0·61) 12·0 Yin et al (2004)75 China SARS Health care 0·78 (0·61–1·00) 12·8 Liu et al* (2009)51 China SARS Health care 0·22 (0·08–0·62) 10·8 Nishiura et al (2005)55 Vietnam SARS Health care 0·29 (0·11–0·75) 11·0 Nishiyama et al (2008)56 Vietnam SARS Health care 0·08 (0·01–0·50) 7·7 Random subtotal (I2=76%) 0·33 (0·17–0·61) 65·5

Random overall (I2=88%) 0·15 (0·07–0·34) 100·0 Bayesian overall (Jefferson31 seasonal viruses) 0·40 (0·16–0·97)

Interaction p=0·090; adjusted for setting, p=0·17; adjusted for AGP, p=0·048

10·5 10· 210

Favours face mask Favours no face mask

Figure 5: Forest plot showing adjusted estimates for the association of face mask use with viral infection causing COVID-19, SARS, or MERS SARS=severe acute respiratory syndrome. MERS=Middle East respiratory syndrome. RR=relative risk. aOR=adjusted odds ratio. AGP=aerosol-generating procedures. *Studies clearly reporting AGP.

Discussion imprecision in treatment effect estimates. In between- The findings of this systematic review of 172 studies study and within-study comparisons, we noted a larger (44 comparative studies; n=25 697 patients) on COVID-19, effect of N95 or similar respirators compared with other SARS, and MERS provide the best available evidence masks. This finding is inconsistent with conclusions of a that current policies of at least 1 m physical distancing review of four randomised trials,13 in which low certainty are associated with a large reduction in infection, and of evidence for no larger effect was suggested. However, in distances of 2 m might be more effective. These data also that review, the CIs were wide so a meaningful protective suggest that wearing face masks protects people (both effect could not be excluded. We harmonised these health-care workers and the general public) against findings with Bayesian approaches, using indirect data infection by these coronaviruses, and that eye protection from randomised trials to inform posterior estimates. could confer additional benefit. However, none of these Despite this step, our findings continued to support the interventions afforded complete protection from infection, ideas not only that masks in general are associated with a and their optimum role might need risk assessment and large reduction in risk of infection from SARS-CoV-2, several contextual considerations. No randomised trials SARS-CoV, and MERS-CoV but also that N95 or similar were identified for these interventions in COVID-19, respirators might be associated with a larger degree of SARS, or MERS. protec­tion from viral infection than disposable medical Previous reviews are limited in that they either have not masks or reusable multilayer (12–16-layer) cotton masks. provided any evidence from COVID-19 or did not use Nevertheless, in view of the limitations of these data, we direct evidence from other related emerging epidemic did not rate the certainty of effect as high.21 Our findings betacoronaviruses (eg, SARS and MERS) to inform the accord with those of a cluster randomised trial showing a effects of interventions to curtail the current COVID-19 potential benefit of continuous N95 respirator use over pandemic.13,19,31,78 Previous data from randomised trials are medical masks against seasonal viral infections.79 Further mainly for common respiratory viruses such as seasonal high-quality research, including randomised trials of influenza, with a systematic review concluding low the optimum physical distance and the effectiveness of certainty of evidence for extrapolating these findings to different types of masks in the general population and COVID-19.13 Further, previous syntheses of available for health-care workers’ protection, is urgently needed. randomised control­led trials have not accounted for Two trials are registered to better in­form the optimum use cluster effects in analyses, leading to substantial of face masks for COVID-19 (NCT04296643 [n=576] and

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Country Respirator Events, eye Events, no RR (95% CI)% weight (0=no) protection eye protection (random) (n/N) (n/N)

MERS Alraddadi et al (2016)34 Saudi Arabia 1 1/47 17/165 0·21 (0·03–1·51) 4·0 Ki et al (2019)47 South Korea 1 0/9 6/64 0·50 (0·03–8·21) 2·2 Kim et al (2016)49 South Korea 1 0/443 2/294 0·13 (0·01–2·76) 1·8 Ryu et al (2019)65 South Korea 1 0/24 0/10 (Not calculable) 0 Random subtotal (I2=0%) 1/523 25/533 0·24 (0·06–0·99) 8·0

SARS Chen et al (2009)39 China 0 1/45 90/703 0·17 (0·02–1·22) 4·2 Liu et al (2009)51 China 0 17/221 34/256 0·58 (0·33–1·01) 21·2 Pei et al (2006)61 China 0 24/120 123/323 0·53 (0·36–0·77) 26·0 Yin et al (2004)75 China 0 10/120 67/137 0·17 (0·09–0·32) 19·4 Caputo et al (2006)38 Canada 1 2/46 4/32 0·35 (0·07–1·79) 5·6 Ma et al (2004)54 China 1 7/175 40/269 0·27 (0·12–0·59) 15·6 Park et al (2004)58 USA 1 0/30 0/72 (Not calculable) 0 Peck et al (2004)60 USA 1 0/13 0/19 (Not calculable) 0 Random subtotal (I2=62%) 61/770 358/1811 0·34 (0·21–0·56) 92·0

COVID-19 Burke et al (2020)37 USA 1 0/42 0/34 (Not calculable) 0 Random subtotal 0/42 0/34 (Not calculable) 0

Random overall (I2=43%) 62/1335 383/2378 0·34 (0·22–0·52) 100·0 Adjusted estimates, overall (2 studies, Yin75 and Ma54) aOR 0·22 (0·12–0·39) aRR 0·25 (0·14–0·43) Interaction by virus, p=0·75 0·1 0·5 1 2 10

Favours eye protection Favours no eye protection

Figure 6: Forest plot showing the association of eye protection with risk of COVID-19, SARS, or MERS transmission Forest plot shows unadjusted estimates. SARS=severe acute respiratory syndrome. MERS=Middle East respiratory syndrome. RR=relative risk. aOR=adjusted odds ratio. aRR=adjusted relative risk.

NCT04337541 [n=6000]). Until such data are available, our associated with a large reduction in infection, and that findings represent the current best estimates to inform distances of 2 m might be more effective, as implemented face mask use to reduce infection from COVID-19. We in some countries. We also provide estimates for 3 m. recognise that there are strong, perhaps opposing, The main benefit of physical distancing measures is to sentiments about policy making during outbreaks. In one prevent onward transmission and, thereby, reduce the viewpoint, the 2007 SARS Commission report stated: adverse outcomes of SARS-CoV-2 infection. Hence, the “...recognize, as an aspect of health worker safety, the results of our current review support the implementation precautionary principle that reasonable action to reduce of a policy of physical distancing of at least 1 m and, if risk, such as the use of a fitted N95 respirator, need not feasible, 2 m or more. Our findings also provide robust await scientific certainty”.80 estimates to inform models and contact tracing used to plan and strategise for pandemic response efforts at “...if we do not learn from SARS and we do not make the multiple levels. government fix the problems that remain, we will pay a The use of face masks was protective for both health- 81 terrible price in the next pandemic”. care workers and people in the community exposed to infection, with both the frequentist and Bayesian A counter viewpoint is that the scientific uncertainty analyses lending support to face mask use irrespective and contextual considerations require a more nuanced of setting. Our unadjusted analyses might, at first approach. Although challenging, policy makers must impression, suggest use of face masks in the community carefully consider these two viewpoints along with our setting to be less effective than in the health-care setting, findings. but after accounting for differential N95 respirator use We found evidence of moderate certainty that current between health-care and non-health-care settings, we did policies of at least 1 m physical distancing are probably not detect any striking differences in effectiveness of www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 11 Articles

face mask use between settings. The credibility of effect- quantitative estimates of effects, although the qualitative modification across settings was, therefore, low. Wearing effect and direction is probably of high certainty. Many face masks was also acceptable and feasible. Policy studies did not provide information on precise distances, makers at all levels should, therefore, strive to address and direct contact was equated to 0 m distance; none of the equity implications for groups with currently limited eligible studies quanti­tatively evaluated whether distances access to face masks and eye protection. One concern is of more than 2 m were more effective, although our meta- that face mask use en masse could divert supplies from regression provides potential predictions­ for estimates of people at highest risk for infection.10 Health-care workers risk. Few studies assessed the effect of interventions in are increasingly being asked to ration and reuse PPE,82,83 non-health-care settings, and they primarily evaluated leading to calls for government-directed repurposing of mask use in households or contacts of cases, although manufacturing capacity to overcome mask shortages84 beneficial associations were seen across settings. and finding solutions for mask use by the general Furthermore, most evidence was from studies that public.84 In this respect, some of the masks studied in reported on SARS and MERS (n=6674 patients with our review were reusable 12–16-layer cotton or gauze COVID-19, of 25 697 total), but data from these previous masks.51,54,61,75 At the moment, although there is consensus epidemics provide the most direct information for that SARS-CoV-2 mainly spreads through large droplets COVID-19 currently. We did not specifically assess the and contact, debate continues about the role of effect of duration of exposure on risk for transmission, aerosol,2–8,85,86 but our meta-analysis provides evidence although whether or not this variable was judged a risk (albeit of low certainty) that respirators might have a factor considerably varied across studies, from any stronger protective effect than surgical masks. Biological duration to a minimum of 1 h. Because of inconsistent plausi­bility would be supported by data for aerosolised reporting, information is limited about whether aerosol- SARS-CoV-25–8 and preclinical data showing seasonal generating procedures were in place in studies using coronavirus RNA detection in fine aerosols during tidal respirators, and whether masks worn by infected patients breathing,87 albeit, RNA detection does not necessarily might alter the effectiveness of each intervention, although imply replication and infection-competent virus. the stronger association with N95 or similar respirators Nevertheless, our findings suggest it plausible that over other masks persisted when adjusting for studies even in the absence of aerosolisation, respirators might reporting aerosol-generating medical procedures. These be simply more effective than masks at preventing factors might account for some of the residual statistical infection. At present, there is no data to support viable heterogeneity seen for some outcomes, albeit I² is com­ virus in the air outside of aerosol generating procedures monly inflated in meta-analyses of observational data,21,22 from available hospital studies. Other factors such as and nevertheless the effects seen were large and probably super-spreading events, the subtype of health-care set­ clinically important in all adjusted studies. ting (eg, emergency room, intensive care unit, medical Our comprehensive systematic review provides the wards, dialysis centre), if aerosolising proce­dures are best available information on three simple and com­ done, and environmental factors such as ventilation, mon interventions to combat the immediate threat of might all affect the degree of protection afforded by COVID-19, while new evidence on pharmacological treat­ personal protection strategies, but we did not identify ments, vaccines,­ and other personal protective strategies is robust data to inform these aspects. being generated. Physical distancing of at least 1 m is Strengths of our review include adherence to full strongly associated with protection, but distances of up to systematic review methods, which included artificial intel­ 2 m might be more effective. Although direct evidence is ligence-supported dual screening of titles and abstracts, limited, the optimum use of face masks, in particular N95 full-text evaluation, assessment of risk of bias, and no or similar respirators in health-care settings and 12–16-layer limitation by language. We included patients infected cotton or surgical masks in the community, could depend with SARS-CoV-2, SARS-CoV, or MERS-CoV and searched on contextual factors; action is needed at all levels to relevant data up to May 3, 2020. We followed the GRADE address the paucity of better evidence. Eye protection approach16 to rate the certainty of evidence. Finally, we might provide additional benefits. Globally collaborative identified and appraise a large body of published work and well conducted studies, including randomised trials, from China, from which much evidence emerged before of different personal protective strategies are needed the pandemic spread to other global regions. regardless of the challenges, but this systematic appraisal The primary limitation of our study is that all studies of currently best available evidence could be considered to were non-randomised, not always fully adjusted, and inform interim guidance. might suffer from recall and measurement bias (eg, direct Contributors contact in some studies might not be measuring near DKC, EAA, SD, KS, SY, and HJS designed the study. SY, SD, KS, distance). However, unadjusted, adjusted, frequentist, and and HJS coordinated the study. SY and LH designed and ran the literature search. All authors acquired data, screened records, extracted Bayesian meta-analyses all supported the main findings, data, and assessed risk of bias. DKC did statistical analyses. DKC and and large or very large effects were recorded. Nevertheless, HJS wrote the report. All authors provided critical conceptual input, we are cautious not to be overly certain in the precise analysed and interpreted data, and critically revised the report.

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COVID-19 Systematic Urgent Review Group Effort (SURGE) study authors 8 Ong SWX, Tan YK, Chia PY, et al. Air, surface environmental, Argentina—German Hospital of Buenos Aires (Ariel Izcovich); and personal protective equipment contamination by severe acute Canada—Cochrane Consumer Executive (Maureen Smith); McMaster respiratory syndrome coronavirus 2 (SARS-CoV-2) from a University (Mark Loeb, Anisa Hajizadeh, Carlos A Cuello-Garcia, symptomatic patient. JAMA 2020; 323: 1610–12. Gian Paolo Morgano, Leila Harrison, Tejan Baldeh, Karla Solo, 9 Qualls N, Levitt A, Kanade N, et al. Community mitigation Tamara Lotfi, Antonio Bognanni, Rosa Stalteri, Thomas Piggott, guidelines to prevent pandemic influenza: United States, 2017. Yuan Zhang, Stephanie Duda, Derek K Chu, Holger J Schünemann); MMWR Recomm Rep 2017; 66: 1–34. Southlake Regional Health Centre (Jeffrey Chan); University of British 10 Feng S, Shen C, Xia N, Song W, Fan M, Cowling BJ. Rational use of Columbia (David James Harris); Chile—Pontificia Universidad Católica face masks in the COVID-19 pandemic. Lancet Respir Med 2020; 8: 434–36. de Chile (Ignacio Neumann); China—Beijing University of Chinese 11 MacIntyre R, Chughtai A, Tham CD, Seale H. COVID-19: Medicine, Dongzhimen Hospital (Guang Chen); Guangzhou University should cloth masks be used by healthcare workers as a last resort? of Chinese Medicine, The Fourth Clinical Medical College (Chen Chen); April 9, 2020. https://blogs.bmj.com/bmj/2020/04/09/covid-19- China Academy of Chinese Medical Sciences (Hong Zhao); Germany— should-cloth-masks-be-used-by-healthcare-workers-as-a-last-resort/ Finn Schünemann; Italy—Azienda USL–IRCCS di Reggio Emilia (accessed May 12, 2020). (Paolo Giorgi Rossi); Universita Vita-Salute San Raffaele, Milan, Italy 12 Loeb M, Dafoe N, Mahony J, et al. Surgical mask vs N95 respirator (Giovanna Elsa Ute Muti Schünemann); Lebanon—American University for preventing influenza among health care workers: a randomized of Beirut (Layal Hneiny, Amena El-Harakeh, Fatimah Chamseddine, trial. JAMA 2009; 302: 1865–71. Joanne Khabsa, Nesrine Rizk, Rayane El-Khoury, Zahra Saad, 13 Bartoszko JJ, Farooqi MAM, Alhazzani W, Loeb M. Medical masks Sally Yaacoub, Elie A Akl); Rafik Hariri University Hospital vs N95 respirators for preventing COVID-19 in healthcare workers: (Pierre AbiHanna); Poland—Evidence Prime, Krakow (Anna Bak, a systematic review and meta-analysis of randomized trials. Ewa Borowiack); UK—The London School of Hygiene & Tropical Influenza Other Respir Viruses 2020; published online April 4. Medicine (Marge Reinap); University of Hull (Assem Khamis). DOI:10.1111/irv.12745. 14 Schünemann HJ, Moja L. Reviews: rapid! Rapid! Rapid! . . . and Declaration of interests systematic. Syst Rev 2015; 4: 4. ML is an investigator of an ongoing clinical trial on medical masks 15 Cochrane Training. Cochrane handbook for systematic reviews of versus N95 respirators for COVID-19 (NCT04296643). All other authors interventions, version 6. 2019. https://training.cochrane.org/ declare no competing interests. handbook/current (accessed May 12, 2020). Acknowledgments 16 Guyatt GH, Oxman AD, Vist GE, et al. GRADE: an emerging This systematic review was commissioned and in part paid for by WHO. consensus on rating quality of evidence and strength of The authors alone are responsible for the views expressed in this article recommendations. BMJ 2008; 336: 924–26. and they do not necessarily represent the decisions, policy, or views of 17 Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting WHO. 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74 Wu J, Xu F, Zhou W, et al. Risk factors for SARS among persons 81 Webster P. Ontario issues final SARS Commission report. without known contact with SARS patients, Beijing, China. Lancet 2007; 369: 264. Emerg Infect Dis 2004; 10: 210–16. 82 Rimmer A. COVID-19: experts question guidance to reuse PPE. 75 Yin WW, Gao LD, Lin WS, et al. Effectiveness of personal BMJ 2020; 369: m1577. protective measures in prevention of nosocomial transmission of 83 Mackenzie D. Reuse of N95 masks. Engineering 2020; published severe acute respiratory syndrome. online April 13. DOI:10.1016/j.eng.2020.04.003. Zhonghua Liu Xing Bing Xue Za Zhi 2004; 25: 18–22. 84 Greenhalgh T, Schmid MB, Czypionka T, Bassler D, Gruer L. 76 Yu ITS, Wong TW, Chiu YL, Lee N, Li Y. Temporal-spatial analysis Face masks for the public during the covid-19 crisis. BMJ 2020; of severe acute respiratory syndrome among hospital inpatients. 369: m1435. Clin Infect Dis 2005; 40: 1237–43. 85 Bahl P, Doolan C, de Silva C, Chughtai AA, Bourouiba L, 77 Yu IT, Xie ZH, Tsoi KK, et al. Why did outbreaks of severe acute MacIntyre CR. Airborne or droplet precautions for health workers respiratory syndrome occur in some hospital wards but not in treating coronavirus disease 2019? J Infect Dis 2020; published others? Clin Infect Dis 2007; 44: 1017–25. online April 16. DOI:10.1093/infdis/jiaa189. 78 Verbeek JH, Rajamaki B, Ijaz S, et al. Personal protective 86 Schünemann HJ, Khabsa J, Solo K, et al. Ventilation techniques equipment for preventing highly infectious diseases due to and risk for transmission of coronavirus disease, including exposure to contaminated body fluids in healthcare staff. COVID-19: a living systematic review of multiple streams of Cochrane Database Syst Rev 2019; 7: CD011621. evidence. Ann Intern Med 2020; published online May 22. 79 MacIntyre CR, Wang Q, Seale H, et al. A randomized clinical trial DOI:10.7326/M20-2306. of three options for N95 respirators and medical masks in health 87 Leung NHL, Chu DKW, Shiu EYC, et al. Respiratory virus workers. Am J Respir Crit Care Med 2013; 187: 960–66. shedding in exhaled breath and efficacy of face masks. 80 Campbell A. Chapter eight: it’s not about the mask: SARS Nat Med 2020; 26: 676–80. Commission final report, volume 3. December, 2006. http://www. archives.gov.on.ca/en/e_records/sars/report/v3-pdf/Vol3Chp8.pdf (accessed May 12, 2020).

www.thelancet.com Published online June 1, 2020 https://doi.org/10.1016/S0140-6736(20)31142-9 15 Morbidity and Mortality Weekly Report

Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents of a Long-Term Care Skilled Nursing Facility — King County, Washington, March 2020

Anne Kimball, MD1,2; Kelly M. Hatfield, MSPH1; Melissa Arons, MSc1,2; Allison James, PhD1,2; Joanne Taylor, PhD1,2; Kevin Spicer, MD1; Ana C. Bardossy, MD1,2; Lisa P. Oakley, PhD1,2; Sukarma Tanwar, MMed1,2; Zeshan Chisty, MPH1; Jeneita M. Bell, MD1; Mark Methner, PhD1; Josh Harney, MS1; Jesica R. Jacobs, PhD1,3; Christina M. Carlson, PhD1,3; Heather P. McLaughlin, PhD1; Nimalie Stone, MD1; Shauna Clark4; Claire Brostrom-Smith, MSN4; Libby C. Page, MPH4; Meagan Kay, DVM4; James Lewis, MD4; Denny Russell5; Brian Hiatt5; Jessica Gant, MS5; Jeffrey S. Duchin, MD4; Thomas A. Clark, MD1; Margaret A. Honein, PhD1; Sujan C. Reddy, MD1; John A. Jernigan, MD1; Public Health – Seattle & King County; CDC COVID-19 Investigation Team

On March 27, 2020, this report was posted as an MMWR Early Immediately upon identification of the index case in Release on the MMWR website (https://www.cdc.gov/mmwr). facility A on March 1, nursing and administrative leader- Older adults are susceptible to severe coronavirus disease ship instituted visitor restrictions, twice-daily assessments of 2019 (COVID-19) outcomes as a consequence of their age and, COVID-19 signs and symptoms among residents, and fever in some cases, underlying health conditions (1). A COVID-19 screening of all health care personnel at the start of each shift. outbreak in a long-term care skilled nursing facility (SNF) On March 6, Public Health – Seattle and King County, in in King County, Washington that was first identified on collaboration with CDC, recommended infection prevention February 28, 2020, highlighted the potential for rapid spread and control measures, including isolation of all symptomatic among residents of these types of facilities (2). On March 1, residents and use of gowns, gloves, eye protection, facemasks, a health care provider at a second long-term care skilled nurs- and hand hygiene for health care personnel entering symptom- ing facility (facility A) in King County, Washington, had a atic residents’ rooms. A data collection tool was developed to positive test result for SARS-CoV-2, the novel coronavirus ascertain symptom status and underlying medical conditions that causes COVID-19, after working while symptomatic for all residents. on February 26 and 28. By March 6, seven residents of this On March 13, the symptom assessment tool was completed second facility were symptomatic and had positive test results by facility A’s nursing staff members by reviewing screening for SARS-CoV-2. On March 13, CDC performed symptom records of residents for the preceding 14 days and by clinician assessments and SARS-CoV-2 testing for 76 (93%) of the 82 interview of residents at the time of specimen collection. For facility A residents to evaluate the utility of symptom screening residents with significant cognitive impairment, symptoms for identification of COVID-19 in SNF residents. Residents were obtained solely from screening records. A follow-up were categorized as asymptomatic or symptomatic at the time symptom assessment was completed 7 days later by nursing of testing, based on the absence or presence of fever, cough, staff members. Nasopharyngeal swabs were obtained from all shortness of breath, or other symptoms on the day of testing 76 residents who agreed to testing and were present in the or during the preceding 14 days. Among 23 (30%) residents facility at the time; oropharyngeal swabs were also collected with positive test results, 10 (43%) had symptoms on the date from most residents, depending upon their cooperation. of testing, and 13 (57%) were asymptomatic. Seven days after The Washington State Public Health Laboratory performed testing, 10 of these 13 previously asymptomatic residents had one-step real-time RT-PCR assay on all specimens using the developed symptoms and were recategorized as presymptom- SARS-CoV-2 CDC assay protocol, which determines the atic at the time of testing. The reverse transcription–polymerase presence of the virus through identification of two genetic chain reaction (RT-PCR) testing cycle threshold (Ct) values markers, the N1 and N2 nucleocapsid protein gene regions indicated large quantities of viral RNA in asymptomatic, (5). The Ct, the cycle number during RT-PCR testing when presymptomatic, and symptomatic residents, suggesting the detection of viral amplicons occurs, is inversely correlated with potential for transmission regardless of symptoms. Symptom- the amount of RNA present; a Ct value <40 cycles denotes a based screening in SNFs could fail to identify approximately positive result for SARS-CoV-2, with a lower value indicating half of residents with COVID-19. Long-term care facilities a larger amount of viral RNA. should take proactive steps to prevent introduction of SARS- Residents were assessed for stable chronic symptoms (e.g., CoV-2 (3). Once a confirmed case is identified in an SNF, all chronic, unchanged cough) as well as typical and atypical signs residents should be placed on isolation precautions if possible and symptoms of COVID-19. Typical COVID-19 signs and (3), with considerations for extended use or reuse of personal symptoms include fever, cough, and shortness of breath (3); protective equipment (PPE) as needed (4). potential atypical symptoms assessed included sore throat,

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One week after testing, the 13 residents who had positive test Summary results and were asymptomatic on the date of testing were reas- What is already known about this topic? sessed; 10 had developed symptoms and were recategorized as pre- Once SARS-CoV-2 is introduced in a long-term care skilled symptomatic at the time of testing (Table 2). The most common nursing facility (SNF), rapid transmission can occur. signs and symptoms that developed were fever (eight residents), What is added by this report? malaise (six), and cough (five). The mean interval from testing Following identification of a case of coronavirus disease 2019 to symptom onset in the presymptomatic residents was 3 days. (COVID-19) in a health care worker, 76 of 82 residents of an SNF Three residents with positive test results remained asymptomatic. were tested for SARS-CoV-2; 23 (30.3%) had positive test results, approximately half of whom were asymptomatic or presymp- Real-time RT-PCR Ct values for both genetic markers tomatic on the day of testing. among residents with positive test results for SARS-CoV-2 What are the implications for public health practice? ranged from 18.6 to 29.2 (symptomatic [typical symptoms]), Symptom-based screening of SNF residents might fail to 24.3 to 26.3 (symptomatic [atypical symptoms only]), 15.3 identify all SARS-CoV-2 infections. Asymptomatic and to 37.9 (presymptomatic), and 21.9 to 31.0 (asymptomatic) presymptomatic SNF residents might contribute to SARS-CoV-2 (Figure). There were no significant differences between the transmission. Once a facility has confirmed a COVID-19 case, all mean Ct values in the four symptom status groups (p = 0.3). residents should be cared for using CDC-recommended personal protective equipment (PPE), with considerations for Discussion extended use or reuse of PPE as needed. Sixteen days after introduction of SARS-CoV-2 into facility A, facility-wide testing identified a 30.3% prevalence of chills, increased confusion, rhinorrhea or nasal congestion, infection among residents, indicating very rapid spread, despite myalgia, dizziness, malaise, headache, nausea, and diarrhea. early adoption of infection prevention and control measures. Residents were categorized as asymptomatic (no symptoms or Approximately half of all residents with positive test results only stable chronic symptoms) or symptomatic (at least one did not have any symptoms at the time of testing, suggesting new or worsened typical or atypical symptom of COVID-19) that transmission from asymptomatic and presymptomatic on the day of testing or during the preceding 14 days. Residents residents, who were not recognized as having SARS-CoV-2 with positive test results and were asymptomatic at time of infection and therefore not isolated, might have contributed testing were reevaluated 1 week later to ascertain whether any to further spread. Similarly, studies have shown that influenza symptoms had developed in the interim. Those who devel- in the elderly, including those living in SNFs, often manifests oped new symptoms were recategorized as presymptomatic. as few or atypical symptoms, delaying diagnosis and contrib- Ct values were compared for the recategorized symptom uting to transmission (6–8). These findings have important groups using one-way analysis of variance (ANOVA) for all implications for infection control. Current interventions for residents with positive test results for SARS-CoV-2. Analyses preventing SARS-CoV-2 transmission primarily rely on pres- were conducted using SAS statistical software (version 9.4; ence of signs and symptoms to identify and isolate residents SAS Institute). or patients who might have COVID-19. If asymptomatic or On March 13, among the 82 residents in facility A; 76 presymptomatic residents play an important role in transmis- (92.7%) underwent symptom assessment and testing; three sion in this population at high risk, additional prevention (3.7%) refused testing, two (2.4%) who had COVID-19 measures merit consideration, including using testing to guide symptoms were transferred to a hospital before testing, and cohorting strategies or using transmission-based precautions one (1.2%) was unavailable. Among the 76 tested residents, for all residents of a facility after introduction of SARS-CoV-2. 23 (30.3%) had positive test results. Limitations in availability of tests might necessitate taking the Demographic characteristics were similar among the 53 latter approach at this time. (69.7%) residents with negative test results and the 23 (30.3%) Although these findings do not quantify the relative con- with positive test results (Table 1). Among the 23 residents with tributions of asymptomatic or presymptomatic residents to positive test results, 10 (43.5%) were symptomatic, and 13 SARS-CoV-2 transmission in facility A, they suggest that these (56.5%) were asymptomatic. Eight symptomatic residents had residents have the potential for substantial viral shedding. typical COVID-19 symptoms, and two had only atypical symp- Low Ct values, which indicate large quantities of viral RNA, toms; the most common atypical symptoms reported were malaise were identified for most of these residents, and there was no (four residents) and nausea (three). Thirteen (24.5%) residents statistically significant difference in distribution of Ct values who had negative test results also reported typical and atypical among the symptom status groups. Similar Ct values were COVID-19 symptoms during the 14 days preceding testing. reported in asymptomatic adults in China who were known to

378 MMWR / April 3, 2020 / Vol. 69 / No. 13 US Department of Health and Human Services/Centers for Disease Control and Prevention Morbidity and Mortality Weekly Report

TABLE 1. Demographics and reported symptoms for residents of a long-term care skilled nursing facility at time of testing* (N = 76), by SARS-CoV-2 test results — facility A, King County, Washington, March 2020 Initial SARS-CoV-2 test results Characteristic Negative, no. (%) Positive, no. (%) Overall 53 (100) 23 (100) Women 32 (60.4) 16 (69.6) Age, mean (SD) 75.1 (10.9) 80.7 (8.4) Current smoker† 7 (13.2) 1 (4.4) Long-term admission type to facility A 35 (66.0) 15 (65.2) Length of stay in facility A before test date, days, median (IQR) 94 (40–455) 70 (21–504) Symptoms in last 14 days Symptomatic 13 (24.5) 10 (43.5) At least one typical COVID-19 symptom§ 9 (17.0) 8 (34.8) Only atypical COVID-19 symptoms¶ 4 (7.5) 2 (8.7) Asymptomatic 40 (75.5) 13 (56.5) No symptoms 32 (60.4) 8 (34.8) Only stable, chronic symptoms 8 (15.1) 5 (21.7) Specific signs and symptoms reported as new or worse in last 14 days Typical symptoms Fever 3 (5.7) 1 (4.3) Cough 6 (11.3) 7 (30.4) Shortness of breath 0 (0) 1 (4.4) Atypical symptoms Malaise 1 (1.9) 4 (17.4) Nausea 0 (0) 3 (13.0) Sore throat 2 (3.8) 2 (8.7) Confusion 2 (3.8) 1 (4.4) Dizziness 1 (1.9) 1 (4.4) Diarrhea 3 (5.7) 1 (4.4) Rhinorrhea/Congestion 1 (1.9) 0 (0) Myalgia 0 (0) 0 (0) Headache 0 (0) 0 (0) Chills 0 (0) 0 (0) Any preexisting medical condition listed 53 (100) 22 (95.7) Specific conditions** Chronic lung disease 16 (30.2) 10 (43.5) Diabetes 20 (37.7) 9 (39.1) Cardiovascular disease 36 (67.9) 20 (87.0) Cerebrovascular accident 19 (35.9) 8 (34.8) Renal disease 18 (34.0) 9 (39.1) Received hemodialysis 2 (3.8) 2 (8.7) Cognitive Impairment 28 (52.8) 13 (56.5) Obesity 11 (20.8) 6 (26.1) Abbreviations: COVID-19 = coronavirus disease 2019; IQR = interquartile range, SD = standard deviation. * Testing performed on March 13, 2020. † Unknown for one resident with negative test results. § Typical symptoms include fever, cough, and shortness of breath. ¶ Atypical symptoms include chills, malaise, sore throat, increased confusion, rhinorrhea or nasal congestion, myalgia, dizziness, headache, nausea, and diarrhea. ** Residents might have multiple conditions. transmit SARS-CoV-2 (9). Studies to determine the presence of long-term care facilities might have limited experience with of viable virus from these specimens are currently under way. proper use of PPE. Symptom ascertainment and room isolation SNFs have additional infection prevention and control chal- can be exceptionally challenging in elderly residents with neuro- lenges compared with those of assisted living or independent logic conditions, including dementia. In addition, symptoms of living long-term care facilities. For example, SNF residents might COVID-19 are common and might have multiple etiologies in be in shared rooms rather than individual apartments, and there this population; 24.5% of facility A residents with negative test is often prolonged and close contact between residents and results for SARS-CoV-2 reported typical or atypical symptoms. health care providers related to the residents’ medical conditions The findings in this report are subject to at least two limita- and cognitive function. The index patient in this outbreak was tions. First, accurate symptom ascertainment in persons with a health care provider, which might have contributed to rapid cognitive impairment and other disabilities is challenging; spread in the facility. In addition, health care personnel in all types however, this limitation is estimated to be representative of

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TABLE 2. Follow-up symptom assessment 1 week after testing for Acknowledgments SARS-CoV-2 among 13 residents of a long-term care skilled nursing facility who were asymptomatic on March 13, 2020 (date of testing) Nursing and administrative leaders at facility A; Washington State and had positive test results — facility A, King County, Washington, Public Health Laboratory’s SARS-CoV-2 testing team. March 2020 Public Health – Seattle & King County Symptom status 1 week after testing No. (%) Asymptomatic 3 (23.1) Atar Baer, Public Health – Seattle & King County; Leslie M. Developed new symptoms 10 (76.7) Barnard, Public Health – Seattle & King County; Eileen Benoliel, Fever 8 (61.5) Public Health – Seattle & King County; Meaghan S. Fagalde, Public Malaise 6 (46.1) Cough 5 (38.4) Health – Seattle & King County; Jessica Ferro, Public Health – Seattle Confusion 4 (30.8) & King County; Hal Garcia Smith, Public Health – Seattle & King Rhinorrhea/Congestion 4 (30.8) County; Elysia Gonzales, Public Health – Seattle & King County; Shortness of breath 3 (23.1) Noel Hatley, Public Health – Seattle & King County; Grace Hatt, Diarrhea 3 (23.1) Sore throat 1 (7.7) Public Health – Seattle & King County; Michaela Hope, Public Nausea 1 (7.7) Health – Seattle & King County; Melinda Huntington-Frazier, Public Dizziness 1 (7.7) Health – Seattle & King County; Vance Kawakami, Public Health – Seattle & King County; Jennifer L. Lenahan, Public Health – Seattle symptom data collected in most SNFs, and thus, these find- & King County; Margaret D. Lukoff, Public Health – Seattle & King County; Emily B. Maier, Public Health – Seattle & King County; ings might be generalizable. Second, because this analysis was Shelly McKeirnan, Public Health – Seattle & King County; Patricia conducted among residents of an SNF, it is not known whether Montgomery, Public Health – Seattle & King County; Jennifer L. findings apply to the general population, including younger Morgan, Public Health – Seattle & King County; Laura A. Mummert, persons, those without underlying medical conditions, or Public Health – Seattle & King County; Sargis Pogosjans, Public similarly aged populations in the general community. Health – Seattle & King County; Francis X. Riedo, Public Health – This analysis suggests that symptom screening could initially Seattle & King County; Leilani Schwarcz, Public Health – Seattle & fail to identify approximately one half of SNF residents with King County; Daniel Smith, Public Health – Seattle & King County; SARS-CoV-2 infection. Unrecognized asymptomatic and Steve Stearns, Public Health – Seattle & King County; Kaitlyn J. presymptomatic infections might contribute to transmission Sykes, Public Health – Seattle & King County; Holly Whitney, Public in these settings. During the current COVID-19 pandemic, Health – Seattle & King County. SNFs and all long-term care facilities should take proactive CDC COVID-19 Investigation Team steps to prevent introduction of SARS-CoV-2, including restricting visitors except in compassionate care situations, Hammad Ali, CDC; Michelle Banks, CDC; Arun Balajee, restricting nonessential personnel from entering the building, CDC; Eric J. Chow, CDC; Barbara Cooper, CDC; Dustin W. Currie, CDC; Jonathan Dyal, CDC; Jessica Healy, CDC; Michael asking staff members to monitor themselves for fever and other Hughes, CDC; Temet M. McMichael, CDC; Leisha Nolen, CDC; symptoms, screening all staff members at the beginning of Christine Olson, CDC; Agam K. Rao, CDC; Kristine Schmit, CDC; their shift for fever and other symptoms, and supporting staff Noah G. Schwartz, CDC; Farrell Tobolowsky, CDC; Rachael Zacks, member sick leave, including for those with mild symptoms CDC; Suzanne Zane, CDC. (3). Once a facility has a case of COVID-19, broad strategies Corresponding author: Anne Kimball, [email protected], 770-488-7100. should be implemented to prevent transmission, including 1 2 restriction of resident-to-resident interactions, universal use CDC COVID-19 Investigation Team; Epidemic Intelligence Service, CDC; 3Laboratory Leadership Service, CDC; 4Public Health – Seattle & King County; of facemasks for all health care personnel while in the facility, 5Washington State Public Health Laboratory. and if possible, use of CDC-recommended PPE for the care of All authors have completed and submitted the International all residents (i.e., gown, gloves, eye protection, N95 respirator, Committee of Medical Journal Editors form for disclosure of potential or, if not available, a face mask) (3). In settings where PPE sup- conflicts of interest. No potential conflicts of interest were disclosed. plies are limited, strategies for extended PPE use and limited reuse should be employed (4). As testing availability improves, References consideration might be given to test-based strategies for iden- 1. CDC COVID-19 Response Team. Severe outcomes among patients tifying residents with SARS-CoV-2 infection for the purpose with coronavirus disease 2019 (COVID-19)—United States, February 12–March 16, 2020. MMWR Morb Mortal Wkly Rep of cohorting, either in designated units within a facility or in 2020;69:343–6. https://dx.doi.org/10.15585/mmwr.mm6912e2 a separate facility designated for residents with COVID-19. 2. McMichael TM, Clark S, Pogosjans S, et al. COVID-19 in a long-term During the COVID-19 pandemic, collaborative efforts are care facility—King County, Washington, February 27–March 9, 2020. MMWR Morb Mortal Wkly Rep 2020;69:339–42. https://dx.doi. crucial to protecting the most vulnerable populations. org/10.15585/mmwr.mm6912e1

380 MMWR / April 3, 2020 / Vol. 69 / No. 13 US Department of Health and Human Services/Centers for Disease Control and Prevention Morbidity and Mortality Weekly Report

FIGURE. Cycle threshold (Ct) values* for residents of a long-term care skilled nursing facility with positive test results for SARS-CoV-2 by real-time reverse transcription–polymerase chain reaction on March 13, 2020 (n = 23), by symptom status†,§ at time of test — facility A, King County, Washington

Symptomatic (typical symptoms) (n = 8)

Symptomatic (atypical symptoms) (n = 2)

Presymptomatic Symptom status Symptom (n = 10)

Asymptomatic (n = 3)

10 15 20 25 30 35 40 Ct value

* Ct values are the number of cycles needed for detection of each genetic marker identified by real-time reverse transcription–polymerase chain reaction testing. A lower Ct value indicates a higher amount of viral RNA. Paired values for each resident are depicted using a different shape. Each resident has two Ct values for the two genetic markers (N1 and N2 nucleocapsid protein gene regions). † Typical symptoms include fever, cough, and shortness of breath. § Atypical symptoms include chills, malaise, sore throat, increased confusion, rhinorrhea or nasal congestion, myalgia, dizziness, headache, nausea, and diarrhea.

3. CDC. Preparing for COVID-19: long-term care facilities, nursing homes. 6. Lam PP, Coleman BL, Green K, et al. Predictors of influenza among Atlanta, GA: US Department of Health and Human Services, CDC; older adults in the emergency department. BMC Infect Dis 2016;16:615. 2020. https://www.cdc.gov/coronavirus/2019-ncov/healthcare-facilities/ https://doi.org/10.1186/s12879-016-1966-4 prevent-spread-in-long-term-care-facilities.html 7. Lansbury LE, Brown CS, Nguyen-Van-Tam JS. Influenza in long-term 4. CDC. Strategies for optimizing the supply of PPE. Atlanta, GA: US care facilities. Influenza Other Respir Viruses 2017;11:356–66. https:// Department of Health and Human Services, CDC; 2020. https://www. doi.org/10.1111/irv.12464 cdc.gov/coronavirus/2019-ncov/hcp/ppe-strategy/index.html 8. Sayers G, Igoe D, Carr M, et al. High morbidity and mortality 5. CDC. Interim guidelines for collecting, handling, and testing clinical associated with an outbreak of influenza A(H3N2) in a psycho-geriatric specimens from persons for coronavirus disease 2019 (COVID-19). facility. Epidemiol Infect 2013;141:357–65. https://doi.org/10.1017/ Atlanta, GA: US Department of Health and Human Services, CDC; S0950268812000659 2020. https://www.cdc.gov/coronavirus/2019-nCoV/lab/guidelines- 9. Zou L, Ruan F, Huang M, et al. SARS-CoV-2 viral load in upper respiratory clinical-specimens.html specimens of infected patients. N Engl J Med 2020;382:1177–9. https:// doi.org/10.1056/NEJMc2001737

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Presymptomatic Transmission of SARS-CoV-2 — Singapore, January 23–March 16, 2020

Wycliffe E. Wei, MPH1,2; Zongbin Li, MBBS1; Calvin J. Chiew, MPH1; Sarah E. Yong, MMed1; Matthias P. Toh, MMed2,3; Vernon J. Lee, PhD1,3

On April 1, 2020, this report was posted as an MMWR Early The surveillance and case detection methods employed in Release on the MMWR website (https://www.cdc.gov/mmwr). Singapore have been described (4). Briefly, all medical prac- Presymptomatic transmission of SARS-CoV-2, the virus that titioners were required by law to notify Singapore’s Ministry causes coronavirus disease 2019 (COVID-19), might pose of Health of suspected and confirmed cases of COVID-19. challenges for disease control. The first case of COVID-19 The definition of a suspected case was based on the presence in Singapore was detected on January 23, 2020, and by of respiratory symptoms and an exposure history. Suspected March 16, a total of 243 cases had been confirmed, including cases were tested, and a confirmed case was defined as a positive 157 locally acquired cases. Clinical and epidemiologic findings test for SARS-CoV-2, using laboratory-based polymerase chain of all COVID-19 cases in Singapore through March 16 were reaction or serologic assays (5). All cases in this report were reviewed to determine whether presymptomatic transmis- confirmed by polymerase chain reaction only. Asymptomatic sion might have occurred. Presymptomatic transmission was persons were not routinely tested, but such testing was per- defined as the transmission of SARS-CoV-2 from an infected formed for persons in groups considered to be at especially person (source patient) to a secondary patient before the source high risk for infection, such as evacuees on flights from Wuhan, patient developed symptoms, as ascertained by exposure and China (6), or families that experienced high attack rates. symptom onset dates, with no evidence that the secondary Patients with confirmed COVID-19 were interviewed to patient had been exposed to anyone else with COVID-19. obtain information about their clinical symptoms and activity Seven COVID-19 epidemiologic clusters in which presymp- history during the 2 weeks preceding symptom onset to ascer- tomatic transmission likely occurred were identified, and tain possible sources of infection. Contact tracing examined 10 such cases within these clusters accounted for 6.4% of the time from symptom onset until the time the patient was the 157 locally acquired cases. In the four clusters for which successfully isolated to identify contacts who had interactions the date of exposure could be determined, presymptomatic with the patient. All contacts were monitored daily for their transmission occurred 1–3 days before symptom onset in the health status, and those who developed symptoms were tested presymptomatic source patient. To account for the possibility as part of active case finding. of presymptomatic transmission, officials developing contact Clinical and epidemiologic data for all 243 reported tracing protocols should strongly consider including a period COVID-19 cases in Singapore during January 23–March 16 before symptom onset. Evidence of presymptomatic trans- were reviewed. Clinical histories were examined to iden- mission of SARS-CoV-2 underscores the critical role social tify symptoms before, during, and after the first positive distancing, including avoidance of congregate settings, plays SARS-CoV-2 test. in controlling the COVID-19 pandemic. Records of cases that were epidemiologically linked (clusters) Early detection and isolation of symptomatic COVID-19 were reviewed to identify instances of likely presymptomatic patients and tracing of close contacts is an important disease transmission. Such clusters had clear contact between a source containment strategy; however, the existence of presymptomatic patient and a patient infected by the source (a secondary or asymptomatic transmission would present difficult chal- patient), had no other likely explanations for infection, and lenges to contact tracing. Such transmission modes have not had the source patient’s date of symptom onset occurring after been definitively documented for COVID-19, although cases the date of exposure to the secondary patient who was subse- of presymptomatic and asymptomatic transmissions have been quently infected. Symptoms considered in the review included reported in China (1,2) and possibly occurred in a nursing facility respiratory, gastrointestinal (e.g., diarrhea), and constitutional in King County, Washington (3). Examination of serial intervals symptoms. In addition, the source patient’s exposure had to (i.e., the number of days between symptom onsets in a primary be strongly attributed epidemiologically to transmission from case and a secondary case) in China suggested that 12.6% of another source. This reduced the likelihood that an unknown transmission was presymptomatic (2). COVID-19 cases in source was involved in the cases in the cluster. Singapore were reviewed to determine whether presymptomatic transmission occurred among COVID-19 clusters.

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Cluster C. A woman aged 53 years (patient C1) was exposed Summary to a patient with confirmed COVID-19 on February 26 and What is already known about this topic? likely passed the infection to her husband, aged 59 years Preliminary evidence indicates the occurrence of presymptomatic (patient C2) during her presymptomatic period; both patients transmission of SARS-CoV-2, based on reports of individual cases in China. developed symptoms on March 5. Cluster D. A man aged 37 years (patient D1) traveled to the What is added by this report? Philippines during February 23–March 2, where he was in con- Investigation of all 243 cases of COVID-19 reported in Singapore tact with a patient with pneumonia who later died. Patient D1 during January 23–March 16 identified seven clusters of cases in which presymptomatic transmission is the most likely likely transmitted the infection to his wife (patient D2), aged explanation for the occurrence of secondary cases. 35 years, during his presymptomatic period. Both patients What are the implications for public health practice? developed symptoms on March 8. The possibility of presymptomatic transmission increases the Cluster E. A man aged 32 years (patient E1) traveled to Japan challenges of containment measures. Public health officials during February 29–March 8, where he was likely infected, conducting contact tracing should strongly consider including and subsequently transmitted the infection to his housemate, a period before symptom onset to account for the possibility a woman aged 27 years (patient E2), before he developed of presymptomatic transmission. The potential for symptoms. Both developed symptoms on March 11. presymptomatic transmission underscores the importance Cluster F. A woman aged 58 years (patient F1) attended of social distancing, including the avoidance of congregate settings, to reduce COVID-19 spread. a singing class on February 27, where she was exposed to a patient with confirmed COVID-19. She attended a church service on March 1, where she likely infected a woman aged Seven Clusters of COVID-19 Cases Suggesting 26 years (patient F2) and a man aged 29 years (patient F3), Presymptomatic Transmission both of whom sat one row behind her. Patient F1 developed Investigation of COVID-19 cases in Singapore identi- symptoms on March 3, and patients F2 and F3 developed fied seven clusters (clusters A–G) in which presymptomatic symptoms on March 3 and March 5, respectively. transmission likely occurred. These clusters occurred during Cluster G. A man aged 63 years (patient G1) traveled to January 19–March 12, and involved from two to five patients Indonesia during March 3–7. He met a woman aged 36 years each (Figure). Ten of the cases within these clusters were (patient G2) on March 8 and likely transmitted SARS-CoV-2 attributed to presymptomatic transmission and accounted for to her; he developed symptoms on March 9, and patient G2 6.4% of the 157 locally acquired cases reported as of March 16. developed symptoms on March 12. Cluster A. A woman aged 55 years (patient A1) and a Investigation of these clusters did not identify other patients man aged 56 years (patient A2) were tourists from Wuhan, who could have transmitted COVID-19 to the persons China, who arrived in Singapore on January 19. They vis- infected. In four clusters (A, B, F, and G), presymptomatic ited a local church the same day and had symptom onset on transmission exposure occurred 1–3 days before the source January 22 (patient A1) and January 24 (patient A2). Three patient developed symptoms. For the remaining three clus- other persons, a man aged 53 years (patient A3), a woman aged ters (C, D, and E), the exact timing of transmission exposure 39 years (patient A4), and a woman aged 52 years (patient A5) could not be ascertained because the persons lived together, attended the same church that day and subsequently developed and exposure was continual. symptoms on January 23, January 30, and February 3, respec- Discussion tively. Patient A5 occupied the same seat in the church that patients A1 and A2 had occupied earlier that day (captured This investigation identified seven clusters of COVID-19 by closed-circuit camera) (5). Investigations of other attendees in Singapore in which presymptomatic transmission likely did not reveal any other symptomatic persons who attended occurred. Among the 243 cases of COVID-19 reported in the church that day. Singapore as of March 16, 157 were locally acquired; 10 of Cluster B. A woman aged 54 years (patient B1) attended a the 157 (6.4%) locally acquired cases are included in these dinner event on February 15 where she was exposed to a patient clusters and were attributed to presymptomatic transmission. with confirmed COVID-19. On February 24, patient B1 and These findings are supported by other studies that suggest that a woman aged 63 years (patient B2) attended the same singing presymptomatic transmission of COVID-19 can occur (1–3). class. Two days later (February 26), patient B1 developed An examination of transmission events among cases in Chinese symptoms; patient B2 developed symptoms on February 29. patients outside of Hubei province, China, suggested that

412 MMWR / April 10, 2020 / Vol. 69 / No. 14 US Department of Health and Human Services/Centers for Disease Control and Prevention Morbidity and Mortality Weekly Report

FIGURE. Seven COVID-19 clusters with evidence of likely presymptomatic SARS-CoV-2 transmission from source patients to secondary patients — Singapore, January 19–March 12, 2020

Dates of likely transmission, symptom onset, and other exposure

Jan Feb

Cluster A 18 19 20 21 22 23 24 25 26 27 28 29 30 31 1 2 3 Symptoms

Patient A1 Fever

Patient A2 Fever

Patient A3 Fever

Patient A4 Fever, cough

Patient A5 Fever, sore throat

Dates of likely transmission, symptom onset, and other exposure

Feb

Cluster B 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Symptoms

Patient B1 Cough, headache, myalgia

Patient B2 Fever, cough, headache, myalgia

Dates of likely transmission, symptom onset, and other exposure

Feb Mar

Cluster C 26 27 28 29 1 2 3 4 5 Symptoms

Patient C1 Itchy throat, chills

Patient C2 Cough

Dates of likely transmission, symptom onset, and other exposure

Feb Mar

Cluster D 23 24 25 26 27 28 29 1 2 3 4 5 6 7 8 Symptoms

Patient D1 Cough, blocked nose

Patient D2 Fever, sore throat, sneezing

Source patient

Other exposure (clusters B, C and F: known COVID-19 case; cluster A: unknown exposure in Wuhan, China; cluster D: patient in Philippines with pneumonia; cluster E: unknown exposure in Japan; cluster G: unknown exposure in Indonesia)

Likely period of transmission from source patient to secondary patients

Symptom onset date

US Department of Health and Human Services/Centers for Disease Control and Prevention MMWR / April 10, 2020 / Vol. 69 / No. 14 413 Morbidity and Mortality Weekly Report

FIGURE. (Continued) Seven COVID-19 clusters with evidence of likely presymptomatic SARS-CoV-2 transmission from source patients to secondary patients — Singapore, January 19–March 12, 2020

Dates of likely transmission, symptom onset, and other exposure

Feb Mar

Cluster E 29 1 2 3 4 5 6 7 8 9 10 11 Symptoms

Patient E1 Fever

Patient E2 Cough

Dates of likely transmission, symptom onset, and other exposure

Feb Mar

Cluster F 27 28 29 1 2 3 4 5 Symptoms

Patient F1 Sore throat, blocked nose

Patient F2 Cough

Patient F3 Cough, runny nose, sore throat, myalgia

Dates of likely transmission, symptom onset, and other exposure

Mar

Cluster G 3 4 5 6 7 8 9 10 11 12 Symptoms

Patient G1 Fever

Patient G2 Sore throat

Source patient

Other exposure (clusters B, C and F: known COVID-19 case; cluster A: unknown exposure in Wuhan, China; cluster D: patient in Philippines with pneumonia; cluster E: unknown exposure in Japan; cluster G: unknown exposure in Indonesia)

Likely period of transmission from source patient to secondary patients

Symptom onset date

12.6% of transmissions could have occurred before symptom Environmental contamination with SARS-CoV-2 has been onset in the source patient (3). documented (8), and the possibility of indirect transmission Presymptomatic transmission might occur through generation through fomites by presymptomatic persons is also a concern. of respiratory droplets or possibly through indirect transmission. Objects might be contaminated directly by droplets or through Speech and other vocal activities such as singing have been shown contact with an infected person’s contaminated hands and to generate air particles, with the rate of emission corresponding transmitted through nonrigorous hygiene practices. to voice loudness (7). News outlets have reported that during The possibility of presymptomatic transmission of a choir practice in Washington on March 10, presymptomatic SARS-CoV-2 increases the challenges of COVID-19 con- transmission likely played a role in SARS-CoV-2 transmission tainment measures, which are predicated on early detection to approximately 40 of 60 choir members.* and isolation of symptomatic persons. The magnitude of this impact is dependent upon the extent and duration of transmis- * https://www.latimes.com/world-nation/story/2020-03-29/ coronavirus-choir-outbreak. sibility while a patient is presymptomatic, which, to date, have

414 MMWR / April 10, 2020 / Vol. 69 / No. 14 US Department of Health and Human Services/Centers for Disease Control and Prevention Morbidity and Mortality Weekly Report not been clearly established. In four clusters (A, B, F, and G), in the public health response to the COVID-19 pandemic, it was possible to determine that presymptomatic transmission including the avoidance of congregate settings. exposure occurred 1–3 days before the source patient developed Corresponding author: Vernon J. Lee, [email protected]. symptoms. Such transmission has also been observed in other 1Ministry of Health, Singapore; 2National Centre for Infectious Diseases, respiratory viruses such as influenza. However, transmissibility Singapore; 3Saw Swee Hock School of Public Health, Singapore. by presymptomatic persons requires further study. All authors have completed and submitted the International The findings in this report are subject to at least three limita- Committee of Medical Journal Editors form for disclosure of potential tions. First, although these cases were carefully investigated, the conflicts of interest. No potential conflicts of interest were disclosed. possibility exists that an unknown source might have initiated the clusters described. Given that there was not widespread References community transmission of COVID-19 in Singapore during 1. Qian G, Yang N, Ma AHY, et al. A COVID-19 Transmission within the period of evaluation and while strong surveillance systems a family cluster by presymptomatic infectors in China. Clin Infect Dis 2020. Epub March 23, 2020. https://doi.org/10.1093/cid/ciaa316 were in place to detect cases, presymptomatic transmission was 2. Du Z, Xu X, Wu Y, Wang L, Cowling BJ, Meyers LA. Serial interval of estimated to be more likely than the occurrence of unidenti- COVID-19 among publicly reported confirmed cases. Emerg Infect Dis fied sources. Further, contact tracing undertaken during this 2020. Epub March 19, 2020. https://doi.org/10.3201/eid2606.200357 period was extensive and would likely have detected other . 3 Kimball A, Hatfield KM, Arons M, et al. Asymptomatic and presymptomatic SARS-CoV-2 infections in residents of a long-term symptomatic cases. Second, recall bias could affect the accuracy care skilled nursing facility—King County, Washington, March 2020. of symptom onset dates reported by cases, especially if symp- MMWR Morb Mortal Wkly Rep 2020. Epub March 27, 2020. https:// toms were mild, resulting in uncertainty about the duration doi.org/10.15585/mmwr.mm6913e1 . 4 Ng Y, Li Z, Chua YX, et al. Evaluation of the effectiveness of surveillance of the presymptomatic period. Finally, because of the nature and containment measures for the first 100 patients with COVID-19 in of detection and surveillance activities that focus on testing Singapore—January 2–February 29, 2020. MMWR Morb Mortal Wkly symptomatic persons, underdetection of asymptomatic illness Rep 2020;69:307–11. https://doi.org/10.15585/mmwr.mm6911e1 . 5 Pung R, Chiew CJ, Young BE, et al.; Singapore 2019 Novel Coronavirus is expected. Recall bias and interviewer bias (i.e., the expecta- Outbreak Research Team. Investigation of three clusters of COVID-19 tion that some symptoms were present, no matter how mild), in Singapore: implications for surveillance and response measures. Lancet could have contributed to this. 2020;395:1039–46. https://doi.org/10.1016/S0140-6736(20)30528-6 The evidence of presymptomatic transmission in Singapore, 6. Ng O-T, Marimuthu K, Chia P-Y, et al. SARS-CoV-2 infection among travelers returning from Wuhan, China. N Engl J Med 2020. Epub in combination with evidence from other studies (9,10) sup- March 12, 2020. https://doi.org/10.1056/NEJMc2003100 ports the likelihood that viral shedding can occur in the absence . 7 Asadi S, Wexler AS, Cappa CD, Barreda S, Bouvier NM, Ristenpart WD. of symptoms and before symptom onset. This study identified Aerosol emission and superemission during human speech increase with voice loudness. Sci Rep 2019;9:2348. https://doi.org/10.1038/ seven clusters of cases in which presymptomatic transmission of s41598-019-38808-z COVID-19 likely occurred; 10 (6.4%) of such cases included . 8 Ong SWX, Tan YK, Chia PY, et al. Air, surface environmental, in these clusters were among the 157 locally acquired cases and personal protective equipment contamination by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a symptomatic reported in Singapore as of March 16. Containment measures patient. JAMA 2020. Epub March 4, 2020. https://doi.org/10.1001/ should account for the possibility of presymptomatic trans- jama.2020.3227 mission by including the period before symptom onset when 9. Hu Z, Song C, Xu C, et al. Clinical characteristics of 24 asymptomatic conducting contact tracing. These findings also suggest that infections with COVID-19 screened among close contacts in Nanjing, China. Sci China Life Sci 2020. Epub March 4, 2020. https://doi. to control the pandemic it might not be enough for only per- org/10.1007/s11427-020-1661-4 sons with symptoms to limit their contact with others because 10. Wang Y, Liu Y, Liu L, Wang X, Luo N, Ling L. Clinical outcome of persons without symptoms might transmit infection. Finally, 55 asymptomatic cases at the time of hospital admission infected with SARS-Coronavirus-2 in Shenzhen, China. J Infect Dis 2020. Epub these findings underscore the importance of social distancing March 17, 2020. https://doi.org/10.1093/infdis/jiaa119

US Department of Health and Human Services/Centers for Disease Control and Prevention MMWR / April 10, 2020 / Vol. 69 / No. 14 415 A modelling framework to royalsocietypublishing.org/journal/rspa assess the likely effectiveness of facemasks in combination with ‘lock-down’ in managing Research

Cite this article: Stutt ROJH, Retkute R, the COVID-19 pandemic Bradley M, Gilligan CA, Colvin J. 2020 A RichardO.J.H.Stutt1, Renata Retkute1,Michael modelling framework to assess the likely 2 1 3 effectiveness of facemasks in combination Bradley , Christopher A. Gilligan and John Colvin with ‘lock-down’ in managing the COVID-19 1Epidemiology and Modelling Group, Department of Plant Sciences, pandemic. Proc.R.Soc.A476: 20200376. University of Cambridge, Downing Street, Cambridge CB2 3EA, UK http://dx.doi.org/10.1098/rspa.2020.0376 2The Wolfson Centre for Bulk Solids Handling Technology, and 3Natural Resources Institute, University of Greenwich, Chatham Received: 30 April 2020 Accepted: 18 May 2020 Maritime ME4 4TB, UK ROJHS, 0000-0002-1765-2633

Subject Areas: COVID-19 is characterized by an infectious pre- computational biology, computational symptomatic period, when newly infected individuals mathematics can unwittingly infect others. We are interested in what benefits facemasks could offer as a non- Keywords: pharmaceutical intervention, especially in the settings COVID-19, modelling, facemask where high-technology interventions, such as contact tracing using mobile apps or rapid case detection via molecular tests, are not sustainable. Here, we Author for correspondence: report the results of two mathematical models and Richard O. J. H. Stutt show that facemask use by the public could make e-mail: [email protected] a major contribution to reducing the impact of the COVID-19 pandemic. Our intention is to provide a simple modelling framework to examine the dynamics of COVID-19 epidemics when facemasks are worn by the public, with or without imposed ‘lock-down’ periods. Our results are illustrated for a number of plausible values for parameter ranges describing epidemiological processes and mechanistic properties of facemasks, in the absence of current measurements for these values. We show that, when facemasks are used by the public all the time (not just from when symptoms first appear), the effective reproduction number, Re, can be decreased below 1, leading to the mitigation of epidemic spread.

2020 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/ by/4.0/, which permits unrestricted use, provided the original author and source are credited. Under certain conditions, when lock-down periods are implemented in combination with 2 100% facemask use, there is vastly less disease spread, secondary and tertiary waves are royalsocietypublishing.org/journal/rspa flattened and the epidemic is brought under control. The effect occurs even when it is assumed ...... that facemasks are only 50% effective at capturing exhaled virus inoculum with an equal or lower efficiency on inhalation. Facemask use by the public has been suggested to be ineffective because wearers may touch their faces more often, thus increasing the probability of contracting COVID-19. For completeness, our models show that facemask adoption provides population-level benefits, even in circumstances where wearers are placed at increased risk. At the time of writing, facemask use by the public has not been recommended in many countries, but a recommendation for wearing face-coverings has just been announced for Scotland. Even if facemask use began after the start of the first lock-down period, our results show that benefits could still accrue by reducing the risk of the occurrence of further COVID-19 waves. We examine the effects of different rates of facemask adoption without lock-down periods and

show that, even at lower levels of adoption, benefits accrue to the facemask wearers. These A Soc. R. Proc. analyses may explain why some countries, where adoption of facemask use by the public is around 100%, have experienced significantly lower rates of COVID-19 spread and associated deaths. We conclude that facemask use by the public, when used in combination with physical

distancing or periods of lock-down, may provide an acceptable way of managing the COVID- 476

19 pandemic and re-opening economic activity. These results are relevant to the developed as 20200376 : well as the developing world, where large numbers of people are resource poor, but fabrication of home-made, effective facemasks is possible. A key message from our analyses to aid the widespread adoption of facemasks would be: ‘my mask protects you, your mask protects me’.

1. Introduction The current COVID-19 pandemic, caused by the virus species severe acute respiratory syndrome- related coronavirus, named SARS-CoV-2 [1], has stimulated considerable controversy over the potential benefits of facemask use by the public and the timing of the initiation and termination of ‘lock-down’ periods. We define ‘facemask’ here to mean a protective covering for the nose and mouth, designed to interfere with airborne pathogen transmission. Clear answers to the questions surrounding facemask use are required urgently because they could inform national governments’ decisions and so prevent substantial loss of life, which might be avoided with this very ‘low’-level/inexpensive technology, and minimize the risk of health systems being overwhelmed with consequent high mortality rates of medical practitioners, front-line essential workers and those involved in healthcare sectors around the globe. It is also possible that this low-level technology, including home-made masks, could reduce the severe global economic impact of COVID-19, which has the potential to cause billions of people to suffer shortened life expectancy because of a reduced standard of living [2]. SARS-CoV-2 is similar to other respiratory pathogens in that airborne transmission occurs by inhaling droplets loaded with SARS-CoV-2 particles that are expelled by infectious people who are talking/coughing/sneezing [3,4]. This is most likely to occur in poorly ventilated areas where droplets or mist particles can accumulate and be inhaled [5–7]. Infection can also occur through the mucous membranes of the head (eyes, nose and mouth), when SARS-Cov-2 particles are picked up on the hands and then transferred to the head by face-touching behaviours. The currently available control measures to combat SARS-Cov-2, therefore, include: physical distancing, population lock-down periods, good sanitation/hand washing/surface disinfecting, good ventilation, facemask and visor protection, as well as diagnostics followed by contact tracing and quarantine of infected and exposed individuals. There is a wide range of dynamic-simulation, individual-based and statistical models that are being used to analyse COVID-19 data. Many of these models, however, are complex, so encounter challenges of analysis and interpretation in all but the most expert hands [8–15]. Our intention here is to provide a simple modelling framework to examine the probable effectiveness 3 of facemask wearing in combination with lock-down periods on the dynamics of COVID-19 royalsocietypublishing.org/journal/rspa epidemics. This involves scaling from individual behaviour to the level of populations to enable ...... conclusions to be drawn about the effectiveness, or otherwise, of wearing facemasks to reduce the spread of SARS-CoV-2. There is an extensive literature describing the dynamics of exhalation of virus from infected individuals (e.g. velocity, reach, separation into small and large droplets) [16,17] with analyses and models that focus on the individual. Here, we approach the key questions of this article by linking the effects of facemask wearing on the individual processes of SARS-Cov-2 transmission with population-level models to assess the effectiveness, or otherwise, of facemask adoption in combination with lock-down periods under different scenarios. We provide a framework for objective recommendations that could reduce the risks of future waves of the COVID-19 pandemic. In addition, we provide a synthesis of current knowledge and identify key areas of missing information/data that would be required to refine parameter values affected by facemask rc .Sc A Soc. R. Proc. interference in SARS-CoV-2 transmission processes. We first use an agent-based branching process model [18] to ask the simple question: given the high infectiousness of SARS-CoV-2, what level of facemask adoption by the public, associated with what level of facemask efficacy, would be required to reduce the effective 476 reproduction number (Re) to below 1? In our second model, we adapt a conventional susceptible– 20200376 : infected–removed (SIR) compartmental model [19,20] with the extension of including ‘free-living’ inoculum. The latter is shed from both pre- and post-symptomatic infectious individuals by talking, coughing and sneezing to generate virus-bearing droplets and a reservoir of SARS-CoV-2 particles on surfaces, known as fomites. At the start of the pandemic, the World Health Organization (WHO) did not advocate facemask wearing by the public owing to concerns over efficacy and the shortage of masks and other personal protective equipment (PPE) for health workers. We argue that the lack of experimental population-based data on facemask use [21] cannot be equated with facemask ineffectiveness, particularly when it is accepted that patients with other respiratory diseases such as influenza have been recommended to wear facemasks to limit virus-particle-laden droplet spread. Influenza has different dynamics from SARS-CoV-2, including a lower effective value for transmissibility [22], yet Yan et al.[22], for example, also reported that an 80% compliance rate for respiratory protective devices eliminated an influenza outbreak. A modelling study associated with the influenza management strategy [22] was also useful to public-health officials making decisions concerning resource allocation or public-education strategies. An earlier study [23]also concluded that household transmission of influenza could be reduced by the use of facemasks and intensified hand hygiene, when implemented early and used diligently. In addition, concerns about the acceptability and tolerability of the interventions should not be used as a reason against their recommendation. Our models can be used to consider the transmission dynamics from the perspective of the susceptible individual, including the possibility that facemask wearing may increase the risk of transmission (e.g. through adjustments to facemasks that result in increased touching of the face, with associated risk of inadvertent transmission of SARS-CoV-2) from airborne and fomite reservoirs. We also examine changes in parameter values across plausible ranges and seek to identify the likely range of effectiveness of facemask wearing, in association with population lock- down. In the absence of robust and reliable estimates for critical parameters, this approach can be used to provide simulations over a wide range of values and also to highlight where improved epidemiological parameter estimates are required. In this spirit, we propose, therefore, that the work presented here provides an objective and logical approach to examining the key question of whether, or not, the public should be advised to wear facemasks in the current COVID-19 pandemic. Our results hold for low-, middle- and high-income countries. We can ask the following questions at a population level. (i) How effective and how frequently would facemasks need to be used by the public to ‘flatten the disease progress curve’? (ii) How effective are facemasks at reducing the free-living SARS-CoV-2 inoculum and transmission rates? (iii) How does the timing of the implementation of lock-down periods and facemask adoption by 4 the public influence the models’ outcomes? royalsocietypublishing.org/journal/rspa ...... 2. Methods We use two complementary modelling approaches to test the effectiveness of facemask wearing by sections of the population in reducing the transmission rate of SARS-Cov-2 and hence in reducing the effective reproduction number, Re (the expected number of new cases caused by a single infectious individual at a given point in the epidemic). The first model uses a branching process to investigate the reduction in transmission by wearing facemasks, in order to assess the likely effectiveness of two control variables in reducing Re for the pathogen. The control variables are the proportion of the population wearing facemasks (essentially the probability that an individual wears a mask on a given day) and the effectiveness of the mask in reducing transmission (which relates to a range of masks that extend from crude porous coverings [24,25] rc .Sc A Soc. R. Proc. to masks of clinical standard [26,27]). The purpose of this model is to identify whether or not there are clear parameter ranges in which the two control variables could reduce Re sufficientlytobe expected to slow or stop the epidemic spread. We simulate the consequences of wearers using facemasks routinely, or only after the onset of symptoms. 476 In the second model, we adapt the common SIR formulation, to which we add free-living 20200376 : SARS-CoV-2 particles transmitted by inhalation from droplet inoculum and by touch and contact with facial orifices from the fomite inoculum deposited on surfaces (§2b(i)). The model is used to consider the likely impacts of facemask wearing in combination with phases of lock- down, interspersed with release from them. The flexible structure of this modelling framework importantly allows a distinction to be made between the potential for facemasks to reduce transmission from infected individuals (before and after symptom expression) and the protection conferred by facemasks on susceptible individuals [28]. The latter may be positive, whereby the facemask reduces inhalation of inoculum. It may also be negative; for example, where frequent manual adjustment of the facemask increases the probability of transmission. Our intention is to provide a flexible, yet comparatively simple modelling framework to test hypotheses about facemask wearing in combination with other epidemic strategies, which also allows scaling from individual behaviour to population consequences. SARS-CoV-2 is a new disease to humanity so, given the gaps in our knowledge about certain parameter values, the inferences should be viewed in this light. Further details of the models are summarized below and the code is available at https://github.com/camepidem/COVID-19_PRSA.

(a) Branching process transmission model We model SARS-CoV-2 transmission as a branching process model, where the number of secondary cases caused by one infectious individual is drawn from a negative binomial distribution with the mean equal to the product of the reproduction number (R0, the number of individuals infected by the introduction of a single infectious individual to an otherwise susceptible population) and dispersion parameter k, and the time of each new infection dependent on the incubation period of the primary case and the relative infectiousness β(t)[18]. The random branching process has been used for many COVID-19 analyses [29–37]. Given the wide variation = = in quoted values for COVID-19’s R0 [38], we consider two cases: R0 2.2 and k 0.54 [36]; and = R0 4.0, which is in line with the recent estimate of around 3.87, which is based on the initial growth of observed cases and deaths in 11 European countries [30]. We assume that time-varying relative infectiousness follows a shifted gamma distribution, reaching a peak 1–2 days before onset of symptoms [39] and then decreasing monotonically [40,41](figure 1). The incubation period is assumed to be lognormal with meanlog 1.43 and s.d.log 0.66 [39]. To implement control by wearing facemasks, we assumed that a proportion of the population (p) is wearing a mask. On a day when an individual wears a facemask, the relative infectiousness asymptomatic symptomatic 5 royalsocietypublishing.org/journal/rspa ...... 0.2

b

0.1

0 –2.5 0 2.5 5.0 7.5 days after symptom onset rc .Sc A Soc. R. Proc. Figure1. DistributionofasymptomaticandsymptomaticinfectiousnessofCOVID-19-infectedindividuals,usedinthebranching process [39]. Horizontal lines show the average infectiousness per time unit for the asymptomatic stage (orange) and the symptomatic stage (red). 476 20200376 : is reduced by (1 − γ ),whereγ is the effectiveness of a facemask in reducing transmissibility. We explore two scenarios: wearing a facemask after the onset of symptoms and wearing a facemask all the time.

(b) Susceptible–infected–removed model with free-living inoculum (i) Model description and formulation

The model structure is summarized in figure 2. There are two populations, facemask wearers and non-facemask wearers, each comprising individuals in the following categories: susceptible (S); exposed, i.e. latently infected (E); asymptomatically infectious (IA); symptomatically infectious (IS);andremoved(R). The removed class includes individuals who recovered from infection and those who died. Susceptible individuals can become infected by coming into contact with inoculum produced by individuals infected with SARS-CoV-2. We separate inoculum creation by infectious individuals, which gives rise to free-living inoculum, from inoculum uptake and infection of susceptible individuals. The inoculum can either be acquired by inhaling from transient droplet (D) forms in the air [42] or by contact with a decaying reservoir of inoculum deposited by infected individuals in the environment as fomites (F)[42], which can survive for up to 72 h on some surfaces [43]. There is a rapid deposition of droplet inoculum [44–46] with a slower decay of fomite (figure 2). There are two pairs of transmission rates, therefore: βA and βS for creation of inoculum by asymptomatic and symptomatic individuals, respectively, and βD and βF for uptake and infection of susceptible individuals from the droplet and fomite inoculum, respectively. Facemask wearing affects some or all of these parameters (cf. mi in figure 2). Facemasks reduce the amount of droplet inoculum escaping from infectious individuals [25] by capturing a proportion of droplets within the mask (mA, ms < 1). Facemasks also reduce the amount of droplet inoculum inhaled by susceptible individuals by capturing a proportion of droplets in inhaled air and hence reducing the uptake transmission rate (βD)bymD (figure 2). We assume initially that masks have a negligible effect on the risk of contacting inoculum from surfaces (βF) with mF = 1. The model does, however, allow for the fact that wearing a mask could increase infection risk from fomite infection (mF > 1); for example, through more frequent touching of the face when adjusting the mask. We note that significant PPE, such as a full face- hood, could act to reduce the risk of fomite infection (mF < 1). In addition, sanitation interventions such as hand washing would act to reduce the risk of infection from fomites (reducing βF)and susceptible exposed asymptomatic symptomatic removed 6 t t t mask infection E A S

S EI I R royalsocietypublishing.org/journal/rspa wearers A S ......

b b b b FmF DmD AmA SmS

t t decay F FDD inoculum creation fomite droplet b b A S inoculum inoculum b b susceptibleF D exposed asymptomatic symptomatic removed non- infection t t t mask E A S SEIA IS R wearers A Soc. R. Proc.

Figure 2. Schematic of the SIR framework model for interacting populations of facemask and non-facemask wearers, in which transmissionpathwaysaredistinguishedbetween(i)inoculumcreationbyasymptomaticandsymptomaticinfectedindividuals

and (ii) uptake/infection from droplet and fomite inoculum. The model can be adapted further to allow for cycles of population 476 lock-downs. 20200376 :

additional cleaning of surfaces or the use of quicker self-sterilizing surfaces can be modelled via reducing the lifespan of fomite inoculum (τ F). Here, we restrict our analysis to the effects of facemasks and lock-down periods. The model is formulated and solved as a simple deterministic differential equation model, summarized below for completeness. We note that the model can be recast readily in stochastic form with transition probabilities. It is also simple to divide the target country into metapopulations in which the contact rates differ, for example among cities and rural areas or between age classes in the population, and to spatially partition the population with localized inoculum pools. Here, we use the model to look at orders of magnitude for how facemask wearing complements a major control strategy that involves lock-down of a proportion of the population. β = We simulate this by assuming that lock-down reduces the transmission rates ( i, i A,S,D,F)by a fixed proportion, q. It reduces the inoculum produced by infectious individuals in public areas and thus reduces the inoculum available in the D and F pools, and additionally reduces the time spent in contact with that inoculum by susceptibles. Thus, in the model, lock-down works to reduce overall effective spread rates by a factor of q2. Model equations dS =−(β m F + β m D)S, dt F F D D dE E = (βFmFF + βDmDD)S − , dt τE dI E I A = − A , dt τE τA dI I I S = A − S , dt τA τS dR I = S , dt τS dD D = βAmAIA + βSmSIS − , dt τD dF D F = − . dt τD τF R0 calculation 7 Given a population size of N (large, R0), all susceptible and the introduction of one exposed royalsocietypublishing.org/journal/rspa individual: ...... Total droplet inoculum produced = β τ + β τ DTotal A A S S. Total infections caused by droplet (D) and fomite (F)inoculum = β τ ID DNDTotal D, = β τ IF FNFTotal F. = Thus R0, i.e. total infections caused by the initial introduction (noting DTotal FTotal ) = β τ + β τ R0 ( D D F F)DTotal N,

= β τ + β τ β τ + β τ A Soc. R. Proc. R0 ( D D F F)( A A S S)N. β τ Given the proportion of R due to droplets, μ = D D , we obtain a relation between the 0 (βDτD+βFτF) droplet and fomite spread rates (μ = 1)   μ τ 476 β = F β D F 20200376 : 1 − μ τD and so     μ − μ R0 1 R0 βD = , βF = . βAτA + βSτS NτD βAτA + βSτS NτF A summary of the model parameters and default values for the modified SIR compartmental model with free-living inoculum is given in table 1.

(ii) Additional assumptions and knowledge gaps

A key assumption of the model is that those people who have been infected and have recovered have immunity to further infections. At present, there are no experimental data to validate this assumption [48] and it is widely accepted that the four related, seasonal coronaviruses, responsible for up to 30% of common colds, cause illness repeatedly, even though people have been exposed to them throughout their lives. We also make assumptions and simplifications about the effectiveness of facemasks because there is a wide range of possible designs [49]. In general, however, the important fact here is that inoculum release is principally through the mouth, which the facemask covers effectively, so this is a key point is estimating the facemasks’ efficacy at catching exhaled inoculum. Evidence from the literature shows that the filtration efficiency of different cotton-fabric facemasks varies between 43% and 94% in controlling the passage of bacteria [47], which travel in moisture droplets in the same way as viruses. Droplet-blocking efficiency of fabric samples was shown to be 90–98% for 100% cotton T-shirt, dishcloth and silk shirt, which was as high as for fabric material used for the production of a three-layered commercial medical mask [50]. More recent research showed that surgical facemasks significantly reduced the detection of influenza virus RNA in respiratory droplets and coronavirus RNA in airborne droplets and it was concluded that surgical facemasks could prevent coronavirus transmission from symptomatic individuals [51]. In addition, facemasks capture the larger droplets most effectively, and these carry most of the virus load (a droplet with twice the diameter has eight times the weight and virus content). Further qualitative evidence of the effectiveness of facemasks at catching exhaled infection agents is the universal acceptance of the need for surgeons to wear a facemask when operating to avoid the infection of the wound on which they are working. We assume, therefore, that facemask effectiveness in exhalation is probably well above 50% on average, but probably poorer on inhalation; we justify this in terms of the difference in dynamics between airflow coming out from or going into an orifice (nose or mouth). This can be illustrated by the ability to blow out Table 1. Model parameters and default values for the modified SIR compartment model with free-living inoculum. Note that 8 our inferences, choices of parameters and population sizes do not relate to healthcare environments, as would be found in royalsocietypublishing.org/journal/rspa

hospitals, where inoculum levels may be extremely high and personnel already wear appropriate PPE......

parameter description default value source N population size 60 million approximate mainland GB population size ...... R0 basic reproductive rate 4 [30] ...... βA inoculum release rate of asymptomatic 2.71 unit inoculum per relative to βS [39] infectious individuals day per capita ...... βS inoculum release rate of symptomatic 1 unit inoculum per arbitrarily defined, without loss of infectious individuals day per capita generality ...... −5 βD infection rate due to droplet inoculum 4.46 × 10 per unit fitted subject to default values of R0, μ N

inoculum per day and A Soc. R. Proc...... −9 βF infection rate due to fomite inoculum 2.58 × 10 per unit fitted subject to default values of R0, inoculum per day μ and N ...... mA reductionininoculumreleaserateof 0.5 arbitrarily set in the absence of detailed asymptomatic individuals for mask data on individual-based transmission; 476 wearers consistent with lower ranges quoted by 20200376 : Furuhashi [47]; van der Sande et al. [25] ...... mS reductionininoculumreleaserateof 0.5 arbitrarily set in the absence of detailed symptomatic individuals of mask data on individual-based transmission; wearers consistent with lower ranges quoted by Furuhashi [47]; van der Sande et al. [25] ...... mD reductionininoculuminfectionratedueto 0.5 arbitrarily set in the absence of detailed droplet inoculum for mask wearers data on individual-based transmission ...... mF reductionininoculuminfectionratedueto 1.0 arbitrarily set in the absence of detailed fomite inoculum for mask wearers data on individual-based transmission ...... q reduction of transmission rates from 0.5 [30] showing Re dropped from ∼4 before lock-down of the population to ∼1afterlock-down ...... τ E average duration between infection and 3.8 d [39] onset of asymptomatic infectiousness ...... τ A average duration between onset of 1.2 d [39] asymptomatic infectiousness and first symptoms ...... τ S average duration between first symptoms 3.2 d [39] and end of infectiousness ...... τ D average lifespan of droplet inoculum 10 s [44–46] before deposition ...... τ F average lifespan of fomite inoculum before 48 h [43] loss of viability ...... μ assumed proportion of infections due to 0.5 arbitrarily set in the absence of detailed dropletinoculumintheabsenceof data on individual-based transmission masks or other forms of control ...... a lit match at arm’s length compared with the impossibility of putting it out by sucking in air. Exhaled air, therefore, is likely to go mostly through the fabric, whereas inhaled air is much more likely to enter around the sides of a facemask, if it is unsealed. R : 2.2 R : 4.0 0 0 9 100 royalsocietypublishing.org/journal/rspa ...... 75

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Figure 3. Heat maps of the effective reproduction numberR ( e) as a function of control parameters for two values of R0.Even when R0 is 4.0, the best outcomes are achieved when masks are worn all the time, a high proportion of the population wear them and their efficacy is high.

3. Results (a) Model 1: branching process transmission

We explore how the effective reproductive number (Re), i.e. the average number of infections generated by an infectious individual in the population, changes under a range of possible values for the proportion of a population wearing facemasks and the efficacy of the facemasks. Figures 3 and 4 show results for simulations with the branching process model run initiated with 100 infectious individuals in generation 1 and the proportion of the population wearing a facemask after generation 3. We distinguish between two scenarios: facemasks worn after symptoms are expressed and facemasks worn all the time. By ‘all the time’, we mean compliance with normal facemask procedures when in public [52], irrespective of whether or not COVID-19 symptoms are being expressed. Even when the initial reproductive number (R0) is 4.0, our analyses show that the best reductions in the Re occur when facemasks are worn all the time, by a high proportion of the population and their efficacy is high (figure 3). It is also possible (subject to the simplifying assumptions) for Re to be brought below 1, when the public wear effective facemasks all of the time (rather than only starting when COVID-19 symptoms appear), leading to the epidemic dying out. These exploratory analyses from this model suggest that there are regions of parameter space (proportion of population wearing facemasks and effectiveness of the facemasks in reducing transmission) in which this intervention strategy could be effective. We now examine the dynamics in more detail, with a more mechanistic model, albeit in which there is still uncertainty over some parameter values. effectiveness: 25% effectiveness: 50% effectiveness: 75% effectiveness: 95% 10 4 royalsocietypublishing.org/journal/rspa ...... 3 e

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1 rc .Sc A Soc. R. Proc. wearing: all time 0 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 population wearing facemask (%) 476 Re

Figure 4. The effect on of the proportion of the population wearing a facemask. The solid line is the mean and the shaded 20200376 : area shows the 95% confidence interval. By the public wearing an effective facemask all of the time (rather than juststarting when COVID-19 symptoms appear), the Re can be brought below 1, leading to the pandemic dying out.

(b) Model 2: the adapted susceptible–infected–removed compartment model This model allows us to investigate the interactions between lock-down periods and various percentages of facemask adoption by the public. Here, we examined the effects of changing the proportion of people wearing masks (0%, 25%, 50%, 100%), when there are successive periods of lock-down. Our focus here is on the potential for reducing SARS-CoV-2 transmission by facemasks and we do not consider any other intervention besides population lock-down. We first examine the epidemic dynamics, for different proportions of facemask wearers, when facemask wearing is initiated at the beginning of the epidemic. The epidemic takes off exponentially and is only slowed by the imposition of the first lock-down period, which we assume reduces overall transmission of the virus (table 1 and figure 5a). A second wave begins after the first lock-down is lifted, which is suppressed by the second lock-down period. By the third lock-down period, under this scenario, everyone has become infected and the epidemic dies down. This does assume that infected/recovered people have become immune/resistant. With 25% facemask adoption, the initial peak is flattened, but the second wave is more pronounced (figure 5b). At 50% adoption, secondary and tertiary disease peaks occur in the second and third lock-down periods (figure 5c). The benefits of the additional reduction in transmission rate effected by facemasks are fairly equally divided between facemask and non-facemask wearers (figure 5c). When 100% of the public wear facemasks, disease spread is greatly diminished and the total numbers of ‘removed’ are substantially lower. Here, we consider an 18 month time scale, either until the introduction of a vaccine or to the point at which sustained lock-down control efforts are not feasible. We next relax the assumption that facemask wearing begins from early in the epidemic when there are just 100 detected cases (as in figure 5) and investigate the later adoption at 30, 60, 90 and 120 days. While later adoption leads to increases in the numbers of individuals who become infected, even when implemented at 120 days after the initiation of the epidemic (figure 6), 100% adoption of facemasks by the public (under the current assumptions: table 1 and figure 6d)stops the occurrence of further COVID-19 epidemic waves. We also note that there are benefits to employing facemasks even when Re has fallen below 1. For example, the number of active cases drops off much faster in figure 6b, where the adoption of facemasks occurs shortly after the peak (a)(no masks b) masks: 25% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles 11 60 total removed 60 total removed total active symptomatic total active symptomatic mask wearers removed

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masks: 50% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% masks: 100% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% (c)(lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles d) lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles 60 total removed 0.06 total removed total active symptomatic total active symptomatic 50 mask wearers removed 0.05 non-mask wearers removed 40 0.04

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Figure 5. The vertical, blue, dotted line indicates the time at which facemask wearing is adopted. (a) With no facemasks, the 20200376 : diseaseprogresscurveincreasesexponentiallybeforeperiods2and3andisonlyslowedbytheimpositionofthefirstlock-down period. When this ends, a second wave begins, which is suppressed by the third lock-down period. By the fourth lock-down period, everyone has become infected and the epidemic dies down. This does assume that infected/recovered people have become immune/resistant. (b) With 25% facemask adoption, the initial three peaks are flattened, but a second, larger wave appears in the fourth lock-down period. There are clear benefits to facemask wearers, compared with non-wearers.c ( )At50% adoption, the disease progress curve does not take-off until after the fourth lock-down period.d ( ) When 100% of the public wear facemasks, disease spread is greatly diminished and the total numbers of ‘removed’ is much lower (note the different y-axis scale for d).

in active cases is reached, than in figure 6d, where facemasks are not adopted until later. This faster drop in active cases could allow for an earlier lifting of lock-down. We note that, when the number of cases is reduced to a sufficiently low level, other forms of control such as contact tracing become more feasible. For completeness, we analysed the effects of facemask use in the absence of lock-down or other mitigation procedures (figure 7). We note that, in scenarios 5c and 5d, the epidemic has not infected enough of the population to reach herd immunity in the absence of periodic lock-downs. The long-term dynamics of these outbreaks after the relaxation of lock-down are examined in figure 6. The default parameters remain as in table 1 and salient parameters are repeated in figure 7. It is clear that, consistent with an epidemic with an R0 value of approximately 4 [30], the epidemic increases exponentially, leading to very high levels of infection. Here, as elsewhere, we assume that infection confers immunity, though that assumption can easily be relaxed by expanding the framework with free-living inoculum to incorporate a SIRS model, where after some time removed individuals can become susceptible again. Adoption of facemask wearing by 25% of the population decreases the level of infection in the population (figure 7b). The effects increase with greater adoption (figure 7c,d). At 100% adoption (figure 7d), the disease progress curve is flattened significantly and the total number of individuals infected is reduced. We note that 100% facemask adoption without lock-down achieves a greater reduction in the final size of epidemic, a lower ‘total removed’ and a lower peak of active cases than lock-down without facemasks (figure 5a). These results are striking in that the benefits accrue to the facemask wearer as well as to the population as a whole. We have assumed a reduction each in inhalation and exhalation of 50% of droplet inoculum compared with no facemask. a masks: start: T+30 days, 100% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% b masks: start: T+60 days, 100% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% ( )(lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles ) lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles 12 6 total removed 60 total removed total active symptomatic total active symptomatic

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masks: start: T+90 days, 100% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% masks: start: T+120 days, 100% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% (c) lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles (d) lock-down: start: T+45 days, duration: 90 days, 50% contact reduction, 30 days off, 4 cycles 60 total removed 60 total removed total active symptomatic total active symptomatic 50 50

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Figure 6. Effect of changing start date for facemask adoption, shown by the blue dashed line.(a–d) T + 30d, T + 60d, 20200376 : T + 90d,T + 120d,respectively.Thefirstlock-downperiodstartedatT + 90d.Earlieradoptionoffacemasks(a)hasadifferent y-axis scale, because the end values of total removed are significantly lower. Even when implemented at T+120 days, 100% adoption of facemasks by the public stops the occurrence of additional COVID-19 pandemic waves.

no masks masks: 25% wearing, inoculum capture: 50% exhale, 50% inhale, fomite 0% (a)(no lock-down b) no lock-down 60 total removed 60 total removed total active symptomatic total active symptomatic 50 50 mask wearers removed non-mask wearers removed 40 40

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Figure7. Effectsoffacemaskadoptionintheabsenceoflock-downperiods,usingthesamefacemask-wearingproportionsasin figure. 6 The vertical, blue dotted line indicates the time at which facemask wearing is adopted. (a) Default epidemic dynamics in the absence of any intervention. (b) Twenty-five per cent facemask wearers in the population slows the overall epidemic progression, but provides minimal reduction in final size.c ( ) Fifty per cent adoption of facemasks further slows epidemic progression and slightly decreases final size, with benefits distributed fairly evenly between mask and non-mask wearers.d ( ) One hundred per cent adoption with 50% reduction in inhalation and exhalation leads to flattening and delay of the disease progress curve and the total number of individuals infected in the population is reduced (see table 1 for default parameters). allocation of benefits from wearing (a) masks: inoculum capture: 50% exhale, 50% inhale, fomite 0% 13 1.0 royalsocietypublishing.org/journal/rspa ......

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Figure 8. The per capita probability of infection in relation to the proportion of the population wearing facemasks and the negative effects of fomite infection, owing to poor compliance. The blue dashed line represents the individual probability of infection when no one wears a facemask. (a) When the fomite parameter is at 0% and droplet exhalation and inhalation are both reduced by 50% for facemask wearers (good compliance and facemask), facemask wearers benefit more than non- facemask wearers and the probability of infection drops with increasing proportion of the population wearing facemasks, and is always lower for both facemask wearers and non-wearers than if nobody wears a mask. (b) When facemask wearing incurs a susceptibility penalty, with the fomite susceptibility increased by 100% and a 50% reduction in droplet exhalation, but no effect on droplet inhalation (bad compliance and facemask), there is a net benefit to the population, but the mask wearersare personally worse off until about 65% of the population is wearing them, when even the facemask wearers become betteroff than if nobody wears facemasks. (c) When compliance and facemask usage are very bad (fomite susceptibility increase of 300% and 50% droplet exhalation reduction), non-facemask wearers are at an advantage but, counterintuitively, until about 80% facemaskadoption,thereisstillasmallnetbenefittothepopulationasawhole,althoughalargerbenefittonon-maskwearers. Note the different axis scales in each subplot, e.g. the facemasks ina ( ) are able to deliver a 40% reduction in population-level risk, while the facemasks in (b,c) are only able to deliver up to a 15% reduction, to a portion of the population. It is also instructive to consider the per capita probability of infection in relation to the 14 proportion of the population wearing facemasks and the negative effects of fomite infection, royalsocietypublishing.org/journal/rspa owing to poor compliance and ineffective facemasks. When the fomite parameter for infection ...... is at 0% (good compliance and facemask), facemask wearers benefit more than non-facemask wearers and the probability of infection drops with increasing proportion of the population wearing facemasks. As the proportion of mask wearers increases, the benefits to both facemask wearers and non-facemask wearers increase (figure 8a). We see that if facemask wearing were to incur a susceptibility penalty—with the fomite parameter increased by 100% and no protection against droplet inhalation, while retaining the 50% reduction in droplet exhalation—there is still a net benefit to the population. In this scenario, the mask wearers are personally worse off until about 65% of the population is wearing masks, at which point even the facemask wearers become better off than if nobody in the population was wearing facemasks (figure 8b). When compliance and facemask wearing are very bad (300% increase in fomite susceptibility with only the 50% reduction in droplet exhalation), non-mask wearers are at an advantage, rc .Sc A Soc. R. Proc. but a highly counterintuitive finding is apparent in that, until about 80% facemask adoption, there is still a net benefit to the population as a whole, and a greater benefit for non-mask wearers. This non-intuitive result is due to the fact that, while an individual is made much more susceptible, this is more than counteracted by the reduced infectiousness of many individuals. 476 These facemask wearers are more likely to contract the disease, but less likely to infect others 20200376 : (particularly non-facemask wearers) once infected. When most of the population is wearing these facemasks, the effect of reduced infectiousness is outweighed by the fact that the majority of the population is much more susceptible. In the unlikely eventuality of facemasks with this property, it would be advisable to preferentially issue these masks to individuals less vulnerable to severe complications, leaving more vulnerable individuals unmasked in order to maximize overall benefits, while still achieving a lower level of infection within the population. 4. Discussion The emergence of the COVID-19 pandemic has stimulated a search for possible interventions, such as SARS-CoV-2 vaccines, but these may not be effective or become available in the near future [53]. There has also been a lack of clarity in the thinking surrounding the potential benefits of population-level adoption of facemasks, which could provide a cheap and effective means of managing COVID-19 epidemics in high-, middle- and low-income countries. Previous work used a similar mathematical model-based approach to estimate the relative contributions of the four pathways to infection risk in the context of a person attending a bed-ridden family member ill with influenza [54]. Our models, however, concern SARS- CoV-2 and are focused on the population consequences of lock-down periods and facemask adoption. Our conclusions are similar, however, in that, given the current limited information on dose and infectivity via different exposure pathways, non-pharmaceutical interventions should simultaneously address potential exposure via face-touching behaviour and inhalation of virus particles. A separate study also recently analysed the effectiveness of facemasks using a compartmental, ordinary differential equation model, albeit in a more conventional form, without the incorporation of free-living inoculum [55]. Similarly, they concluded that facemasks were valuable in reducing virus transmission. They also demonstrated that the relative benefit of facemask use was greater when adopted earlier [55]. Neither Nicas & Jones [54] nor Eikenberry et al.[55] considered facemasks in combination with lock-down periods. We first used a relatively simple mathematical model to ascertain the potential impacts of facemasks, given the transmission characteristics of SARS-CoV-2. Then, we used a modified SIR model with free-living inoculum that enables distinction between SARS-CoV-2 particle shedding and uptake/infection to integrate cycles of lock-down periods interspersed with release of the public. Our intention here is not to reproduce detailed, realistic, individual-based simulation models [56] but rather to introduce and analyse a simple mechanistic model that can be used to inform understanding of fundamental dynamics. We use available literature as well as plausible assumptions to parametrize our models. It is understood, however, that our estimated outcomes 15 are influenced by these parameter ranges and values. royalsocietypublishing.org/journal/rspa

Our mechanistic, modified SIR model can be used to analyse any intervention that ...... affects transmission rates, with the advantages of separating droplet from fomite components. This model could also readily be made more realistic and complex, by considering and including linked subpopulations within a metapopulation, stochastic processes and allowing for uncertainty by sampling parameters from posterior or other distributions. Our approach is to accept that, with a new disease, it is impossible to get accurate experimental evidence for potential control interventions, but that this problem can be approached by using mathematical modelling tools to provide a framework to aid rational decision-making. For completeness and objectivity, we also model a scenario where facemask adoption had negative effects. We do consider this scenario unlikely, however, because countries where facemask wearing is mandatory are currently experiencing relatively low numbers of COVID-19 cases and deaths [57,58]. rc .Sc A Soc. R. Proc. Both of our models show that, under a wide range of plausible parameter conditions, facemask use by the public could significantly reduce the rate of COVID-19 spread, prevent further disease waves and allow less stringent lock-down regimes. The effect is greatest when 100% of the public wear facemasks. It follows that the adoption of this simple technology ought to be re-evaluated in 476 countries where facemask use is not being encouraged. Within the parameter regimes tested, the 20200376 : models also show that, if COVID-19 is to be controlled or eradicated, early lock-down combined with facemask adoption by close to 100% by the public needs to occur. This, of course, does not exclude the implementation of other management interventions, such as widespread testing and contact tracing. The detailed conclusions that can be drawn from the branching process, transmission model are:

(i) With a COVID-19 R0 of 2.2 and for scenarios where facemasks were worn only after onset of symptoms, the median R0 fell below 1, if at least 95% of the population wore facemasks (with an efficacy similar to that of N95 respirators designed to achieve a very close facial fit and highly efficient filtration of 0.3 µm airborne particles). (ii) When the COVID-19 R0 was higher (4.0), wearing a facemask after the onset of symptoms still decreased the median Re to just below 2, when there was high adoption and efficacy of facemasks. (iii) With a policy that all individuals must wear a facemask all of the time, a median effective COVID-19 R0 of below 1 could be reached, even with facemask effectiveness of 50% (for = = R0 2.2) or facemask effectiveness of 75% (for R0 4).

Our analyses from this model are consistent with the conclusions of practical studies on the use of professional and home-made facemasks to reduce exposure to respiratory infections among the public, where it was concluded that any type of general mask use is likely to decrease viral exposure and infection risk on a population level, in spite of imperfect fit and/or adherence [25]. Other studies on respiratory virus transmission have concluded that, for compliant users, facemasks were highly efficacious at preventing spread [59]. In a pandemic situation as now exists, compliance is affected by perception of risk, so we would expect compliance to be high. The detailed conclusions from the modified SIR model are consistent with those of the first model and are that:

(iv) Lock-down periods alone do not prevent the occurrence of secondary and tertiary waves of the pandemic occurring and these may be larger than the initial wave (figures 5 and 6). (v) If lock-down periods are combined with 100% adoption of facemask use by the public, the initial disease progress peak is dramatically flattened and delayed and subsequent waves are prevented (figures 5c and 7a). (vi) At the time of writing, facemask or face-covering use by the public has not been 16 recommended by the UK, apart from in Scotland. We considered, therefore, the effects royalsocietypublishing.org/journal/rspa

of varying the time of facemask adoption by the public and show that, even if facemask ...... use began immediately while in the first lock-down period, major benefits would still be accrued by preventing the occurrence of further COVID-19 disease waves (figure 6a–c). (vii) We consider a scenario, for completeness, where there are no lock-down periods and facemask use has negative effects on the wearer (figure 8b,c). This is clearly the worst case but we consider that, in practice, negative effects of facemask adoption are improbable, because countries where facemask use is mandatory have relatively low COVID-19 spread and numbers of deaths. Even here, however, there is the highly counterintuitive outcome that, although the facemasks were bad for the individuals wearing them (because of extremely poor compliance issues and a bad facemask design), people wearing them still provided a net benefit to the population as a whole. Here, we have analysed a range of possible values for the enhanced risk from fomite inoculum to rc .Sc A Soc. R. Proc. facemask wearers. With currently available data, it is not possible to identify which, if any, of these values is most likely. Further experimental work is required to address this important aspect of facemask use. (viii) We examined the effects of different rates of facemask adoption alone (with no lock- 476 down periods) by the public and show that, at lower levels of adoption, there are real 20200376 : benefits to facemask wearers. This difference is reduced as the per cent facemask adoption increases to 50%. At 100% adoption, the disease progress curve is flattened and delayed significantly, as well as the total removed from the population being reduced. There is, therefore, a clear incentive for people to adopt facemask wearing (figures 7 and 8a). This is a similar conclusion to that reached by another modelling study that concluded that facemask use by the public is potentially of high value in curtailing community transmission and the burden of the pandemic [55]. (ix) A combination of facemask wearing and lock-down periods implemented together is indicated to provide a better solution to the COVID-19 pandemic than either in isolation. The models indicate that a combined mitigation strategy is required to reduce the transmission of the pathogen to flatten and delay the disease progress curves and to prevent repeated waves of infection. Here and elsewhere, our results are subject to the assumptions in our models, including some arbitrary but reasonable assumptions about key parameters, given the current state of knowledge. The effects of control measures = observed in the results presented here with R0 4.0 are greatly enhanced with a lower R0.

When a new disease to humanity, caused by a pathogen, first appears and spreads, there is an unavoidable lack of information on which to base rational control-intervention decisions. An obvious knowledge gap is the lack of accurate data on the period when individuals are non- symptomatic, but infectious. These data would clearly help with contact tracing, in terms of the duration of the historical search-period required. Also, information on the size of the infectious dose for SARS-CoV-2 is lacking, but research on SARS-CoV (the 2003 virus) showed that between 43 and 280 individual virus particles had to enter the human body in order to start an infection [60]. Even home-made masks, washed in soapy water after each use, therefore, should reduce fomite build-up and droplet-mediated airborne transmission. Surgical-grade masks, however, would probably be required to reduce transmission by droplets containing viral inoculum, as was reported for the influenza virus [61]. In the current COVID-19 pandemic, one solution to this dearth of information has been to advocate implementation of the precautionary principle on interventions, which can be defined as ‘a strategy for approaching issues of potential harm, when extensive scientific knowledge on the matter is lacking’. Evidence on the efficacy and acceptability, or otherwise, of facemasks to combat respiratory disease spread, for example, is sparse and contested [62], but deaths in many countries are rising steeply, with little time as yet to collect appropriate and rigorous scientific data. The precautionary principle approach would be to encourage populations to adopt facemask wearing 17 immediately, given that facemasks are considered essential PPE for front-line healthcare workers royalsocietypublishing.org/journal/rspa and that ‘we have little to lose and potentially something to gain from this measure’ [63]...... Our modelling framework highlights the urgent need to translate individual-based research on coughing, sneezing and exhaling into SARS-CoV-2 transmission rates, as shown in figure 2. One way to do this is to identify viral loads of SARS-CoV-2 that are required for infection and also to quantify the dispersal of particulate inoculum. That would also have a bearing on social distancing advice where, to date, the identification of 2 m is arguably arbitrary. In a study investigating environmental contamination by SARS-CoV-2 from a symptomatic patient wearing an N95 facemask, no SARS-CoV-2 particles were detected on the front surface of the facemasks worn by the study’s physicians [65]. Other recent evidence on facemasks for reducing SARS- CoV-2 transmission is provided by an epidemiological investigation where a patient transmitted COVID-19 to five people in one vehicle when he did not wear a facemask. In a later journey, no one was infected in the second vehicle when he wore a facemask [5]. rc .Sc A Soc. R. Proc. Although our modelling framework demonstrates that, under certain conditions, facemask adoption by entire populations would have a significant impact on reducing COVID-19 spread, there are additional human factors and obstacles that may prevent the implementation of this policy or a directive being issued at a governmental level. The most important of these is probably 476 the perceived lack of availability of efficient facemasks (N95 respirators) and the view that these 20200376 : should and must be reserved for front-line medical workers. In emergency situations such as this where there are acute PPE shortages, however, it would be pragmatic and acceptable for people to improvise and fabricate their own solutions to the problem [25,49,66]. The natural mechanics of filtration are that larger droplets are captured more effectively. So, it can safely be assumed that droplets in the 1 µm plus range will be almost completely eliminated by such an informally made mask. This is very important because a 2 µm droplet has a thousand times the mass of a 200 nm droplet, and a 20 µm droplet has a million times the mass of a 200 nm droplet, the virus load being proportional to the mass. The larger the droplets, the more important it is to capture them, and even a home-made mask will do this very well. There are also experimental data, for instance, that show that home-made facemasks consisting of one facial tissue (inner layer on the face) and two kitchen paper towels as the outer layers achieved over 90% of the function of surgical mask in terms of filtration of 20–200 nm droplets [25]. These facemasks are also disposable, so would clearly provide a pragmatic solution to the problem, and there are many sites now on social media that provide clear instructions on facemask making and safe use [49]. Our analysis indicates that a high proportion of the population would need to wear facemasks to achieve reasonable impact of the intervention. In Hong Kong, 99% of survey respondents reported wearing facemasks when outside of their home [67]. Another human factor that may reduce facemask adoption in Western countries is cultural, because the use of facemasks is not common in public, or there is an implication that the facemask wearer considers others as a threat. In the current emergency, however, it is necessary to change this view, which could be achieved if the message conveyed by a facemask was ‘my facemask protects you, your facemask protects me’. Indeed, it is probable that making facemasks into fashion items may be another route to changing the culture surrounding facemask use in public. A further positive effect from this cultural change would be to reinforce the message that it is necessary to keep to a safe distance from one another. This educational message could be conveyed easily by the government and popular press. While our mathematical models indicate the need for improved parameter estimates, β τ especially for i and mi, but also for the intrinsic epidemiological parameters ( i)anddecay rates for droplet inoculum and fomite, they have also indicated some important interactions with respect to timing of interventions in relation to the periodicity imposed on the dynamics by periods of lock-down. Our exploratory analyses when modelling the initiation of facemask adoption before, during and after an initial lock-down period indicate that the precise balance of infecteds and susceptibles upon release from lock-down can have profound, counterintuitive consequences for the occurrence of subsequent waves and the ultimate numbers of infected individuals in the population. This and further analyses of the benefits to facemask and 18 non-facemask wearers are the subject of further research. royalsocietypublishing.org/journal/rspa

Potential extensions to the modelling framework presented here include the extension to ...... a metapopulation, spatially partitioning areas of high and low contact risk, as well as the incorporation of human behavioural shifts dependent on an individual’s perceived risk of disease, adoption fatigue or inconsistent adoption. Despite the potential for facemasks to reduce SARS-CoV-2 transmission, there does not appear to be any focus on investing efforts in properly designed studies on facemasks, or evaluating large populations including ‘at risk’ patients and in a variety of communities. We argue that these are required urgently, and our modelling framework can readily be adapted to incorporate any new data that become available. In summary, our modelling analyses provide support for the immediate, universal adoption of facemasks by the public, similar to what has been done in Taiwan, for example, where production will soon reach 13 million facemasks daily, with well-developed plans for N95 rc .Sc A Soc. R. Proc. respirator production in the pipeline [68]. Our analyses indicate that actions to facilitate this in the UK should include clear instructions on the fabrication and safe use of home-made masks, as well as accompanying governmental policies to increase swiftly the availability of medical standard surgical, or N95 respirators, to the public. 476

Data accessibility. The code for models 1 and 2 is available at https://github.com/camepidem/COVID-19_ 20200376 : PRSA. Authors’ contributions. The original high-level question concerning the effectiveness of facemasks at population scales was proposed by J.C. and M.B. to C.A.G., R.O.J.H.S. and R.R. RR designed, implemented and analysed the branching process model while R.O.J.H.S. did so for the SECIR-DF compartmental model in discussion with C.A.G. J.C., C.A.G., R.O.J.H.S. and R.R. reviewed and discussed the results, and drafted the paper. M.B. reviewed the manuscript and gave technical inputs on mask designs. All authors reviewed and agreed the final form of the manuscript and agree to be held accountable for the work performed therein. Competing interests. We declare we have no competing interests. Funding. R.O.J.H.S., R.R. and C.A.G. acknowledge support from the Epidemiology and Modelling Group, Cambridge, UK. M.B. acknowledges support from the Wolfson Centre, University of Greenwich, UK. J.C. acknowledges support from the Natural Resources Institute, University of Greenwich, UK. Acknowledgements. We are grateful to Dr Sharon van Brunschot and Theodore Bradley for percipient suggestions for the draft article and Dr Fiona Hansell for consultation on medical terminology. We also thank the two reviewers for helpful comments. References 1. Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. 2020 The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat. Microbiol. 5, 536–544. (doi:10.1038/s41564-020-0695-z) 2. Chetty R, Stepner M, Abraham S, Lin S, Scuderi B, Turner N, Bergeron A, Cutler D. 2016 The association between income and life expectancy in the United States, 2001–2014. JAMA 315, 1750. (doi:10.1001/jama.2016.4226) 3. van Doremalen N et al. 2020 Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1. N. Engl. J. Med. 382, 1564–1567. (doi:10.1056/NEJMc2004973) 4. World Health Organization. 2020 Coronavirus disease 2019 (COVID-19). WHO situation report -73. See https://www.who.int/docs/default-source/coronaviruse/situation-reports/ 20200402-sitrep-73-covid-19.pdf. 5. Liu X, Zhang S. 2020 COVID-19: face masks and human-to-human transmission. Influenza Other Respir Viruses.Seehttp://doi.wiley.com/10.1111/irv.12740. 6. Noakes CJ, Beggs CB, Sleigh PA, Kerr KG. 2006 Modelling the transmission of airborne infections in enclosed spaces. Epidemiol. Infect. 134, 1082–1091. (doi:10.1017/ S0950268806005875) 7. Noakes CJ, Sleigh PA. 2009 Mathematical models for assessing the role of airflow on the risk of airborne infection in hospital wards. J. R Soc. Interface. 6, S791–S800. (doi:10.1098/rsif.2009.0305.focus) 8. Ferguson NM et al. 2020 Report 9: impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. See https://www.imperial.ac.uk/ media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19- 19 NPI-modelling-16-03-2020.pdf.

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Figure 1 (facing page). Findings from a Mouse Model of study. Future studies are needed to address these Electronic-Cigarette, or Vaping, Product Use–Associated issues. Our findings, coupled with previous re- Lung Injury (EVALI). search identifying vitamin E acetate in BAL fluid Panel A shows levels of vitamin E acetate (VEA) quanti- from patients with EVALI1,2 and in samples of fied by isotope-dilution mass spectrometry in broncho­ case-associated product liquids,5 provide addi- alveolar-lavage (BAL) fluid harvested from mice. Val- tional evidence for vitamin E acetate as a possi- ues are means and standard deviations for 10 mice. Panel B shows albumin levels measured in BAL fluid ble cause of EVALI. from mice exposed to air, a mixture of propylene glycol Tariq A. Bhat, Ph.D. and vegetable glycerin (PG–VG), or VEA. Values are Maciej L. Goniewicz, Ph.D., Pharm.D. means and standard deviations for 10 mice. Panel C Yasmin M. Thanavala, Ph.D. shows the total number of CD45+ cells infiltrating the Roswell Park Comprehensive Cancer Center lung in mice exposed to air, PG–VG, or VEA. Values Buffalo, NY are means and standard deviations for 10 mice. The yasmin​.­thanavala@​­roswellpark​.­org P values in Panels A, B, and C were calculated by two- way analysis of variance in Tukey’s post-test compari- and Others sons among the exposure groups. Panel D shows BAL Dr. Blount is a member of the Lung Injury Response Lab Task fluid from a mouse exposed to VEA, containing lipid- Force; additional members are listed in the Supplementary Ap- laden macrophages (representative examples are indi- pendix, available with the full text of this letter at NEJM.org. A complete list of authors is available with the full text of this cated with arrows) with cytoplasmic staining by oil red letter at NEJM.org. O in a vesicular pattern. The macrophages are numer- The views and opinions expressed in this letter are those of ous and contain variable amounts of lipid. Background the authors and do not necessarily represent the official position pneumocytes (arrowheads) show comparatively scant of the Centers for Disease Control and Prevention, the National cytoplasm and are present as single cells or loose sheets. Institutes of Health, or the Food and Drug Administration. Panel E shows BAL fluid from a mouse exposed to PG– Supported by grants from the National Heart, Lung, and Blood VG, which contained fewer identifiable macrophages Institute of the National Institutes of Health (R01HL142511), and had minimal to no specific staining by oil red O. the National Cancer Institute (NCI) (P30CA016056), and the Without lipid staining, it is more difficult to distinguish NCI and the Center for Tobacco Products of the Food and Drug Administration (U54CA228110). between small alveolar macrophages and pneumocytes Disclosure forms provided by the authors are available with in these preparations. Panels F and G show findings in the full text of this letter at NEJM.org. lung sections. In mice exposed to VEA (Panel F), alveo- lar macrophages (arrowheads and circles) in residence This letter was published on February 26, 2020, at NEJM.org. among pneumocytes (P) lining the alveoli (A) contained 1. Blount BC, Karwowski MP, Morel-Espinosa M, et al. Evalua- abundant oil red O–stained lipid. In mice exposed to tion of bronchoalveolar lavage fluid from patients in an out- PG–VG, tiny oil red O–stained granules in the cyto- break of e-cigarette, or vaping, product use–associated lung in- plasm of cells lining the alveoli, including pneumocytes jury — 10 states, August–October 2019. MMWR Morb Mortal (arrows) and alveolar macrophages (arrowheads), were Wkly Rep 2019;​68:​1040-1. observed. B denotes bronchiole. 2. Blount BC, Karwowski MP, Shields PG, et al. Vitamin E acetate in bronchoalveolar-lavage fluid associated with EVALI. N Engl J Med 2020;​382:​697-705. 3. Layden JE, Ghinai I, Pray I, et al. Pulmonary illness related the generated aerosols would be required to to e-cigarette use in Illinois and Wisconsin — preliminary re- identify such by-products. Another limitation is port. N Engl J Med. DOI: ​10.1056/NEJMoa1911614. that we did not expose animals to aerosols that 4. Maddock SD, Cirulis MM, Callahan SJ, et al. Pulmonary lipid-laden macrophages and vaping. N Engl J Med 2019;​381:​ contained tetrahydrocannabinol (THC) or nico- 1488-9. tine in a dose-dependent manner. Finally, it is 5. Krishnasamy VP, Hallowell BD, Ko JY, et al. Update: charac- possible that aerosols generated from other lipo- teristics of a nationwide outbreak of e-cigarette, or vaping, prod- uct use–associated lung injury — United States, August 2019– philic solvents may produce outcomes similar to January 2020. MMWR Morb Mortal Wkly Rep 2020;​69:​90-4. the outcome seen with vitamin E acetate in this DOI: 10.1056/NEJMc2000231

SARS-CoV-2 Viral Load in Upper Respiratory Specimens of Infected Patients

To the Editor: The 2019 novel coronavirus ternational concern by the World Health Organi- (SARS-CoV-2) epidemic, which was first reported zation, may progress to a pandemic associated in December 2019 in Wuhan, China, and has with substantial morbidity and mortality. SARS- been declared a public health emergency of in- CoV-2 is genetically related to SARS-CoV, which

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A Nasal Swabs Figure 1. Viral Load Detected in Nasal and Throat 15 Patient Swabs ­Obtained from Patients Infected with SARS-CoV-2. B N C O Panel A shows cycle threshold (Ct) values of Orf1b on 20 D P reverse-transcriptase–polymerase-chain-reaction (RT-PCR) E Q assay that were detected in nasal swabs obtained from 25 F S 14 patients with imported cases and 3 patients with H T secondary cases, and Panel B shows the Ct values in 30 throat swabs. Patient Z did not have clinical symptoms

Ct Value I X K and is not included in the figure. Patients with import- 35 L ed cases who had severe illness (Patients E, I, and P) are labeled in red, patients with imported cases who 40 had mild-to-moderate illness are labeled in black, and 0 3 6 9 12 15 18 21 patients with secondary cases (Patients D, H, and L) are labeled in blue. A linear mixed-effects model was Days since Onset of Symptoms used to test the Ct values from nasal and throat swabs among severe as compared with mild-to-moderate im- B Throat Swabs ported cases, which allowed for within-patient correla- Patient 15 B N tion and a time trend of Ct change. The mean Ct values C O in nasal and throat swabs obtained from patients with 20 D P severe cases were lower by 2.8 (95% confidence inter- E Q val [CI], −2.4 to 8.0) and 2.5 (95% CI, −0.8 to 5.7), re- 25 F S spectively, than the values in swabs obtained from pa- H T tients with mild-to-moderate cases. Panel C shows the 30 aggregated Ct values of Orf1b on RT-PCR assay in 14

Ct Value I W K X patients with imported cases and 3 patients with sec- 35 L ondary cases, according to day after symptom onset. Ct values are inversely related to viral RNA copy num- 40 ber, with Ct values of 30.76, 27.67, 24.56, and 21.48 cor- 4 5 6 7 0 3 6 9 12 15 18 21 responding to 1.5×10 , 1.5×10 , 1.5×10 , and 1.5×10 copies per milliliter. Negative samples are denoted Days since Onset of Symptoms with a Ct of 40, which was the limit of detection.

C Aggregated Ct Values 15 median age, 59 years; range, 26 to 76) in Zhuhai, Throat swabs Guangdong, China, including 4 patients with 20 Nasal swabs secondary infections (1 of whom never had

25 symptoms) within two family clusters (Table S1 in the Supplementary Appendix, available with 30 the full text of this letter at NEJM.org). The pa- Ct Value tient who never had symptoms was a close con- 35 tact of a patient with a known case and was 40 therefore monitored. A total of 72 nasal swabs (sampled from the mid-turbinate and nasophar- 0 3 6 9 12 15 18 21 ynx) (Fig. 1A) and 72 throat swabs (Fig. 1B) were Days since Onset of Symptoms analyzed, with 1 to 9 sequential samples ob- tained from each patient. Polyester flock swabs caused a global epidemic with 8096 confirmed were used for all the patients. cases in more than 25 countries in 2002–2003.1 From January 7 through January 26, 2020, a The epidemic of SARS-CoV was successfully con- total of 14 patients who had recently returned tained through public health interventions, in- from Wuhan and had fever (≥37.3°C) received a cluding case detection and isolation. Transmis- diagnosis of Covid-19 (the illness caused by sion of SARS-CoV occurred mainly after days of SARS-CoV-2) by means of reverse-transcriptase– illness2 and was associated with modest viral polymerase-chain-reaction assay with primers loads in the respiratory tract early in the illness, and probes targeting the N and Orf1b genes of with viral loads peaking approximately 10 days SARS-CoV-2; the assay was developed by the after symptom onset.3 We monitored SARS- Chinese Center for Disease Control and Preven- CoV-2 viral loads in upper respiratory specimens tion. Samples were tested at the Guangdong obtained from 18 patients (9 men and 9 women; Provincial Center for Disease Control and Pre-

n engl j med 382;12 nejm.org March 19, 2020 The New England Journal of Medicine Downloaded from nejm.org on June 24, 2020. For personal use only. No other uses without permission. Copyright © 2020 Massachusetts Medical Society. All rights reserved. Correspondence vention. Thirteen of 14 patients with imported determine transmission dynamics and inform cases had evidence of pneumonia on computed our screening practices. tomography (CT). None of them had visited the Lirong Zou, M.Sc. Huanan Seafood Wholesale Market in Wuhan Guangdong Provincial Center for Disease Control and Prevention within 14 days before symptom onset. Patients Guangzhou, China Feng Ruan, M.Med. E, I, and P required admission to intensive care Zhuhai Center for Disease Control and Prevention units, whereas the others had mild-to-moderate Zhuhai, China illness. Secondary infections were detected in Mingxing Huang, Ph.D. close contacts of Patients E, I, and P. Patient E Fifth Affiliated Hospital of Sun Yat-Sen University worked in Wuhan and visited his wife (Patient Zhuhai, China L), mother (Patient D), and a friend (Patient Z) in Lijun Liang, Ph.D. Guangdong Provincial Center for Disease Control and Prevention Zhuhai on January 17. Symptoms developed in Guangzhou, China Patients L and D on January 20 and January 22, Huitao Huang, B.Sc. respectively, with viral RNA detected in their Zhuhai Center for Disease Control and Prevention nasal and throat swabs soon after symptom on- Zhuhai, China set. Patient Z reported no clinical symptoms, but Zhongsi Hong, M.D. his nasal swabs (cycle threshold [Ct] values, 22 Fifth Affiliated Hospital of Sun Yat-Sen University Zhuhai, China to 28) and throat swabs (Ct values, 30 to 32) Jianxiang Yu, B.Sc. tested positive on days 7, 10, and 11 after con- Min Kang, M.Sc. tact. A CT scan of Patient Z that was obtained on Yingchao Song, B.Sc. February 6 was unremarkable. Patients I and P Guangdong Provincial Center for Disease Control and Prevention lived in Wuhan and visited their daughter (Pa- Guangzhou, China tient H) in Zhuhai on January 11 when their Jinyu Xia, M.D. symptoms first developed. Fever developed in Fifth Affiliated Hospital of Sun Yat-Sen University Zhuhai, China Patient H on January 17, with viral RNA detected Qianfang Guo, M.Sc. in nasal and throat swabs on day 1 after symp- Tie Song, M.Sc. tom onset. Jianfeng He, B.Sc. We analyzed the viral load in nasal and throat Guangdong Provincial Center for Disease Control and Prevention swabs obtained from the 17 symptomatic pa- Guangzhou, China tients in relation to day of onset of any symp- Hui-Ling Yen, Ph.D. toms (Fig. 1C). Higher viral loads (inversely re- Malik Peiris, Ph.D. lated to Ct value) were detected soon after University of Hong Kong symptom onset, with higher viral loads detected Hong Kong, China Jie Wu, Ph.D. in the nose than in the throat. Our analysis sug- Guangdong Provincial Center for Disease Control and Prevention gests that the viral nucleic acid shedding pattern Guangzhou, China of patients infected with SARS-CoV-2 resembles [email protected] that of patients with influenza4 and appears dif- Ms. Zou, Mr. Ruan, and Dr. Huang contributed equally to this letter. ferent from that seen in patients infected with Disclosure forms provided by the authors are available with SARS-CoV.3 The viral load that was detected in the full text of this letter at NEJM.org. the asymptomatic patient was similar to that in This letter was published on February 19, 2020, and updated on the symptomatic patients, which suggests the February 20, 2020, at NEJM.org. transmission potential of asymptomatic or min- 1. Summary of probable SARS cases with onset of illness from 1 November 2002 to 31 July 2003. Geneva: ​World Health Organi- imally symptomatic patients. These findings are zation, 2004 (https://www​.who​.int/​csr/​sars/​country/​table2004_04 in concordance with reports that transmission _21/​en/​). may occur early in the course of infection5 and 2. Lipsitch M, Cohen T, Cooper B, et al. Transmission dynam- ics and control of severe acute respiratory syndrome. Science suggest that case detection and isolation may 2003;300:​ 1966-70.​ require strategies different from those required 3. Peiris JSM, Chu CM, Cheng VCC, et al. Clinical progression for the control of SARS-CoV. How SARS-CoV-2 and viral load in a community outbreak of coronavirus-associated SARS pneumonia: a prospective study. Lancet 2003;​361:​1767-72. viral load correlates with culturable virus needs 4. Tsang TK, Cowling BJ, Fang VJ, et al. Influenza A virus shed- to be determined. Identification of patients with ding and infectivity in households. J Infect Dis 2015;​212:​1420-8. few or no symptoms and with modest levels of 5. Rothe C, Schunk M, Sothmann P, et al. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. detectable viral RNA in the oropharynx for at N Engl J Med 2020;​382:​970-1. least 5 days suggests that we need better data to DOI: 10.1056/NEJMc2001737

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Correspondence

Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany

To the Editor: The novel coronavirus (2019- tive for 2019-nCoV on January 26 (index patient nCoV) from Wuhan is currently causing concern in Fig. 1) (see Supplementary Appendix, available in the medical community as the virus is spread- at NEJM.org, for details on the timeline of symp- ing around the world.1 Since identification of the tom development leading to hospitalization). virus in late December 2019, the number of cases On January 27, she informed the company from China that have been imported into other about her illness. Contact tracing was started, countries is on the rise, and the epidemiologic and the above-mentioned colleague was sent to picture is changing on a daily basis. We are re- the Division of Infectious Diseases and Tropical porting a case of 2019-nCoV infection acquired Medicine in Munich for further assessment. At outside Asia in which transmission appears to presentation, he was afebrile and well. He re- have occurred during the incubation period in ported no previous or chronic illnesses and had the index patient. no history of foreign travel within 14 days before A 33-year-old otherwise healthy German busi- the onset of symptoms. Two nasopharyngeal nessman (Patient 1) became ill with a sore throat, swabs and one sputum sample were obtained chills, and myalgias on January 24, 2020. The and were found to be positive for 2019-nCoV on following day, a fever of 39.1°C (102.4°F) devel- quantitative reverse-transcriptase–polymerase- oped, along with a productive cough. By the chain-reaction (qRT-PCR) assay.2 Follow-up qRT- evening of the next day, he started feeling better PCR assay revealed a high viral load of 108 copies and went back to work on January 27. per milliliter in his sputum during the following Before the onset of symptoms, he had attended days, with the last available result on January 29. meetings with a Chinese business partner at his On January 28, three additional employees at company near Munich on January 20 and 21. the company tested positive for 2019-nCoV (Pa- The business partner, a Shanghai resident, had tients 2 through 4 in Fig. 1). Of these patients, visited Germany between January 19 and 22. only Patient 2 had contact with the index patient; During her stay, she had been well with no signs the other two patients had contact only with or symptoms of infection but had become ill on Patient 1. In accordance with the health au- her flight back to China, where she tested posi- thorities, all the patients with confirmed 2019- nCoV infection were admitted to a Munich infec- this week's letters tious diseases unit for clinical monitoring and 970 Transmission of 2019-nCoV Infection from an isolation. So far, none of the four confirmed Asymptomatic Contact in Germany patients show signs of severe clinical illness. This case of 2019-nCoV infection was diag- 972 Dapagliflozin in Patients with Heart Failure and nosed in Germany and transmitted outside Asia. Reduced Ejection Fraction However, it is notable that the infection appears to have been transmitted during the incubation 974 A Smartwatch to Identify Atrial Fibrillation period of the index patient, in whom the illness 976 Focused Cardiac Ultrasonography for Left was brief and nonspecific.3 Ventricular Systolic Function The fact that asymptomatic persons are po- tential sources of 2019-nCoV infection may war-

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C Contact with Patient 1

Flight to China Visit to Germany Symptoms Index Patient Attended business meetings Positive PCR Positive PCR Attended business Symptoms Patient 1 meetings Positive PCR Attended business Symptoms Patient 2 meetings Positive PCR Symptoms Patient 3 C C Positive PCR Symptoms Patient 4 C C C C

Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Jan. 19 20 21 22 23 24 25 26 27 28 29 Date

Figure 1. Timeline of Exposure to Index Patient with Asymptomatic 2019-CoV Infection in Germany. rant a reassessment of transmission dynamics of Wolfgang Guggemos, M.D. the current outbreak. In this context, the detec- Michael Seilmaier, M.D. tion of 2019-nCoV and a high sputum viral load Klinikum Mü nchen-Schwabing in a convalescent patient (Patient 1) arouse con- Munich, Germany cern about prolonged shedding of 2019-nCoV Christian Drosten, M.D. after recovery. Yet, the viability of 2019-nCoV Charité Universitätsmedizin Berlin detected on qRT-PCR in this patient remains to Berlin, Germany be proved by means of viral culture. Patrick Vollmar, M.D. Despite these concerns, all four patients who Katrin Zwirglmaier, Ph.D. were seen in Munich have had mild cases and Sabine Zange, M.D. were hospitalized primarily for public health Roman Wölfel, M.D. purposes. Since hospital capacities are limited Bundeswehr Institute of Microbiology — in particular, given the concurrent peak of Munich, Germany the influenza season in the northern hemi- Michael Hoelscher, M.D., Ph.D. sphere — research is needed to determine University Hospital LMU Munich whether such patients can be treated with ap- Munich, Germany propriate guidance and oversight outside the Disclosure forms provided by the authors are available with the full text of this letter at NEJM.org. hospital. Camilla Rothe, M.D. This letter was published on January 30, 2020, and updated on Mirjam Schunk, M.D. February 6, 2020, at NEJM.org.

Peter Sothmann, M.D. 1 . Zhu N, Zhang D, Wang W, et al. A novel coronavirus from Gisela Bretzel, M.D. patients with pneumonia in China, 2019. N Engl J Med 2020; 382: Guenter Froeschl, M.D. 727-33. 2 . Corman V, Bleicker T, Brünink S, et al. Diagnostic detec- Claudia Wallrauch, M.D. tion of Wuhan coronavirus 2019 by real-time RT-PCR. Geneva: Thorbjörn Zimmer, M.D. World Health Organization, January 13, 2020 (https://www Verena Thiel, M.D. . who . int/ docs/ default - source/ coronaviruse/ wuhan - virus - assay - v1991527e5122341d99287a1b17c111902 . pdf). Christian Janke, M.D. 3 . Callaway E, Cyranoski D. China coronavirus: six questions University Hospital LMU Munich scientists are asking. Nature 2020; 577: 605-7. Munich, Germany [email protected] DOI: 10.1056/NEJMc2001468

n engl j med 382;10 nejm.org March 5, 2020 The New England Journal of Medicine Downloaded from nejm.org on June 24, 2020. For personal use only. No other uses without permission. Copyright © 2020 Massachusetts Medical Society. All rights reserved. Infectious Disease Modelling 5 (2020) 293e308

Contents lists available at ScienceDirect

Infectious Disease Modelling

journal homepage: www.keaipublishing.com/idm

To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic

Steffen E. Eikenberry, Marina Mancuso, Enahoro Iboi, Tin Phan, * Keenan Eikenberry, Yang Kuang, Eric Kostelich, Abba B. Gumel

School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, 85287, USA article info abstract

Article history: Face mask use by the general public for limiting the spread of the COVID-19 pandemic is Received 6 April 2020 controversial, though increasingly recommended, and the potential of this intervention is Accepted 16 April 2020 not well understood. We develop a compartmental model for assessing the community- Available online 21 April 2020 wide impact of mask use by the general, asymptomatic public, a portion of which may be asymptomatically infectious. Model simulations, using data relevant to COVID-19 dy- Keywords: namics in the US states of New York and Washington, suggest that broad adoption of even Face mask relatively ineffective face masks may meaningfully reduce community transmission of Non-pharmaceutical intervention Cloth mask COVID-19 and decrease peak hospitalizations and deaths. Moreover, mask use decreases N95 respirator the effective transmission rate in nearly linear proportion to the product of mask effec- Surgical mask tiveness (as a fraction of potentially infectious contacts blocked) and coverage rate (as a SARS-CoV-2 fraction of the general population), while the impact on epidemiologic outcomes (death, COVID-19 hospitalizations) is highly nonlinear, indicating masks could synergize with other non- pharmaceutical measures. Notably, masks are found to be useful with respect to both preventing illness in healthy persons and preventing asymptomatic transmission. Hypo- thetical mask adoption scenarios, for Washington and New York state, suggest that im- mediate near universal (80%) adoption of moderately (50%) effective masks could prevent on the order of 17e45% of projected deaths over two months in New York, while decreasing the peak daily death rate by 34e58%, absent other changes in epidemic dy- namics. Even very weak masks (20% effective) can still be useful if the underlying trans- mission rate is relatively low or decreasing: In Washington, where baseline transmission is much less intense, 80% adoption of such masks could reduce mortality by 24e65% (and peak deaths 15e69%), compared to 2e9% mortality reduction in New York (peak death reduction 9e18%). Our results suggest use of face masks by the general public is potentially of high value in curtailing community transmission and the burden of the pandemic. The community-wide benefits are likely to be greatest when face masks are used in conjunction with other non-pharmaceutical practices (such as social-distancing), and when adoption is nearly universal (nation-wide) and compliance is high. © 2020 The Authors. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).

* Corresponding author. E-mail address: [email protected] (A.B. Gumel). Peer review under responsibility of KeAi Communications Co., Ltd. https://doi.org/10.1016/j.idm.2020.04.001 2468-0427/© 2020 The Authors. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). 294 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308

1. Introduction

Under the ongoing COVID-19 pandemic (caused by the SARS-CoV-2 coronavirus), recommendations and common prac- tices regarding face mask use by the general public have varied greatly and are in rapid flux: Mask use by the public in public spaces has been controversial in the US, although as of April 3, 2020, the US Centers for Disease Control and Prevention (CDC) is recommending the public wear cloth masks. Public mask use is far more prevalent in many Asian countries, which have longer experience with novel coronavirus epidemics; public mask use may have been effective at limiting community spread during the 2003 SARS epidemic (Lau, Tsui, Lau, & Yang, 2004; Wu et al., 2004), and widespread mask use is a prominent feature of the relatively successful COVID-19 response in Taiwan (Wang, Ng, & Brook, 2020), for example. Masks have also been suggested as a method for limiting community transmission by asymptomatic or at least clinically undetected carriers (Chan & Yuen, 2020), who may be a major driver of transmission of COVID-19 (Li et al., 2020). Various experimental studies suggest that masks may both protect the wearer from acquiring various infections (Davies et al., 2013; Lai, Poon, & Cheung, 2012) or transmitting infection (Dharmadhikari et al., 2012). Medical masks (i.e., surgical masks and N95 respirators) in healthcare workers appear to consistently protect against respiratory infection under metanalysis (MacIntyre et al., 2017; Offeddu, Yung, Low, & Tam, 2017), although clinical trials in the community have yielded more mixed results (Canini et al., 2010; Cowling et al., 2009; MacIntyre et al., 2009). While medical-grade masks should be prioritized for healthcare providers, homemade cloth masks may still afford significant, although variable and generally lesser, protection (Davies et al., 2013; van der Sande, Teunis, & Sabel, 2008), but clinical trials in the community remain lacking. Given the flux in recommendations, and uncertainty surrounding the possible community-wide impact of mass face masks (especially homemade cloth masks) on COVID-19 transmission, we have developed a multi-group Kermack-McKen- drick-type compartmental mathematical model, extending prior work geared towards modeling the COVID-19 pandemic (e.g. Ferguson et al., 2020; Li et al., 2020; Tracht, Del Valle, & Hyman, 2010), as well as models previously used to examine masks in a potential influenza pandemic (Brienen, Timen, Wallinga, Van Steenbergen, & Teunis, 2010; Tracht et al., 2010). This initial framework suggests that masks could be effective even if implemented as a singular intervention/mitigation strategy, but especially in combination with other non-pharmaceutical interventions that decrease community transmission rates. Whether masks can be useful, even in principle, depends on the mechanisms for transmission for SARS-CoV-2, which are likely a combination of droplet, contact, and possible airborne (aerosol) modes. The traditional model for respiratory disease transmission posits infection via infectious droplets (generally 5e10 mm) that have a short lifetime in the air and infect the upper respiratory tract, or finer aerosols, which may remain in the air for many hours (Leung et al.,2020 ), with ongoing uncertainties in the relative importance of these modes (and in the conceptual model itself Bourouiba, 2020) for SARS-CoV-2 transmission (Bourouiba, 2020; Han, Lin, Ni, & You, 2020). The WHO (World Health Organization, 2020, p. 27) has stated that SARS-CoV-2 transmission is primarily via coarse respiratory droplets and contact routes. An experimental study (van Doremalen et al., 2020) using a nebulizer found SARS-CoV-2 to remain viable in aerosols ( < 5 mm) for 3 h (the study dura- tion), but the clinical relevance of this setup is debatable (World Health Organization, 2020, p. 27). One out of three symp- tomatic COVID-19 patients caused extensive environmental contamination in (Ong et al., 2020), including of air exhaust outlets, though the air itself tested negative. Face masks can protect against both coarser droplet and finer aerosol transmission, though N95 respirators are more effective against finer aerosols, and may be superior in preventing droplet transmission as well (MacIntyre et al., 2017). Metanalysis of studies in healthy healthcare providers (in whom most studies have been performed) indicated a strong protective value against clinical and respiratory virus infection for both surgical masks and N95 respirators (Offeddu et al., 2017). Case control data from the 2003 SARS epidemic suggests a strong protective value to mask use by community members in public spaces, on the order of 70% (Lau et al., 2004; Wu et al., 2004). Experimental studies in both humans and manikins indicate that a range of masks provide at least some protective value against various infectious agents (Davies et al., 2013; Driessche et al., 2015; Stockwell et al., 2018; van der Sande et al., 2008; Leung et al.,2020 ). Medical masks were potentially highly effective as both source control and primary prevention under tidally breathing and coughing conditions in manikin studies (Lai et al., 2012; Patel, Skaria, Mansour, & Smaldone, 2016), with higher quality masks (e.g. N95 respirator vs. surgical mask) offering greater protection (Patel et al., 2016). It is largely un- known to what degree homemade masks (typically made from cotton, teacloth, or other polyesther fibers) may protect against droplets/aerosols and viral transmission, but experimental results by Davies et al. 7 suggest that while the homemade masks were less effective than surgical masks, they were still markedly superior to no mask. A clinical trial in healthcare workers (MacIntyre et al., 2015) showed relatively poor performance for cloth masks relative to medical masks. Mathematical modeling has been influential in providing deeper understanding on the transmission mechanisms and burden of the ongoing COVID-19 pandemic, contributing to the development of public health policy and understanding. Most mathematical models of the COVID-19 pandemic can broadly be divided into either population-based, SIR (Kermack- McKendrick)-type models, driven by (potentially stochastic) differential equations (Li et al., 2020; Tang et al., 2020; Wu, Leung, & Leung, 2020; Kucharski et al., 2020; Calafiore, Novara, & Possieri, 2020; Simha, Prasad, & Narayana, 2020; Dehning et al., 2020; Nesteruk, 2020; Zhang et al., 2020; Anastassopoulou, Russo, Tsakris, & Siettos, 2020; Moore & Okyere, 2004), or agent-based models (Biswas, Khaleque, & Sen, 2020; Chang, Harding, Zachreson, Cliff, & Prokopenko, 2020; Ferguson et al., 2020; Ruiz Estrada & Koutronas, 2020; Wilder et al., 2020), in which individuals typically interact on a network structure and exchange infection stochastically. One difficulty of the latter approach is that the network structure is time-varying and can be difficult, if not impossible, to construct with accuracy. Population-based models, alternatively, may S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 295 risk being too coarse to capture certain real-world complexities. Many of these models, of course, incorporate features from both paradigms, and the right combination of dynamical, stochastic, data-driven, and network-based methods will always depend on the question of interest. In Li et al. (2020) imposed a metapopulation structure onto an SEIR-model to account for travel between major cities in China. Notably, they include compartments for both documented and undocumented infections. Their model suggests that as many as 86% of all cases went undetected in Wuhan before travel restrictions took effect on January 23, 2020. They addi- tionally estimated that, on a per person basis, asymptomatic individuals were only 55% as contagious, yet were responsible for 79% of new infections, given their increased prevalence. The importance of accounting for asymptomatic individuals has been confirmed by other studies (Calafiore et al., 2020; Ferguson et al., 2020; Moriarty, 2020; Verity et al., 2020). In their model- based assessment of case-fatality ratios, Verity et al. (2020) estimated that 40e50% of cases went unidentified in China, as of February 8, 2020, while in the case of the Princess Diamond cruise ship, 46.5% of individuals who tested positive for COVID-19 were asymptomatic (Moriarty, 2020). Further, Calafiore et al. (2020), using a modified SIR-model, estimated that, on average, cases in Italy went underreported by a factor of 63, as of March 30, 2020. Several prior mathematical models, motivated by the potential for pandemic influenza, have examined the utility of mask wearing by the general public. These include a relatively simple modification of an SIR-type model by Brienen et al. (2010), while Tracht et al. (2010) considered a more complex SEIR model that explicitly disaggregated those that do and do not use masks. The latter concluded that, for pandemic H1N1 influenza, modestly effective masks (20%) could halve total infections, while if masks were just 50% effective as source control, the epidemic could be essentially eliminated if just 25% of the population wore masks. We adapt these previously developed SEIR model frameworks for transmission dynamics to explore the potential community-wide impact of public use of face masks, of varying efficacy and compliance, on the transmission dynamics and control of the COVID-19 pandemic. In particular, we develop a two-group model, which stratifies the total population into those who habitually do and do not wear face masks in public or other settings where transmission may occur. This model takes the form of a deterministic system of nonlinear differential equations, and explicitly includes asymptomatically- infectious humans. We examine mask effectiveness and coverage (i.e., the fraction of the population that habitually wears masks) as our two primary parameters of interest. We explore possible nonlinearities in mask coverage and effectiveness and the interaction of these two parameters; we find that the product of mask effectiveness and coverage level strongly predicts the effect of mask use on epidemiologic outcomes. Thus, homemade cloth masks are best deployed en masse to benefit the population at large. There is also a potentially strong nonlinear effect of mask use on the epidemiologic outcomes of cumulative death and peak hospitalizations. We note a possible temporal effect: Delaying mass mask adoption too long may undermine its efficacy. Moreover, we perform simulated case studies using mortality data for New York and Washington state. These case studies likewise suggest a beneficial role to mass adoption of even poorly effective masks, with the relative benefit likely greater in Washington state, where baseline transmission is less intense. The absolute potential for saving lives is still, however, greater under the more intense transmission dynamics in New York state. Thus, early adoption of masks is useful regardless of transmission in- tensities, and should not be delayed even if the case load/mortality seems relatively low. In summary, the benefit to routine face mask use by the general public during the COVID-19 pandemic remains uncertain, but our initial mathematical modeling work suggests a possible strong potential benefit to near universal adoption of even weakly effective homemade masks that may synergize with, not replace, other control and mitigation measures.

2. Methods

2.1. Baseline mathematical models

2.1.1. Model with no mask use We consider a baseline model without any mask use to form the foundation for parameter estimation and to estimate transmission rates in New York and Washington state; we also use this model to determine the equivalent transmission rate reductions resulting from public mask use in the full model. We use a deterministic susceptible, exposed, symptomatic infectious, hospitalized, asymptomatic infectious, and recov- ered modeling framework, with these classes respectively denoted SðtÞ, EðtÞ, IðtÞ, HðtÞ, AðtÞ, and RðtÞ; we also include DðtÞ to track cumulative deaths. We assume that some fraction of symptomatic infectious individuals progress to the hospitalized class, HðtÞ, where they are unable to pass the disease to the general public; we suppose that some fraction of hospitalized patients ultimately require critical care (and may die) (Zhou et al., 2020), but do not explicitly disaggregate, for example, ICU and non-ICU patients. Based on these assumptions and simplifications, the basic model for the transmission dynamics of COVID-19 is given by the following deterministic system of nonlinear differential equations:

dS S ¼bðtÞðI þ hAÞ ; (1) dt N 296 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308

dE S ¼ bðtÞðI þ hAÞ sE; (2) dt N

dI ¼ asE 4I g I; (3) dt I

dA ¼ð1 aÞsE g A; (4) dt A

dH ¼ 4I dH g H; (5) dt H

dR ¼ g I þ g A þ g H; (6) dt I A H

dD ¼ dH; (7) dt where

N ¼ S þ E þ I þ A þ R; (8) is the total population in the community, and bðtÞ is the baseline infectious contact rate, which is assumed to vary with time in general, but typically taken fixed. Additionally, h accounts for the relative infectiousness of asymptomatic carriers (in comparison to symptomatic carriers), s is the transition rate from the exposed to infectious class (so 1=s is the disease in- cubation period), a is the fraction of cases that are symptomatic, 4 is the rate at which symptomatic individuals are hospi- d talized, is the disease-induced death rate, and gA, gI and gH are recovery rates for the subscripted population. We suppose hospitalized persons are not exposed to the general population. Thus, they are excluded from the tabulation of N, and do not contribute to infection rates in the general community. This general modeling framework is similar to a variety of SEIR-style models recently employed in (Ferguson et al., 2020; Li et al., 2020), for example. ð Þ≡ For most results in this paper, we set b t b0. However, given ongoing responses to the COVID-19 pandemic in terms of voluntary and mandated social distancing, etc., we also consider the possibility that b varies with time and adopt the following functional form from Tang et al. (Tang et al., 2020), with the modification that contact rates do not begin declining from the initial contact rate, b0, until time t0: ; < ð Þ¼ b0 t t0 b t þð Þ ð ð ÞÞ; (9) bmin b0 bmin exp r t t0 t t0 where bmin is the minimum contact rate and r is the rate at which contact decreases.

2.2. Baseline epidemiological parameters

The incubation period for COVID-19 is estimated to average 5.1 days (Lauer et al., 2020), similar to other model-based estimates (Li et al., 2020), giving s ¼ 1=5:1 day 1. Some previous model-based estimates of infectious duration are on the order of several days (Ferguson et al., 2020; Li et al., 2020; Tang et al., 2020), with (Tang et al., 2020) giving about 7 days for asymptomatic individuals to recover. However, the clinical course of the disease is typically much longer: In a study of hospitalized patients (Zhou et al., 2020), average total duration of illness until hospital discharge or death was 21 days, and moreover, the median duration of viral shedding was 20 days in survivors. 1 The effective transmission rate, b0 (as a constant), ranges from around 0.5 to 1.5 day in prior modeling studies (Li et al., 2020; Read, Bridgen, Cummings, Ho, & Jewell, 2020; Shen, Peng, Xiao, & Zhang, 2020), and typically trends down with time (Li et al., 2020; Tang et al., 2020). We have left this as a free parameter in our fits to Washington and New York state mortality fi z : z : 1 data, and nd b0 0 5 and b0 1 4 day for these states, respectively, which is consistent with the cited range. The relative infectiousness of asymptomatic carriers, h, is not known, although Ferguson et al. (Ferguson et al., 2020) estimated this parameter at about 0.5, and Li et al. (Li et al., 2020) gave values of 0.42e0.55. The fraction of cases that are symptomatic, a, is also uncertain, with Li et al. 5 suggesting an overall case reporting rate of just 14% early in the outbreak in China, but increasing to 65e69% later; further, a ¼ 2=3 was used in (Ferguson et al., 2020). In the case of the Diamond Princess Cruise ship 43, 712 (19.2%) passengers and crews tested positive for SARS-CoV-2, with 331 (46.5%) asymptomatic at the time of testing. Therefore, we choose a ¼ 0:5 as our default. Given an average time from symptom onset to dyspnea of 7 days in 44, 9 days to sepsis, and a range of 1e10 days to hospitalization, a midpoint of 5 days seems reasonable (see also 15); 4z0:025 day 1 is consistent with on the order of 5e15% S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 297 of symptomatic patients being hospitalized. If about 15% of hospitalized patients die (Ferguson et al., 2020), then dz 0:015 1 ¼ = 1 day (based on gH 1 14 day ).

2.2.1. Model with general population mask use We assume that some fraction of the general population wears masks with uniform inward efficiency (i.e., primary ε fi protection against catching disease) of i, and outward ef ciency (i.e., source control/protection against transmitting disease) of εo. We disaggregate all population variables into those that typically do and do not wear masks, respectively subscripted with U and M. Based on the above assumptions and simplifications, the extended multi-group model for COVID-19 (where members of the general public wear masks in public) is given by:

dS S S U ¼bðI þ hA Þ U bðð1 ε ÞI þð1 ε ÞhA Þ U; (10) dt U U N o M o M N dE S S U ¼ bðI þ hA Þ U þ bðð1 ε ÞI þð1 ε ÞhA Þ U sE ; (11) dt U U N o M o M N U dI U ¼ asE 4I g I ; (12) dt U U I U dA U ¼ ð1 aÞsE g A ; (13) dt U A U dH U ¼ 4I dH g H ; (14) dt U U H U dR U ¼ g I þ g A þ g H ; (15) dt I U A U H U dD U ¼ dH ; (16) dt U dS S S M ¼bð1 ε ÞðI þ hA Þ M bð1 ε Þðð1 ε ÞI þð1 ε ÞhA Þ M; (17) dt i U U N i o M o M N dE S S M ¼ bð1 ε ÞðI þ hA Þ M þ bð1 ε Þðð1 ε ÞI þð1 ε ÞhA Þ M sE ; (18) dt i U U N i o M o M N M dI M ¼ asE 4I g I ; (19) dt M M I M dA M ¼ð1 aÞsE g A ; (20) dt M A M dH M ¼ 4I dH g H ; (21) dt M M H M dR M ¼ g I þ g A þ g H ; (22) dt I M A M H M dD M ¼ dH ; (23) dt M where

N ¼ SU þ EU þ IU þ AU þ RU þ SM þ EM þ IM þ AM þ RM: (25)

While much more complex than the baseline model, most of the complexity lies in what are essentially bookkeeping terms. We also consider a reduced version of the above model (equations not shown), such that only symptomatically infected persons wear a mask, to compare the consequences of the common recommendation that only those experiencing symptoms (and their immediate caretakers) wear masks with more general population coverage.

2.3. Mask efficiency parameters

We assume a roughly linear relationship between the overall filtering efficiency of a mask and clinical efficiency in terms of fi ε fi ε fi either inward ef ciency (i.e., effect on i) or outward ef ciency ( o), based on Brienen et al. (2010). The t factor for homemade masks averaged 2 in Davies et al. (2013), while the fit factor averaged 5 for surgical masks. When volunteers coughed into a 298 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 mask, depending upon sampling method, the number of colony-forming units resulting varied from 17% to 50% for home- made masks and 0e30% for surgical masks, relative to no mask (Davies et al., 2013). Surgical masks reduced P. aeruginosa infected aerosols produced by coughing by over 80% in cystic fibrosis patients in Driessche et al. (2015), while surgical masks reduced CFU count by > 90% in a similar study (Stockwell et al., 2018). N95 masks were more effective in both studies. Homemade teacloth masks had an inward efficiency between (58) and 77% over 3 h of wear in van der Sande et al. (2008), while inward efficiency ranged 72e85% and 98e99% for surgical and N95-equivalent masks. Outward efficiency was marginal for teacloth masks, and about 50e70% for medical masks. Surgical masks worn by tuberculosis patients also reduced the infectiousness of hospital ward air in Dharmadhikari et al. (2012), and Leung et al. (2020) very recently observed surgical masks to decrease infectious aerosol produced by individuals with seasonal coro- naviruses. Manikin studies seem to recommend masks as especially valuable under coughing conditions for both source control (Patel et al., 2016) and prevention (Lai et al., 2012). We therefore estimate that inward mask efficiency could range widely, anywhere from 20 to 80% for cloth masks, with 50% possibly more typical (and higher values are possible for well-made, tightly fitting masks made of optimal materials), 70e90% typical for surgical masks, and > 95% typical for properly worn N95 masks. Outward mask efficiency could range from practically zero to over 80% for homemade masks, with 50% perhaps typical, while surgical masks and N95 masks are likely 50e90% and 70e100% outwardly protective, respectively.

2.4. Data and model fitting

We use state-level time series for cumulative mortality data compiled by the Center for Systems Science and Engineering at Johns Hopkins University (2020), from January 22, 2020, through April 2, 2020, to calibrate the model initial conditions and ð Þ fi infective contact rate, b0,aswellasbmin when b t is taken as an explicit function of time. Other parameters are xed at default values in Table 1. Parameter fitting was performed using a nonlinear least squares algorithm implemented using the lsqnonlin function in MATLAB. We consider two US states in particular as case studies, New York and Washington, and total population data for each state was defined according to US Census data for July 1, 2019 (US Census).

3. Results

3.1. Analytic results

Closed-form expressions for the basic reproduction number, R 0, for the baseline model without masks and the full model ð Þ≡ with masks are given, for b t b0,inAppendix A and B, respectively.

3.2. Masks coverage/efficacy/time to adoption in simulated epidemics

3.2.1. Mask/efficacy interaction under immediate adoption ¼ 1 We run simulated epidemics using either b0 0.5 or 1.5 day , with other parameters set to the defaults given in Table 1. These parameter sets give epidemic doubling times early in time (in terms of cumulative cases and deaths) of approximately seven or three days, respectively, corresponding to case and mortality doubling times observed (early in time) in Washington and New York state, respectively. We use as initial conditions a normalized population of 1 million persons, all of whom are initially susceptible, except 50 initially symptomatically infected (i.e., 5 out 100,000 is the initial infection rate), not wearing masks. We choose some fraction of the population to be initially in the masked class (’‘mask coverage’‘), which we also denote p, ε ¼ ε ¼ ε and assume o i . The epidemic is allowed to run its course (18 simulated months) under constant conditions, and the outcomes of interest are peak hospitalization, cumulative deaths, and total recovered. These results are normalized against the counterfactual of no mask coverage, and results are presented as heat maps in Fig. 1.

Table 1 Baseline model parameters with brief description, likely ranges based on modeling and clinical studies (see text for further details), and default value chosen for this study.

Parameter Likely range (references) Default value b (infectious contact rate) 0.5e1.5 day-1 (Li et al., 2020; Read et al., 2020; Shen et al., 2020), this work 0.5 day 1 s (transition exposed to infectious) 1/14e1/3 day-1 (Lauer et al., 2020; Li et al., 2020) 1/5.1 day 1 h (infectiousness factor for asymptomatic carriers) 0.4e0.6 (Ferguson et al., 2020; Li et al., 2020) 0.5 a (fraction of infections that become symptomatic) 0.15e0.7 (Ferguson et al., 2020; Li et al., 2020; Moriarty, 2020; Verity et al., 2020) 0.5 4 (rate of hospitalization) 0.02e0.1 (Ferguson et al., 2020; Zhou et al., 2020) 0.025 day 1 e -1 1 gA (recovery rate, Asymptomatic) 1/14 1/3 day (Tang et al., 2020; Zhou et al., 2020) 1/7 day e -1 1 gI (recovery rate, symptomatic) 1/30 1/3 day (Tang et al., 2020; Zhou et al., 2020) 1/7 day e -1 1 gH (recovery rate, hospitalized) 1/30 1/3 day (Tang et al., 2020; Zhou et al., 2020) 1/14 day d (death rate, hospitalized) 0.001e0.1 (Ferguson et al., 2020) 0.015 day 1 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 299

¼ 1 Fig. 1. Relative peak hospitalizations and cumulative mortality under simulated epidemics, under either a base b0 0.5 or 1.5 day , under different general fi ε ¼ ε ¼ ε fi mask coverage levels and ef cacies (where o i ). Results are relative to a base case with no mask use. The left half of the gure gives these metrics as two- dimensional functions of coverage and efficacy. The right half gives these metrics as one-dimensional functions of coverage efficacy.

Note that the product ε p predicts quite well the effect of mask deployment: Fig. 1 also shows (relative) peak hospi- talizations and cumulative deaths as functions of this product. There is, however, a slight asymmetry between coverage and efficacy, such that increasing coverage of moderately effective masks is generally more useful than increasing the effec- tiveness of masks from a starting point of moderate coverage.

3.2.2. Delayed adoption We run the simulated epidemics described, supposing the entire population is unmasked until mass mask adoption after some discrete delay. The level of adoption is also fixed as a constant. We find that a small delay in mask adoption (without any changes in b) has little effect on peak hospitalized fraction or cumulative deaths, but the ‘‘point of no return’’ can rapidly be crossed, if mask adoption is delayed until near the time at which the epidemic otherwise crests. This general pattern holds regardless of b0, but the point of no return is further in the future for smaller b0.

3.3. Mask use and equivalent b reduction

The relationship between mask coverage, efficacy, and metrics of epidemic severity considered above are highly nonlinear. The relationship between b0 (the infectious contact rate) and such metrics is similarly nonlinear. However, incremental re- ductions in b0, due to social distancing measures, etc., can ultimately synergize with other reductions to yield a meaningful effect on the epidemic. Therefore, we numerically determine what the equivalent change in b0 under the baseline would have fi ~ been under mask use at different coverage/ef cacy levels, and we denote the equivalent b0 value as b0. fi fi That is, we numerically simulate an epidemic with and without masks, with a xed b0. Then, we t the baseline model to ~ fi ~ this (simulated) case data, yielding a new equivalent b0, b0. An excellent t giving b0 can almost always be obtained, though fi fi occasionally results are extremely sensitive to b0 for high mask coverage/ef cacy, yielding somewhat poorer ts. Results are ~ b ~ summarized in Fig. 2, where the b0 values obtained and the relative changes in equivalent (i.e., (b0)/(b0)) are plotted as fi ε functions of ef cacy times coverage, p, under simulated epidemics with three baseline (true) b0 values. From Fig. 2, we see that even 50% coverage with 50% effective masks roughly halves the effective disease transmission rate. Widespread adoption, say 80% coverage, of masks that are only 20% effective still reduces the effective transmission rate by about one-third.

3.4. Outward vs. inward efficiency

Fig. 3 demonstrates the effect of mask coverage on peak hospitalizations, cumulative deaths, and equivalent b0 values ε ¼ : ε ¼ : ¼ 1 when either o 0 2 and i 0 8, or visa versa (and for simulated epidemics using either b0 0.5 or 1.5 day ). These results ε suggest that, all else equal, the protection masks afford against acquiring infection ( i) is actually slightly more important than protection against transmitting infection (εo), although there is overall little meaningful asymmetry. 300 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308

~ Fig. 2. Equivalent b , b (infectious contact rate) under baseline model dynamics as a function of mask coverage efficacy, with the left panel giving the absolute 0 0 ~ value, and the right giving the ratio of b0 to the true b0 in the simulation with masks. That is, simulated epidemics are run with mask coverage and effectiveness fi ranging from 0 to 1, and the outcomes are tracked as synthetic data. The baseline model without mask dynamics is then t to this synthetic data, with b0 the ~ 1 trainable parameter; the resulting b0 is the b0. This is done for simulated epidemics with a true b0 of 1.5, 1, or 0.5 day .

ε ¼ : Fig. 3. Epidemiologic outcomes and equivalent b0 changes as a function of mask coverage when masks are either much better at blocking outgoing ( o 0 8, ε ¼ : ε ¼ : ε ¼ : ¼ i 0 2) or incoming ( 0 0 2, i 0 8) transmission. Results are demonstrated for both mask permutations under simulated epidemics with baseline b0 0.5 or 1.5 day 1.

3.5. Masks for symptomatic alone vs. general population

Finally, we consider numerical experiments where masks are given to all symptomatically infected persons, whether they otherwise habitually wear masks or not (i.e., both IU and IM actually wear masks). We explore how universal mask use in εI symptomatically infected persons interacts with mask coverage among the general population; we let o represent the S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 301 effectiveness of masks in the symptomatic, not necessarily equal to εo. We again run simulated epidemics with no masks, or with universal masks among the symptomatic, and then compare different levels of mask coverage in the general (asymp- tomatic) population in addition to universal masks for the symptomatic. In this section, we use equivalent b0 as our primary metric. Fig. 4 shows how this metric varies as a function of the mask effectiveness given to symptomatic persons, along with the coverage and effectiveness of masks worn by the general public. We also explore how conclusions vary when either 25%, 50%, or 75% of infectious COVID-19 patients are asymptomatic (i.e., we vary a). Unsurprisingly, the greater the proportion of infected people that are asymptomatic, the more benefit there is to giving the general public masks in addition to those experiencing symptoms.

3.6. Simulated case studies: New York & Washington states

Fitting to cumulative death data for New York and Washington states, we use the baseline model to determine the best fi ð Þ xed b0 and I 0 . We use New York state data beginning on March 1, 2020, through April 2, 2020, and Washington state data fi ð Þ¼ e from February 20, 2020 through April 2, 2020. For New York state, best- t parameters are I 0 208 (range 154 264) and b0 ¼ e 1 fi ð Þ fi ¼ : 1 ¼ fi 1.40 (1.35 1.46) day under xed b0. For the time-varying b t ,we x r 0 03 day and t0 20, yielding a best- t b0 ¼ e 1 ¼ e 1 ð Þ¼ e 1.33 (1.24 1.42) day , bmin 0.51 ( 0.25 1.26) day , and I 0 293 (191 394). ð Þ¼ e ¼ e 1 fi For Washington state, parameters are I 0 622 (571 673) and b0 0.50 (0.49 0.52) day under xed b0. For time- ð Þ fi ¼ : 1 ¼ fi ¼ e 1 ¼ e 1 varying b t ,we x r 0 04 day and t0 0, to yield a best- t b0 1.0 (0.87 1.23) day , bmin 0.10 (0 0.19) day , and Ið0Þ¼238 (177e300). fi We x r and t0, as it is not possible to uniquely identify r, t0 and bmin from death or case data alone (see, e.g., Roda, Varughese, Han, & Li, 2020 on identifiability problems). Fig. 5 gives cumulative death and case data versus the model pre- dictions for the two states, and for the two choices of bðtÞ. Note that while modeled and actual cumulative deaths match well, model-predicted cases markedly exceed reported cases in the data, consistent with the notion of broad underreporting. fi ð Þ We then consider either xed b0 or time-varying b t , according to the parameters above, in combination with the following purely hypothetical scenarios in each state.

ð Þ≡ fi ð Þ 1. No masks, epidemic runs its course unaltered with either b t b0 xed or b t variable as described above. 2. The two b scenarios are considered in combination with: weak, moderate, or strong deployment of masks, such that p ¼ 0.2, 0.5, or 0.8; and weak, moderate, or strong masks, such that ε ¼ 0.2, 0.5, or 0.8. No masks are used up until April 2, 2020, and then these coverage levels are instantaneously imposed.

This yields 18 scenarios in all (nine mask coverage/efficacy scenarios, plus two underlying trends). Following the modeled imposition of masks on April 2, 2020, the scenarios are run for 60 additional simulated days. Figs. 6 and 8 summarize the

Fig. 4. Equivalent b0 under the model where all symptomatic persons wear a mask (whether they otherwise habitually wear a mask or not), under varying levels fi εI of ef cacy for the masks given to the symptomatic ( o), and in combination with different degrees of coverage and effectiveness for masks used by the rest of the 1 general public. Results are for simulated epidemics with a baseline b0 of 1.5 day . 302 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308

Fig. 5. The left half of the figure gives model predictions and data for Washington state, using either a constant (top panels) or variable b (bottom panel), as described in the text. The right half of the figure is similar, but for New York state.

Fig. 6. Simulated future (cumulative) death tolls for Washington state, using either a fixed (top panels) or variable (bottom panels) transmission rate, b, and nine different permutations of general public mask coverage and effectiveness. The y-axes are scaled differently in top and bottom panels. S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 303

Fig. 7. Simulated future daily death rates for Washington state, using either a fixed (top panels) or variable (bottom panels) transmission rate, b, and nine different permutations of general public mask coverage and effectiveness. The y-axes are scaled differently in top and bottom panels.

future modeled death toll in each city under the 18 different scenarios, along with historical mortality data. Figs. 7 and 9 show modeled daily death rates, with deaths peaking sometime in late April in New York state under all scenarios, while deaths could peak anywhere from mid-April to later than May, for Washington state. We emphasize that these are hypothetical and exploratory results, with possible death tolls varying dramatically based upon the future course of bðtÞ. However, the results do suggest that even modestly effective masks, if widely used, could help ‘‘bend the curve,’’ with the relative benefit greater in ð Þ combination with a lower baseline b0 or stronger underlying trend towards smaller b t (i.e., in Washington vs. New York).

4. Discussion & conclusions

There is considerable ongoing debate on whether to recommend general public face mask use (likely mostly homemade cloth masks or other improvised face coverings) 4, and while the situation is in flux, more authorities are recommending public mask use, though they continue to (rightly) cite appreciable uncertainty. With this study, we hope to help inform this debate by providing insight into the potential community-wide impact of widespread face mask use by members of the general population. We have designed a mathematical model, parameterized using data relevant to COVID-19 transmission dynamics in two US states (New York and Washington), and our model suggests nontrivial and possibly quite strong benefits to general face mask use. The population-level benefit is greater the earlier masks are adopted, and at least some benefitis realized across a range of epidemic intensities. Moreover, even if they have, as a sole intervention, little influence on epidemic outcomes, face masks decrease the equivalent effective transmission rate (b0 in our model), and thus can stack with other interventions, including social distancing and hygienic measures especially, to ultimately drive nonlinear decreases in epidemic mortality and healthcare system burden. It bears repeating that our model results are consistent with the idea that face masks, while no panacea, may synergize with other non-pharmaceutical control measures and should be used in combination with and not in lieu of these. Under simulated epidemics, the effectiveness of face masks in altering the epidemiologic outcomes of peak hospitalization and total deaths is a highly nonlinear function of both mask efficacy and coverage in the population (see Fig. 1), with the product of mask efficacy and coverage a good one-dimensional surrogate for the effect. We have determined how mask use in ~ fi ~ the full model alters the equivalent b0, denoted b0, in the baseline model (without masks), nding this equivalent b0 to vary nearly linearly with efficacy coverage (Fig. 2). Masks alone, unless they are highly effective and nearly universal, may have only a small effect (but still nontrivial, in terms of absolute lives saved) in more severe epidemics, such as the ongoing epidemic in New York state. However, the fi relative bene t to general mask use may increase with other decreases in b0, such that masks can synergize with other public health measures. Thus, it is important that masks not be viewed as an alternative, but as a complement, to other public health 304 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 control measures (including non-pharmaceutical interventions, such as social distancing, self-isolation etc.). Delaying mask adoption is also detrimental. These factors together indicate that even in areas or states where the COVID-19 burden is low (e.g. the Dakotas), early aggressive action that includes face masks may pay dividends. These general conclusions are illustrated by our simulated case studies, in which we have tuned the infectious contact rate, b fi ð Þ (either as xed b0 or time-varying b t ), to cumulative mortality data for Washington and New York state through April 2, 2020, and imposed hypothetical mask adoption scenarios. The estimated range for b is much smaller in Washington state, consistent with this state’s much slower epidemic growth rate and doubling time. Model fitting also suggests that total symptomatic cases may be dramatically undercounted in both areas, consistent with prior conclusions on the pandemic (Li et al., 2020). Simulated futures for both states suggest that broad adoption of even weak masks could help avoid many deaths, but the greatest relative death reductions are generally seen when the underlying transmission rate also falls or is low at baseline. fi Considering a xed transmission rate, b0, 80% adoption of 20%, 50%, and 80% effective masks reduces cumulative relative (absolute) mortality by 1.8% (4,419), 17% (41,317), and 55% (134,920), respectively, in New York state. In Washington state, relative (absolute) mortality reductions are dramatic, amounting to 65% (22,262), 91% (31,157), and 95% (32,529). When bðtÞ varies with time, New York deaths reductions are 9% (21,315), 45% (103,860), and 74% (172,460), while figures for Washington are 24% (410), 41% (684), and 48% (799). In the latter case, the epidemic peaks soon even without masks. Thus, a range of outcomes are possible, but both the absolute and relative benefit to weak masks can be quite large; when the relative benefit is small, the absolute benefit in terms of lives is still highly nontrivial. Most of our model projected mortality numbers for New York and Washington state are quite high (except for variable bðtÞ in Washington), and likely represent worst-case scenarios, as they primarily reflect b values early in time. Thus, they may be dramatic overestimates, depending upon these states’ populations ongoing responses to the COVID-19 epidemics. Never- theless, the estimated transmission values for the two states, under fixed and variable bðtÞ, represent a broad range of possible transmission dynamics and are within the range estimated in prior studies (Li et al., 2020; Read et al., 2020; Shen et al., 2020), and so we may have some confidence in our general conclusions on the possible range of benefits to masks. Note also that we have restricted our parameter estimation only to initial conditions and transmission parameters, owing to identifiability problems with more complex models and larger parameter groups (see e.g. Roda, Varughese, Han, & Li, 2020). For example, d the same death data may be consistent with either a large b0 and low (death rate), or visa versa. Considering the subproblem of general public mask use in addition to mask use for source control by any (known) symptomatic person, we find that general face mask use is still highly beneficial (see Fig. 4). Unsurprisingly, this benefitis greater if a larger proportion of infected people are asymptomatic (i.e., a in the model is smaller). Moreover, it is not the case that masks are helpful exclusively when worn by asymptomatic infectious persons for source control, but provide benefit when worn by (genuinely) healthy people for prevention as well. Indeed, if there is any asymmetry in outward vs. inward mask effectiveness, inward effectiveness is actually slightly preferred, although the direction of this asymmetry matters little with respect to overall epidemiologic outcomes. At least one experimental study (Patel et al., 2016) does suggest that masks may be superior at source control, especially under coughing conditions vs. normal tidal breathing and so any realized benefit of masks in the population may still be more attributable to source control. ε ε This is somewhat surprising, given that o appears more times than i in the model terms giving the forces of infection, which would suggest outward effectiveness to be of greater import at first glance. Our conclusion runs counter to the notion that general public masks are primarily useful in preventing asymptomatically wearers from transmitting disease: Masks are valuable as both source control and primary prevention. This may be important to emphasize, as some people who have self- isolated for prolonged periods may reasonably believe that the chance they are asymptomatically infected is very low and therefore do not need a mask if they venture into public, whereas our results indicate they (and the public at large) still stand to benefit. Our theoretical results still must be interpreted with caution, owing to a combination of potentially high rates of noncompliance with mask use in the community, uncertainty with respect to the intrinsic effectiveness of (especially homemade) masks at blocking respiratory droplets and/or aerosols, and even surprising amounts of uncertainty regarding the basic mechanisms for respiratory infection transmission (Bourouiba, 2020; MacIntyre et al., 2017). Several lines of evi- dence support the notion that masks can interfere with respiratory virus transmission, including clinical trials in healthcare workers (MacIntyre et al., 2017; Offeddu et al., 2017), experimental studies as reviewed in (Davies et al., 2013; Dharmadhikari et al., 2012; Lai et al., 2012; Patel et al., 2016; van der Sande et al., 2008), and case control data from the 2003 SARS epidemic (Lau et al., 2004; Wu et al., 2004). Given the demonstrated efficacy of medical masks in healthcare workers (Offeddu et al., 2017), and their likely superiority over cloth masks in MacIntyre et al. (2015), it is clearly essential that healthcare works be prioritized when it comes to the most effective medical mask supply. Fortunately, our theoretical results suggest significant (but potentially highly variable) value even to low quality masks when used widely in the community. With social distancing orders in place, essential service providers (such as retail workers, emergency services, law enforcement, etc.) represent a special category of concern, as they represent a largely unavoidable high contact node in transmission networks: Individual public-facing workers may come into contact with hundreds or thousands of people in the course of a day, in relatively close contact (e.g. cashiers). Such contact likely exposes the workers to many asymptomatic S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 305 carriers, and they may in turn, if asymptomatic, expose many susceptible members of the general public to potential transmission. Air exposed to multiple infectious persons (e.g. in grocery stores) could also carry a psuedo-steady load of infectious particles, for which masks would be the only plausible prophylactic (Lai et al., 2012). Thus, targeted, highly effective mask use by service workers may be reasonable. We are currently extending the basic model framework presented here to examine this hypothesis. In conclusion, our findings suggest that face mask use should be as nearly universal (i.e., nation-wide) as possible and implemented without delay, even if most masks are homemade and of relatively low quality. This measure could contribute greatly to controlling the COVID-19 pandemic, with the benefit greatest in conjunction with other non-pharmaceutical in- terventions that reduce community transmission. Despite uncertainty, the potential for benefit, the lack of obvious harm, and the precautionary principle lead us to strongly recommend as close to universal (homemade, unless medical masks can be used without diverting healthcare supply) mask use by the general public as possible.

Declaration of competing interest

None.

Acknowledgements

One of the authors (ABG) acknowledge the support, in part, of the Simons Foundation (Award #585022) and the National Science Foundation (Award 1917512).

Appendix A. Basic Reproduction Number for the Baseline Model

ð Þ≡ The basic reproduction number is calculated for the special case when b t b0. The local stability of the disease-free equilibrium (DFE) is explored using the next generation operator method (Diekmann, Heesterbeek, & Metz, 1990; van den Driessche & Watmough, 2002). Using the notation in (van den Driessche & Watmough, 2002), it follows that the matrices F of new infection terms and V of the remaining transfer terms associated with the baseline model are given, respectively, by 2 3 0 b0 b0h F ¼ 4 00 05; 00 0 2 3 s 00 V ¼ 4 s ð4 þ Þ 5: a gI 0 ð Þs 1 a 0 gA

The basic reproduction number of the model, denoted by R 0, is given by ð Þ R ¼ b0a þ b0h 1 a : 0 ð4 þ Þ (26) gI gA

Appendix B. Basic Reproduction Number for Full Model

The local stability of the DFE is explored using the next generation operator method (Diekmann et al., 1990; van den Driessche & Watmough, 2002). Using the notation in van den Driessche and Watmough (2002), it follows that the matrices F of new infection terms and V of the remaining transfer terms associated with the version of the model are given, respectively, by 306 S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308

2 3 ð Þ ð Þ ð Þ ð Þ SU 0 SU 0 ð ε Þ SU 0 ð ε Þ SU 0 6 0 b0 b0h 0 b0 1 o b0 1 o h 7 6 Nð0Þ Nð0Þ Nð0Þ Nð0Þ 7 6 7 6 7 6 00 0 0 0 0 7 6 7 6 7 6 00 0 0 0 0 7 F ¼ 6 7; 6 S ð0Þ S ð0Þ S ð0Þ S ð0Þ 7 6 0 b ð1 ε Þ M b ð1 ε Þh M 0 b ð1 ε Þð1 ε Þ M b ð1 ε Þð1 ε Þh M 7 6 0 i ð Þ 0 i ð Þ 0 o i ð Þ 0 o i ð Þ 7 6 N 0 N 0 N 0 N 0 7 6 7 4 00 0 0 0 0 5 00 0 0 0 0 2 3 s 00000 6 7 6 as ð4 þ g Þ 00 0 07 6 I 7 6 ð1 aÞs 0 g 0007 V ¼ 6 A 7 6 000s 007 4 s ð4 þ Þ 5 000a gI 0 ð Þs 0001 a 0 gA

The basic reproduction number of the model, denoted by R 0, is given by ð Þ ð Þ ð Þ R ¼ SU 0 þ SM 0 ð ε Þð ε Þ a þ h 1 a : 0 b0 ð Þ ð Þ 1 o 1 i 4 þ (27) N 0 N 0 gI gA

Fig. 8. Simulated future (cumulative) death tolls for New York state, using either a fixed (top panels) or variable (bottom panels) transmission rate, b, and nine different permutations of general public mask coverage and effectiveness. S.E. Eikenberry et al. / Infectious Disease Modelling 5 (2020) 293e308 307

Fig. 9. Simulated future daily death rates for New York state, using either a fixed (top panels) or variable (bottom panels) transmission rate, b, and nine different permutations of general public mask coverage and effectiveness.

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Rapid Expert Consultation on the Effectiveness of Fabric Masks for the COVID-19 Pandemic (April 8, 2020)

April 8, 2020

Kelvin Droegemeier, Ph.D. Office of Science and Technology Policy Executive Office of the President Eisenhower Executive Office Building 1650 Pennsylvania Avenue, NW Washington, DC 20504

Dear Dr. Droegemeier:

Attached please find a rapid expert consultation that was prepared by Rich Besser and Baruch Fischhoff, members of the National Academies of Sciences, Engineering, and Medicine’s Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats, with input from Sundaresan Jayaraman and Michael Osterholm. Details on the authors and reviewers of this rapid expert consultation can be found in the Appendix.

The aim of this rapid expert consultation is to respond to your request concerning the effectiveness of homemade fabric masks worn by the general public to protect others, as distinct from protecting the wearer. The request stems from an interest in reducing transmission within the community by individuals who are infected, potentially contagious, but asymptomatic. Overall, the available evidence is inconclusive about the degree to which homemade fabric masks may suppress the spread of infection from the wearer to others. For as long as homemade fabric masks are in use by the public, the investigations outlined at the end of the rapid expert consultation could reduce uncertainty about the effectiveness of these masks.

My colleagues and I hope this input is helpful to you as you continue to guide the nation’s response in this ongoing public health crisis.

Respectfully, Harvey V. Fineberg, M.D., Ph.D. Chair Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats

This rapid expert consultation responds to your request concerning the effectiveness of homemade fabric masks worn by the general public to protect others, as distinct from protecting

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Copyright National Academy of Sciences. All rights reserved. Rapid Expert Consultation on the Effectiveness of Fabric Masks for the COVID-19 Pandemic (April 8, 2020)

the wearer. The request stems from an interest in reducing transmission within the community by individuals who are infected, potentially contagious, but asymptomatic or presymptomatic. As discussed below, the answer depends on both the masks themselves and how infected individuals use them. The following analysis is restricted to the effectiveness of homemade fabric masks, of the sort illustrated in recommendations1 directed at the general public, in terms of their ability to reduce viral spread during the asymptomatic or presymptomatic period. It does not apply to either N95 respirators or medical masks.

In considering the evidence about the potential effectiveness of homemade fabric masks, it is important to bear in mind how a respiratory virus such as SARS-CoV-2 spreads from person to person. Current research supports the possibility that, in addition to being spread by respiratory droplets that one can see and feel, SARS-CoV-2 can also be spread by invisible droplets, as small as 5 microns (or micrometers), and by even smaller bioaerosol particles.2 Such tiny bioaerosol particles may be found in an infected person’s normal exhalation.3 The relative contribution of each particle size in disease transmission is unknown.

There is limited research on the efficacy of fabric masks for influenza and specifically for SARS- CoV-2. As we describe below, the few available experimental studies have important limitations in their relevance and methods. Any type of mask will have its own capacity to arrest particles of different sizes. Even if the filtering capacity of a mask were well understood, however, the degree to which it could in practice reduce disease spread depends on the unknown role of each particle size in transmission.

Asymptomatic but infected individuals are of special concern, and the particles they would emit from breathing are predominantly bioaerosols. To complicate matters further, different individuals vary in the extent to which they emit bioaerosols while breathing. Because of the concern with spread from asymptomatic individuals, who, unlike symptomatic persons, may be out and about, this rapid expert consultation includes the effects of fabric masks on bioaerosol transmission.

1 Centers for Disease Control and Prevention (CDC) Recommendation Regarding the Use of Cloth Face Coverings, Especially in Areas of Significant Community-Based Transmission in response to COVID-19. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/cloth-face-cover.html. 2 Gralton et al. (2011) noted the following in regard to particulate size and the importance of airborne precautions whenever there is a risk of both droplet and aerosol transmission: “Regardless of the complexities and limitations of sizing particles and the contention of size cut-offs, it remains that particles have been observed to occupy a size range between 0.05 and 500 microns. Even using the conservative cut-off of 10 microns, rather than the 5 micron to define between airborne and droplet transmission, this size range indicates that particles do not exclusively disperse by airborne transmission or via droplet transmission but rather avail of both methods simultaneously. This suggestion is further supported by the simultaneous detection of both large and small particles. In line with these observations and logic, current dichotomous infection control precautions should be updated to include measures to contain both modes of aerosolised transmission. This may require airborne precautions to be used when at risk of any aerosolized infection, as airborne precautions are considered as a step-up from droplet precautions.” Gralton et al. 2011. The role of particle size in aerosolised pathogen transmission: A review. Journal of Infection 62(1):1-13. DOI: 10.1016/j.jinf.2010.11.010. 3 National Academies of Sciences, Engineering, and Medicine. 2020. Rapid Expert Consultation on the Possibility of Bioaerosol Spread of SARS-CoV-2 for the COVID-19 Pandemic (April 1, 2020). Washington, DC: The National Academies Press. https://doi.org/10.17226/25769.

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IMPACT OF MASK DESIGN AND FABRICATION ON PERFORMANCE

Any effects of fabric masks will depend on how and how well they are made. In an unpublished study whose raw data are not currently available, Jayaraman et al.4 examined a range of fabric- based filtration systems, in terms of how well they stopped particles (filtration efficiency) and how much they impeded breathing (differential pressure, Delta-P, the measured pressure drop across the material, which determines the resistance of the material to air flow).5 The study varied fabric type (woven, woven brushed, knitted, knitted brushed, knitted pile), material type (cotton, polyester, polypropylene, silk), fabric parameters (fabric areal density, yarn linear density, fabric weight), and construction type (number of layers, orientation of the layers). The study found wide variation in filtration efficiency. A mask made from a four-layer woven handkerchief fabric, of a sort that might be found in many homes, had 0.7% filtration efficiency for 0.3 micron size particles and a Delta-P of 0.1”. Much higher filtration efficiency was observed with filters created specifically for the research from a five-layer woven brushed fabric (35.3% of the particles were trapped) and from four layers of polyester knitted cut-pile fabric (50% of the particles were trapped with a Delta-P of 0.2”).

The greater a mask’s breathing resistance, which is reflected in a higher Delta-P, the more difficult it is for users to wear it consistently, and the more likely they are to experience breathing difficulties when they do.6 Although Jayaraman et al. did not measure breathing resistance directly, almost all of the masks they tested would be expected to have breathing resistance within the range of commercial N95 respirators. One mask that used 16 layers of the handkerchief fabric, in order to increase filtration efficiency (63% efficiency with a Delta-P of 0.425”), had breathing resistance greater than that of commercial N95 respirators, which would cause great discomfort to many wearers and cause some to pass out.

An additional consideration in the effectiveness of any mask is how well it fits the user.7 Even with the best material, if a mask does not fit, virus-containing particles can escape through creases and gaps between the mask and face. Leakage can also occur if the holding mechanism (e.g., straps, Velcro®) is weak. We found no studies of non-expert individuals’ ability to produce properly fitting masks. Nor did we find any studies of the effectiveness of masks produced by professionals, when following instructions available to the general public (e.g., online). Given the current Centers for Disease Control and Prevention (CDC) recommendation to wear cloth face coverings in public settings in areas of significant community-based transmission, additional research should examine the ability of the general public to produce properly fitted fabric masks when following communications and instructions.

4 Jayaraman et al. Pandemic Flu—Textile Solutions Pilot: Design and Development of Innovative Medical Masks, Final Technical Report, Georgia Institute of Technology, Atlanta, Georgia, submitted to CDC, February 14, 2012. 5 The tests were conducted according to ASTM F2299-3 test method using poly-dispersed sodium chloride aerosol particles with an airflow rate of 30L/min and airflow velocity of 11 cm/s. Aerosol sizes measured: 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 1, and 2 microns. 6 3M™ Health Care Particulate Respirator and Surgical Masks, Healthcare Respirator Brochure, 3M Company, Minnesota. 7 Davies et al. (2013) noted that, “Although any material may provide a physical barrier to an infection, if as a mask it does not fit well around the nose and mouth, or the material freely allows infectious aerosols to pass through it, then it will be of no benefit.” Davies et al. 2013. Testing the efficacy of homemade masks: Would they protect in an influenza pandemic? Disaster Medicine and Public Health Preparedness 7(4):413-418. DOI: 10.1017/dmp.2013.43.

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Copyright National Academy of Sciences. All rights reserved. Rapid Expert Consultation on the Effectiveness of Fabric Masks for the COVID-19 Pandemic (April 8, 2020)

ROLE OF THE WEARER

The effectiveness of homemade fabric masks will also depend on the wearer’s behavior. Even if a mask could fit well, its effectiveness still depends on how well the wearer puts it on and keeps it in place. As mentioned, breathing difficulty can impede effective use (e.g., pulling a mask down), as can moisture from the wearer’s breath. Moisture saturation is inevitable with fabrics available in most homes. Moreover, moisture can trap the virus and become a potential contamination source for others after a mask is removed.

EFFECTIVENESS OF HOMEMADE FABRIC MASKS IN PROTECTING OTHERS

Several experimental studies have examined the effects of fabric masks on the transmission of droplets of various sizes.

Anfinrud et al.8 shared via email that they used sensitive laser light-scattering procedures to detect droplet emission while people were speaking. The authors found that “a damp homemade cloth facemask” reduced droplet emission to background levels (when users said “Stay Healthy” three times). However, when a fabric is dampened, the yarns can swell over time, potentially altering its filtering performance. That swelling will depend on the fabric: cotton swells readily, synthetics less so. In an unpublished follow-up experiment, Anfinrud et al. repeated their study with a variety of dry (not moistened) cloths, including a standard workers dust mask (not certified N95) and a mask rigged from an airline eye covering. They found that all of these masks reduced droplet emission generated by speech to background level.9

Bae et al. (2020) evaluated the effectiveness of surgical and cotton masks in filtering SARS- CoV-2.10 They found that neither kind of mask reduced the dissemination of SARS-CoV-2 from the coughs of four symptomatic patients with COVID-19 to the environment and external mask surface. The study used disposable surgical masks (180 mm × 90 mm, 3 layers [inner surface mixed with polypropylene and polyethylene, polypropylene filter, and polypropylene outer surface], pleated, bulk packaged in cardboard; KM Dental Mask, KM Healthcare Corp) and reusable 100% cotton masks (160 mm × 135 mm, 2 layers, individually packaged in plastic; Seoulsa). The median viral loads of nasopharyngeal and saliva samples from the four participants were 5.66 log copies/mL and 4.00 log copies/mL, respectively. The median viral loads after coughs without a mask, with a surgical mask, and with a cotton mask were similar: 2.56 log copies/mL, 2.42 log copies/mL, and 1.85 log copies/mL, respectively. All swabs from the outer mask surfaces of the masks were positive for SARS-CoV-2, whereas swabs from three out of the four symptomatic patients from the inner mask surfaces were negative. Note that this study focused on symptomatic patients who coughed.

8 Anfinrud et al. In Press. Could SARS-CoV-2 be transmitted via speech droplets? New England Journal of Medicine. https://doi.org/10.1101/2020.04.02.20051177. 9 Personal communication, Adriaan Bax, National Institutes of Health, April 4, 2020. 10 Bae et al. 2020. Effectiveness of surgical and cotton masks in blocking SARS-CoV-2: A controlled comparison in 4 patients. Annals of Internal Medicine. DOI: 10.7326/M20-1342.

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Copyright National Academy of Sciences. All rights reserved. Rapid Expert Consultation on the Effectiveness of Fabric Masks for the COVID-19 Pandemic (April 8, 2020)

Rengasamy et al. (2010)11 tested the filtration performance of five common household fabric materials: sweatshirts, T-shirts, towels, scarves, and cloth masks (of unknown material) in a laboratory setting. These fabric materials were tested for sprays having both similar and diverse particle sizes (monodisperse and polydisperse). The range of sizes used in the study (0.02-1 micron) includes that of potential virus-containing droplets.12 The study projected the particles at face velocities, typical of breathing at rest and during exertion (5.5 and 16.5 cm/s). The test also examined N95 respirator filter media. At the lower velocity, 0.12% of particles penetrated the N95 respirator material; at the higher velocity, penetration was less than 5%. For the five common household fabric materials, across the tests, penetration ranged from about 40-90%, indicating a 10-60% reduction. The authors concluded that common fabric materials may provide a low level of protection against nanoparticles, including those in the size ranges of virus-containing particles in exhaled breath (0.02-1 micron). However, Gralton et al. (2011) found particles generated from respiratory activities range from 0.01 up to 500 microns, with a particle size range of 0.05 to 500 microns associated with infection. They stress the need for airborne precautions to be used when at risk of any aerosolized infection, as airborne precautions are considered as a step-up from droplet precautions.

Davies et al. (2013)13 had 21 healthy volunteers make their own face masks from fresh, unworn cotton t-shirts. This is the only study we found with user-made masks. Participants then coughed into a box, when wearing their own mask, a surgical mask, or no mask. They received no help or guidance from the researcher in making or fitting their masks. The researchers took samples of particles settling onto agar plates and a Casella slit sampler in the box. Under the baseline conditions of no mask, only a small number of colony-forming units (indicative of bacteria) were detected, limiting the opportunity to demonstrate reductions. Still, the investigators reported that both homemade and surgical masks reduced the number of large-sized microorganisms expelled by volunteers, with the surgical mask being more effective.

van der Sande et al. (2008)14 examined the extent to which respirator masks, surgical masks, and tea-cloth masks made by the researchers would reduce tiny (0.02-1 micron) particle counts on one side of the mask compared to the other. They used burning candles in a test room to generate particles. Two of the study’s three experiments examined the protection afforded the wearer (reduced particle counts inside the masks compared to outside). Although not directly germane to the question of protecting others, the study found a modest degree of protection for the wearer from cloth masks, an intermediate degree from surgical masks, and a marked degree with the equivalent of N95 masks. For example, among adults, N95 masks provided 25 times the protection of surgical masks and 50 times the protection of cloth masks. The study’s third

11 Rengasamy et al. 2010. Simple respiratory protection—evaluation of the filtration performance of cloth masks and common fabric materials against 20-1000 nm size particles. Annals of Occupational Hygiene 54(7):789-798. https://doi.org/10.1093/annhyg/meq044. 12 According to Gralton et al. (2011), particles generated from respiratory activities range from 0.01 up to 500 microns, with a particle size range of 0.05 to 500 microns associated with infection. Gralton et al. 2011. The role of particle size in aerosolised pathogen transmission: A review. Journal of Infection 62:1-13. DOI: 10.1016/j.jinf.2010.11.010. 13 Davies et al. 2013. Testing the efficacy of homemade masks: Would they protect in an influenza pandemic? Disaster Medicine and Public Health Preparedness 7(4):413-418. DOI: 10.1017/dmp.2013.43. 14 van der Sande et al. 2008. Professional and home-made face masks reduce exposure to respiratory infections among the general population. PLOS ONE 3(7):e2618. DOI: 10.1371/journal.pone.0002618.

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Copyright National Academy of Sciences. All rights reserved. Rapid Expert Consultation on the Effectiveness of Fabric Masks for the COVID-19 Pandemic (April 8, 2020)

experiment tested the effectiveness of the three masks at reducing emissions from a simulation dummy head that produced uniform “exhalations.” It found that cloth masks reduced emitted particles (leakage) by one-fifth, surgical masks reduced it by one-half, and N95-equivalent masks reduced it by two-thirds.

MacIntyre et al. (2015)15 conducted a randomized controlled trial comparing infection rates of 1,607 hospital health care workers wearing cloth (two layers, made of cotton) or medical masks (three layers, made of non-woven material) while performing their normal tasks. Workers who used cloth masks experienced much higher rates of influenza-like illness (relative risk = 13.00, 95% confidence interval 1.59 to 100.07). This study measured the protective effect for the wearer, rather than the protection of others from the wearer, and did not include a condition with individuals wearing no masks.

EFFECT ON USERS’ RISK BEHAVIOR

In our rapid review, we found no studies of the effects of wearing masks on users’ behavior. Speculatively, for some users, masks could provide a constant reminder of the importance of social distancing, as well as signal its importance to others, strengthening the social norm of social distancing. Conversely, for some users, masks might “crowd out” other precautionary behaviors, giving them a feeling that they have done enough to protect themselves and others. Prior research, conducted in less intense settings, could support either speculation. Focused research could help determine when precautionary behaviors reinforce or displace one another.

It is critically important that any discussion of homemade fabric masks reinforce the central importance of physical distancing and personal hygiene (frequent handwashing) in reducing spread of infection.

CONCLUSIONS

There are no studies of individuals wearing homemade fabric masks in the course of their typical activities. Therefore, we have only limited, indirect evidence regarding the effectiveness of such masks for protecting others, when made and worn by the general public on a regular basis. That evidence comes primarily from laboratory studies testing the effectiveness of different materials at capturing particles of different sizes.

The evidence from these laboratory filtration studies suggests that such fabric masks may reduce the transmission of larger respiratory droplets. There is little evidence regarding the transmission of small aerosolized particulates of the size potentially exhaled by asymptomatic or presymptomatic individuals with COVID-19. The extent of any protection will depend on how the masks are made and used. It will also depend on how mask use affects users’ other precautionary behaviors, including their use of better masks, when those become widely available. Those behavioral effects may undermine or enhance homemade fabric masks’ overall effect on public health. The current level of benefit, if any, is not possible to assess.

15 MacIntyre et al. 2015. A cluster randomised trial of cloth masks compared with medical masks in healthcare workers. BMJ Open 5(4):e006577. DOI: 10.1136/bmjopen-2014-006577.

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Copyright National Academy of Sciences. All rights reserved. Rapid Expert Consultation on the Effectiveness of Fabric Masks for the COVID-19 Pandemic (April 8, 2020)

Research could provide firmer answers by assessing the effectiveness of such fabric masks, as made and used by the general public. That research would have the goals of providing the public with (1) usable instructions on how to make, fit, use, and clean homemade fabric masks; (2) estimates of the protection that such masks afford users and others in different environments (e.g., where the likelihood of contact is higher, like grocery stores, compared to wearing masks all of the time); and (3) effective reinforcement of other precautionary behaviors. That research could provide policy makers with estimates of the net effect of encouraging the use of homemade fabric masks on public health, with realistic estimates of how such masks will be made and used, as well as how they will affect other precautionary behaviors of users and others who observe and interact with them.

My colleagues and I hope this input is helpful to you as you continue to guide the nation’s response in this ongoing public health crisis.

Respectfully, Richard Besser, M.D. Member Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats

Baruch Fischhoff, Ph.D. Member Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats

APPENDIX

Authors and Reviewers of This Rapid Expert Consultation

This rapid expert consultation was prepared by staff of the National Academies of Sciences, Engineering, and Medicine, and members of the National Academies’ Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats: Richard Besser, Robert Wood Johnson Foundation, and Baruch Fischhoff, Carnegie Mellon University. The following subject- matter experts also provided input: Sundaresan Jayaraman, Georgia Tech, and Michael Osterholm, University of Minnesota.

Harvey Fineberg, chair of the Standing Committee, approved this document. The following individuals served as reviewers: Ned Calonge, The Colorado Trust; Robert Hornik, University of Pennsylvania; Thomas Inglesby, Johns Hopkins Bloomberg School of Public Health Center for Health Security; and Grace Lee, Stanford University. Bobbie A. Berkowitz, Columbia University School of Nursing; Ellen Wright Clayton, Vanderbilt University Medical Center; and Susan Curry, University of Iowa, served as arbiters of this review on behalf of the National Academies’ Report Review Committee and their Health and Medicine Division.

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Copyright National Academy of Sciences. All rights reserved. Brief Communication https://doi.org/10.1038/s41591-020-0843-2

Respiratory virus shedding in exhaled breath and efficacy of face masks

Nancy H. L. Leung 1, Daniel K. W. Chu1, Eunice Y. C. Shiu1, Kwok-Hung Chan2, James J. McDevitt3, Benien J. P. Hau1,4, Hui-Ling Yen 1, Yuguo Li5, Dennis K. M. Ip1, J. S. Malik Peiris1, Wing-Hong Seto1,6, Gabriel M. Leung1, Donald K. Milton7,8 and Benjamin J. Cowling 1,8 ✉

We identified seasonal human coronaviruses, influenza medically attended ARIs and determining the potential efficacy of viruses and rhinoviruses in exhaled breath and coughs of chil- surgical face masks to prevent respiratory virus transmission. dren and adults with acute respiratory illness. Surgical face masks significantly reduced detection of influenza virus RNA Results in respiratory droplets and coronavirus RNA in aerosols, with We screened 3,363 individuals in two study phases, ultimately a trend toward reduced detection of coronavirus RNA in respi- enrolling 246 individuals who provided exhaled breath samples ratory droplets. Our results indicate that surgical face masks (Extended Data Fig. 1). Among these 246 participants, 122 (50%) could prevent transmission of human coronaviruses and influ- participants were randomized to not wearing a face mask during enza viruses from symptomatic individuals. the first exhaled breath collection and 124 (50%) participants were Respiratory virus infections cause a broad and overlapping spec- randomized to wearing a face mask. Overall, 49 (20%) voluntarily trum of symptoms collectively referred to as acute respiratory virus provided a second exhaled breath collection of the alternate type. illnesses (ARIs) or more commonly the ‘common cold’. Although Infections by at least one respiratory virus were confirmed by mostly mild, these ARIs can sometimes cause severe disease and reverse transcription PCR (RT–PCR) in 123 of 246 (50%) partici- death1. These viruses spread between humans through direct or pants. Of these 123 participants, 111 (90%) were infected by human indirect contact, respiratory droplets (including larger droplets that (seasonal) coronavirus (n = 17), influenza virus (n = 43) or rhinovi- fall rapidly near the source as well as coarse aerosols with aerody- rus (n = 54) (Extended Data Figs. 1 and 2), including one participant namic diameter >5 µm) and fine-particle aerosols (droplets and co-infected by both coronavirus and influenza virus and another droplet nuclei with aerodynamic diameter ≤5 µm)2,3. Although two participants co-infected by both rhinovirus and influenza virus. hand hygiene and use of face masks, primarily targeting contact and These 111 participants were the focus of our analyses. respiratory droplet transmission, have been suggested as important There were some minor differences in characteristics of the 111 mitigation strategies against influenza virus transmission4, little is participants with the different viruses (Table 1a). Overall, 24% of known about the relative importance of these modes in the trans- participants had a measured fever ≥37.8 °C, with patients with influ- mission of other common respiratory viruses2,3,5. Uncertainties enza more than twice as likely than patients infected with coronavi- similarly apply to the modes of transmission of COVID-19 (refs. 6,7). rus and rhinovirus to have a measured fever. Coronavirus-infected Some health authorities recommend that masks be worn by participants coughed the most with an average of 17 (s.d. = 30) ill individuals to prevent onward transmission (source control)4,8. coughs during the 30-min exhaled breath collection. The profiles Surgical face masks were originally introduced to protect patients of the participants randomized to with-mask versus without-mask from wound infection and contamination from surgeons (the groups were similar (Supplementary Table 1). wearer) during surgical procedures, and were later adopted to We tested viral shedding (in terms of viral copies per sample) protect healthcare workers against acquiring infection from their in nasal swabs, throat swabs, respiratory droplet samples and aero- patients. However, most of the existing evidence on the filtering effi- sol samples and compared the latter two between samples collected cacy of face masks and respirators comes from in vitro experiments with or without a face mask (Fig. 1). On average, viral shedding was with nonbiological particles9,10, which may not be generalizable to higher in nasal swabs than in throat swabs for each of coronavi- infectious respiratory virus droplets. There is little information on rus (median 8.1 log10 virus copies per sample versus 3.9), influenza the efficacy of face masks in filtering respiratory viruses and reduc- virus (6.7 versus 4.0) and rhinovirus (6.8 versus 3.3), respectively. ing viral release from an individual with respiratory infections8, and Viral RNA was identified from respiratory droplets and aerosols most research has focused on influenza11,12. for all three viruses, including 30%, 26% and 28% of respiratory Here we aimed to explore the importance of respiratory droplet droplets and 40%, 35% and 56% of aerosols collected while not and aerosol routes of transmission with a particular focus on coro- wearing a face mask, from coronavirus, influenza virus and rhino- naviruses, influenza viruses and rhinoviruses, by quantifying the virus-infected participants, respectively (Table 1b). In particular for amount of respiratory virus in exhaled breath of participants with coronavirus, we identified OC43 and HKU1 from both respiratory

1WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China. 2Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China. 3Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA. 4Department of Surgery, Queen Mary Hospital, Hong Kong, China. 5Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China. 6Department of Pathology, Hong Kong Baptist Hospital, Hong Kong, China. 7Maryland Institute for Applied Environmental Health, School of Public Health, University of Maryland, College Park, MD, USA. 8These authors jointly supervised this work: Donald K. Milton, Benjamin J. Cowling. ✉e-mail: [email protected]

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Table 1a | Characteristics of individuals with symptomatic coronavirus, influenza virus or rhinovirus infection All who provided exhaled breath Coronavirus Infuenza virus Rhinovirus (n = 246) (n = 17) (n = 43) (n = 54) n (%) n (%) n (%) n (%) Female 144 (59) 13 (76) 22 (51) 30 (56) Age group, years 11–17 12 (5) 0 (0) 8 (19) 4 (7) 18–34 114 (46) 10 (59) 11 (26) 24 (44) 35–50 79 (32) 2 (12) 16 (37) 18 (33) 51–64 35 (14) 4 (24) 8 (19) 5 (9) ≥ 65 6 (2) 1 (6) 0 (0) 3 (6) Chronic medical conditions Any 49 (20) 5 (29) 5 (12) 10 (19) Respiratory 18 (7) 0 (0) 4 (9) 3 (6) Influenza vaccination Ever 94 (38) 6 (35) 15 (35) 20 (37) Current season 23 (9) 2 (12) 1 (2) 4 (7) Previous season only 71 (29) 4 (24) 14 (33) 16 (30) Ever smoker 31 (13) 1 (6) 6 (14) 6 (11) Time since illness onset, h <24 22 (9) 0 (0) 5 (12) 2 (4) 24–48 100 (41) 9 (53) 13 (30) 25 (46) 48–72 85 (35) 8 (47) 18 (42) 20 (37) 72–96 39 (16) 0 (0) 7 (16) 7 (13) History of measured fever ≥37.8 °C 58 (24) 3 (18) 17 (40) 8 (15) Measured fever ≥37.8 °C at presentation 36 (15) 2 (12) 18 (42) 2 (4) Measured body temperature (˚C) at enrollment 36.8 (0.8) 36.9 (0.8) 37.4 (0.9) 36.6 (0.7) (mean, s.d.) Symptoms at presentation Fever 111 (45) 10 (59) 27 (63) 16 (30) Cough 198 (80) 15 (88) 40 (93) 44 (81) Sore throat 211 (86) 15 (88) 31 (72) 49 (91) Runny nose 200 (81) 17 (100) 36 (84) 48 (89) Headache 186 (76) 13 (76) 30 (70) 38 (70) Myalgia 176 (72) 12 (71) 31 (72) 34 (63) Phlegm 176 (72) 9 (53) 34 (79) 41 (76) Chest tightness 64 (26) 3 (18) 12 (28) 9 (17) Shortness of breath 103 (42) 6 (35) 14 (33) 25 (46) Chills 100 (41) 8 (47) 29 (67) 16 (30) Sweating 95 (39) 5 (29) 18 (42) 20 (37) Fatigue 218 (89) 16 (94) 38 (88) 48 (89) Vomiting 19 (8) 2 (12) 5 (12) 2 (4) Diarrhea 17 (7) 2 (12) 1 (2) 6 (11) Number of coughs during exhaled breath collection 8 (14) 17 (30) 8 (11) 5 (9) (mean, s.d.)

Seasonal coronavirus (n = 17), seasonal influenza virus (n = 43) and rhinovirus (n = 54) infections were confirmed in individuals with acute respiratory symptoms by RT–PCR in any samples (nasal swab, throat swab, respiratory droplets and aerosols) collected. droplets and aerosols, but only identified NL63 from aerosols and masks, respectively, but did not detect any virus in respiratory drop- not from respiratory droplets (Supplementary Table 2 and Extended lets or aerosols collected from participants wearing face masks, this Data Fig. 3). difference was significant in aerosols and showed a trend toward We detected coronavirus in respiratory droplets and aerosols in 3 reduced detection in respiratory droplets (Table 1b). For influenza of 10 (30%) and 4 of 10 (40%) of the samples collected without face virus, we detected virus in 6 of 23 (26%) and 8 of 23 (35%) of the

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a Coronavirus 1010

P = 0.07 P = 0.02 108

106

104

2

Virus copies per sample 10

100

Nasal Throat Droplet Droplet Aerosol Aerosol swab swab particles >5 µm, particles >5 µm, particles ≤5 µm, particles ≤5 µm, without mask with mask without mask with mask Sample type

Influenza virus b 1010

P = 0.01 P = 0.26 108

106

104

2

Virus copies per sample 10

100

Nasal Throat Droplet Droplet Aerosol Aerosol swab swab particles >5 µm, particles >5 µm, particles ≤5 µm, particles ≤5 µm, without mask with mask without mask with mask Sample type

c Rhinovirus 1010

P = 0.44 P = 0.12 108

106

104

2

Virus copies per sample 10

100

Nasal Throat Droplet Droplet Aerosol Aerosol swab swab particles >5 µm, particles >5 µm, particles ≤5 µm, particles ≤5 µm, without mask with mask without mask with mask Sample type

Fig. 1 | Efficacy of surgical face masks in reducing respiratory virus shedding in respiratory droplets and aerosols of symptomatic individuals with coronavirus, influenza virus or rhinovirus infection. a–c, Virus copies per sample collected in nasal swab (red), throat swab (blue) and respiratory droplets collected for 30min while not wearing (dark green) or wearing (light green) a surgical face mask, and aerosols collected for 30min while not wearing (brown) or wearing (orange) a face mask, collected from individuals with acute respiratory symptoms who were positive for coronavirus (a), influenza virus (b) and rhinovirus (c), as determined by RT–PCR in any samples. P values for mask intervention as predictor of log10 virus copies per sample in an unadjusted univariate Tobit regression model which allowed for censoring at the lower limit of detection of the RT–PCR assay are shown, with significant differences in bold. For nasal swabs and throat swabs, all infected individuals were included (coronavirus, n=17; influenza virus, n=43; rhinovirus, n=54). For respiratory droplets and aerosols, numbers of infected individuals who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: coronavirus (n=10 and 11), influenza virus (n=23 and 28) and rhinovirus (n=36 and 32). A subset of participants provided exhaled breath samples for both mask interventions (coronavirus, n=4; influenza virus, n=8; rhinovirus, n=14). The box plots indicate the median with the interquartile range (lower and upper hinge) and ±1.5×interquartile range from the first and third quartile (lower and upper whiskers).

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Table 1b | Efficacy of surgical face masks in reducing respiratory virus frequency of detection and viral shedding in respiratory droplets and aerosols of symptomatic individuals with coronavirus, influenza virus or rhinovirus infection

Droplet particles >5 μm Aerosol particles ≤5 μm Virus type Without surgical face mask With surgical face mask P Without surgical face mask With surgical face mask P Detection of virus No. positive/no. total (%) No. positive/no. total (%) No. positive/no. total (%) No. positive/no. total (%) Coronavirus 3 of 10 (30) 0 of 11 (0) 0.09 4 of 10 (40) 0 of 11 (0) 0.04 Influenza virus 6 of 23 (26) 1 of 27 (4) 0.04 8 of 23 (35) 6 of 27 (22) 0.36 Rhinovirus 9 of 32 (28) 6 of 27 (22) 0.77 19 of 34 (56) 12 of 32 (38) 0.15

Viral load (log10 virus copies per sample) Median (IQR) Median (IQR) Median (IQR) Median (IQR) Coronavirus 0.3 (0.3, 1.2) 0.3 (0.3, 0.3) 0.07 0.3 (0.3, 3.3) 0.3 (0.3, 0.3) 0.02 Influenza virus 0.3 (0.3, 1.1) 0.3 (0.3, 0.3) 0.01 0.3 (0.3, 3.0) 0.3 (0.3, 0.3) 0.26 Rhinovirus 0.3 (0.3, 1.3) 0.3 (0.3, 0.3) 0.44 1.8 (0.3, 2.8) 0.3 (0.3, 2.4) 0.12

P values for comparing the frequency of respiratory virus detection between the mask intervention were obtained by two-sided Fisher’s exact test and (two-sided) P values for mask intervention as

predictor of log10 virus copies per sample were obtained by an unadjusted univariate Tobit regression model, which allowed for censoring at the lower limit of detection of the RT–PCR assay, with significant

differences in bold. Undetectable values were imputed as 0.3 log10 virus copies per sample. IQR, interquartile range. respiratory droplet and aerosol samples collected without face size fractionation) collected from hospitals treating patients with masks, respectively. There was a significant reduction by wearing severe acute respiratory syndrome and Middle East respiratory face masks to 1 of 27 (4%) in detection of influenza virus in respira- syndrome, but ours demonstrates detection of human seasonal tory droplets, but no significant reduction in detection in aerosols coronaviruses in exhaled breath, including the detection of OC43 (Table 1b). Moreover, among the eight participants who had influ- and HKU1 from respiratory droplets and NL63, OC43 and HKU1 enza virus detected by RT–PCR from without-mask aerosols, five from aerosols. were tested by viral culture and four were culture-positive. Among Our findings indicate that surgical masks can efficaciously reduce the six participants who had influenza virus detected by RT–PCR the emission of influenza virus particles into the environment in from with-mask aerosols, four were tested by viral culture and two respiratory droplets, but not in aerosols12. Both the previous and were culture-positive. For rhinovirus, there were no significant dif- current study used a bioaerosol collecting device, the Gesundheit-II ferences between detection of virus with or without face masks, both (G-II)12,15,19, to capture exhaled breath particles and differentiated in respiratory droplets and in aerosols (Table 1b). Conclusions were them into two size fractions, where exhaled breath coarse particles similar in comparisons of viral shedding (Table 1b). In addition, >5 μm (respiratory droplets) were collected by impaction with a we found a significant reduction in viral shedding (Supplementary 5-μm slit inertial Teflon impactor and the remaining fine particles Table 2) in respiratory droplets for OC43 (Extended Data Fig. 4) ≤5 μm (aerosols) were collected by condensation in buffer. We also and influenza B virus (Extended Data Fig. 5) and in aerosols for demonstrated the efficacy of surgical masks to reduce coronavi- NL63 (Extended Data Fig. 4). rus detection and viral copies in large respiratory droplets and in We identified correlations between viral loads in different aerosols (Table 1b). This has important implications for control of samples (Extended Data Figs. 6–8) and some evidence of declines COVID-19, suggesting that surgical face masks could be used by ill in viral shedding by time since onset for influenza virus but not people to reduce onward transmission. for coronavirus or rhinovirus (Extended Data Fig. 9). In univari- Among the samples collected without a face mask, we found that able analyses of factors associated with detection of respiratory the majority of participants with influenza virus and coronavirus viruses in various sample types, we did not identify significant infection did not shed detectable virus in respiratory droplets or association in viral shedding with days since symptom onset aerosols, whereas for rhinovirus we detected virus in aerosols in 19 (Supplementary Table 3) for respiratory droplets or aerosols of 34 (56%) participants (compared to 4 of 10 (40%) for coronavi- (Supplementary Tables 4–6). rus and 8 of 23 (35%) for influenza). For those who did shed virus A subset of participants (72 of 246, 29%) did not cough at all dur- in respiratory droplets and aerosols, viral load in both tended to be ing at least one exhaled breath collection, including 37 of 147 (25%) low (Fig. 1). Given the high collection efficiency of the G-II (ref. 19) during the without-mask and 42 of 148 (28%) during the with-mask and given that each exhaled breath collection was conducted for breath collection. In the subset for coronavirus (n = 4), we did not 30 min, this might imply that prolonged close contact would be detect any virus in respiratory droplets or aerosols from any partici- required for transmission to occur, even if transmission was primar- pants. In the subset for influenza virus (n = 9), we detected virus in ily via aerosols, as has been described for rhinovirus colds20. Our aerosols but not respiratory droplets from one participant. In the results also indicate that there could be considerable heterogene- subset for rhinovirus (n = 17), we detected virus in respiratory drop- ity in contagiousness of individuals with coronavirus and influenza lets from three participants, and we detected virus in aerosols in five virus infections. participants. The major limitation of our study was the large proportion of participants with undetectable viral shedding in exhaled breath Discussion for each of the viruses studied. We could have increased the sam- Our results indicate that aerosol transmission is a potential mode pling duration beyond 30 min to increase the viral shedding being of transmission for coronaviruses as well as influenza viruses and captured, at the cost of acceptability in some participants. An rhinoviruses. Published studies detected respiratory viruses13,14 such alternative approach would be to invite participants to perform as influenza12,15 and rhinovirus16 from exhaled breath, and the detec- forced coughs during exhaled breath collection12. However, it was tion of SARS-CoV17 and MERS-CoV18 from air samples (without the aim of our present study to focus on recovering respiratory

Nature Medicine | VOL 26 | May 2020 | 676–680 | www.nature.com/naturemedicine 679 Brief Communication NATuRE MEDicinE virus in exhaled breath in a real-life situation and we expected that 6. Cowling, B. J. & Leung, G. M. Epidemiological research priorities for public some individuals during an acute respiratory illness would health control of the ongoing global novel coronavirus (2019-nCoV) outbreak. Euro Surveill. https://doi.org/10.2807/1560-7917.ES.2020.25.6.2000110 (2020). not cough much or at all. Indeed, we identified virus RNA in a 7. Han, Q., Lin, Q., Ni, Z. & You, L. Uncertainties about the transmission routes small number of participants who did not cough at all during of 2019 novel coronavirus. Infuenza Other Respir. Viruses https://doi. the 30-min exhaled breath collection, which would suggest drop- org/10.1111/irv.12735 (2020). let and aerosol routes of transmission are possible from individu- 8. MacIntyre, C. R. & Chughtai, A. A. Facemasks for the prevention of infection als with no obvious signs or symptoms. Another limitation is that in healthcare and community settings. BMJ 350, h694 (2015). 9. Ha’eri, G. B. & Wiley, A. M. Te efcacy of standard surgical face masks: we did not confirm the infectivity of coronavirus or rhinovirus an investigation using “tracer particles”. Clin. Orthop. Relat. Res. 148, detected in exhaled breath. While the G-II was designed to preserve 160–162 (1980). viability of viruses in aerosols, and in the present study we were able 10. Patel, R. B., Skaria, S. D., Mansour, M. M. & Smaldone, G. C. Respiratory to identify infectious influenza virus in aerosols, we did not attempt source control using a surgical mask: an in vitro study. J. Occup. Environ. to culture coronavirus or rhinovirus from the corresponding aero- Hyg. 13, 569–576 (2016). 11. Johnson, D. F., Druce, J. D., Birch, C. & Grayson, M. L. A quantitative sol samples. assessment of the efcacy of surgical and N95 masks to flter infuenza virus in patients with acute infuenza infection. Clin. Infect. Dis. 49, 275–277 (2009). Online content 12. Milton, D. K., Fabian, M. P., Cowling, B. J., Grantham, M. L. & McDevitt, J. J. Any methods, additional references, Nature Research reporting Infuenza virus aerosols in human exhaled breath: particle size, culturability, and efect of surgical masks. PLoS Pathog. 9, e1003205 (2013). summaries, source data, extended data, supplementary informa- 13. Huynh, K. N., Oliver, B. G., Stelzer, S., Rawlinson, W. D. & Tovey, E. R. A tion, acknowledgements, peer review information; details of author new method for sampling and detection of exhaled respiratory virus aerosols. contributions and competing interests; and statements of data and Clin. Infect. Dis. 46, 93–95 (2008). code availability are available at https://doi.org/10.1038/s41591- 14. Stelzer-Braid, S. et al. Exhalation of respiratory viruses by breathing, coughing 020-0843-2. and talking. J. Med. Virol. 81, 1674–1679 (2009). 15. Yan, J. et al. Infectious virus in exhaled breath of symptomatic seasonal infuenza cases from a college community. Proc. Natl Acad. Sci. USA 115, Received: 2 March 2020; Accepted: 20 March 2020; 1081–1086 (2018). Published online: 3 April 2020 16. Tovey, E. R. et al. Rhinoviruses signifcantly afect day-to-day respiratory symptoms of children with asthma. J. Allergy Clin. Immunol. 135, References 663–669 (2015). 1. Nichols, W. G., Peck Campbell, A. J. & Boeckh, M. Respiratory viruses other 17. Booth, T. F. et al. Detection of airborne severe acute respiratory syndrome than infuenza virus: impact and therapeutic advances. Clin. Microbiol. Rev. (SARS) coronavirus and environmental contamination in SARS outbreak 21, 274–290 (2008). units. J. Infect. Dis. 191, 1472–1477 (2005). 2. Shiu, E. Y. C., Leung, N. H. L. & Cowling, B. J. Controversy around airborne 18. Kim, S. H. et al. Extensive viable Middle East respiratory syndrome (MERS) versus droplet transmission of respiratory viruses: implication for infection coronavirus contamination in air and surrounding environment in MERS prevention. Curr. Opin. Infect. Dis. 32, 372–379 (2019). isolation wards. Clin. Infect. Dis. 63, 363–369 (2016). 3. Tellier, R., Li, Y., Cowling, B. J. & Tang, J. W. Recognition of aerosol 19. McDevitt, J. J. et al. Development and performance evaluation of an transmission of infectious agents: a commentary. BMC Infect. Dis. 19, exhaled-breath bioaerosol collector for infuenza virus. Aerosol Sci. Technol. 101 (2019). 47, 444–451 (2013). 4. Xiao, J. et al. Nonpharmaceutical measures for pandemic infuenza in 20. Jennings, L. C. & Dick, E. C. Transmission and control of rhinovirus colds. nonhealthcare settings-personal protective and environmental measures. Eur. J. Epidemiol. 3, 327–335 (1987). Emerg. Infect. Dis. https://doi.org/10.3201/eid2605.190994 (2020). 5. Kutter, J. S., Spronken, M. I., Fraaij, P. L., Fouchier, R. A. M. & Herfst, S. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in Transmission routes of respiratory viruses among humans. Curr. Opin. Virol. published maps and institutional affiliations. 28, 142–151 (2018). © The Author(s), under exclusive licence to Springer Nature America, Inc. 2020

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Methods correlation between viral shedding in nose swabs, throat swabs, respiratory droplets Study design. Participants were recruited year-round from March 2013 through May and aerosols and factors affecting viral shedding in respiratory droplets and aerosols. 2016 in a general outpatient clinic of a private hospital in Hong Kong. As routine We identified three groups of respiratory viruses with the highest frequency of practice, clinic staf screened all individuals attending the clinics for respiratory and infection as identified by RT–PCR, namely coronavirus (including NL63, OC43, any other symptoms regardless of the purpose of the visit at triage. Study staf then HKU1 and 229E), influenza virus and rhinovirus, for further statistical analyses. We approached immediately those who reported at least one of the following symptoms defined viral shedding as log10 virus copies per sample and plotted viral shedding in of ARI for further screening: fever ≥37.8 °C, cough, sore throat, runny nose, each sample (nasal swab, throat swab, respiratory droplets and aerosols); the latter headache, myalgia and phlegm. Individuals who reported ≥2 ARI symptoms, within two were stratified by mask intervention. As a proxy for the efficacy of face masks 3 d of illness onset and ≥11 years of age were eligible to participate. Afer explaining in preventing transmission of respiratory viruses via respiratory droplet and aerosol the study to and obtaining informed consent from the participants, a rapid infuenza routes, we compared the respiratory virus viral shedding in respiratory droplet and diagnostic test, the Sofa Infuenza A + B Fluorescent Immunoassay Analyzer (cat. aerosol samples between participants wearing face masks or not, by comparing the no. 20218, Quidel), was used to identify infuenza A or B virus infection as an frequency of detection with a two-sided Fisher’s exact test and by comparing viral incentive to participate. All participants provided a nasal swab for the rapid test load (defined as log10 virus copies per sample) by an unadjusted univariate Tobit and an additional nasal swab and a separate throat swab for subsequent virologic regression model, which allowed for censoring at the lower limit of detection of the confrmation at the laboratory. All participants also completed a questionnaire to RT–PCR assay. We also used the unadjusted univariate Tobit regression to investigate record basic information including age, sex, symptom severity, medication, medical factors affecting viral shedding in respiratory droplets and aerosols without mask use, conditions and smoking history. In the frst phase of the study from March 2013 to for example age, days since symptom onset, previous influenza vaccination, current February 2014 (‘Infuenza Study’), the result of the rapid test was used to determine medication and number of coughs during exhaled breath collection. We investigated eligibility for further participation in the study and exhaled breath collection, whereas correlations between viral shedding in nasal swab, throat swab, respiratory droplets in the second phase of the study from March 2014 to May 2016 (‘Respiratory Virus and aerosols with scatter-plots and calculated the Spearman’s rank correlation −1 Study’), the rapid test did not afect eligibility. Eligible participants were then invited coefficient between any two types of samples. We imputed 0.3 log10 virus copies ml to provide an exhaled breath sample for 30 min in the same clinic visit. for undetectable values before transformation to log10 virus copies per sample. All 22 23 Before exhaled breath collection, each participant was randomly allocated in analyses were conducted with R v.3.6.0 (ref. ) and the VGAM package v.1.1.1 (ref. ). a 1:1 ratio to either wearing a surgical face mask (cat. no. 62356, Kimberly-Clark) or not during the collection. To mimic the real-life situation, under observation by Reporting Summary. Further information on research design is available in the the study staff, participants were asked to attach the surgical mask themselves, but Nature Research Reporting Summary linked to this article. instruction on how to wear the mask properly was given when the participant wore the mask incorrectly. Participants were instructed to breathe as normal during Data availability the collection, but (natural) coughing was allowed and the number of coughs was Anonymized raw data and R syntax to reproduce all the analyses, figures, tables recorded by study staff. Participants were then invited to provide a second exhaled and supplementary tables in the published article are available at: https://doi. breath sample of the alternate type (for example if the participant was first assigned org/10.5061/dryad.w9ghx3fkt. to wearing a mask they would then provide a second sample without a mask), but most participants did not agree to stay for a second measurement because References of time constraints. Participants were compensated for each 30-min exhaled 21. Chan, K. H., Peiris, J. S., Lim, W., Nicholls, J. M. & Chiu, S. S. Comparison of breath collection with a supermarket coupon worth approximately US$30 and all nasopharyngeal focked swabs and aspirates for rapid diagnosis of respiratory participants were gifted a tympanic thermometer worth approximately US$20. viruses in children. J. Clin. Virol. 42, 65–69 (2008). 22. R: a language and environment for statistical computing (R Foundation for Ethical approval. Written informed consent was obtained from all participants Statistical Computing, Vienna, Austria, 2019). 18 years of age and written informed consent was obtained from parents or ≥ 23. Yee, T. W. Vector Generalized Linear and Additive Models: with an legal guardians of participants 11–17 years of age in addition to their own written Implementation in R (Springer, 2016). informed consent. The study protocol was approved by the Institutional Review Board of The University of Hong Kong and the Clinical and Research Ethics Committee of Hong Kong Baptist Hospital. Acknowledgements This work was supported by the General Research Fund of the University Grants Collection of swabs and exhaled breath particles. Nasal swabs and throat swabs Committee (grant no. 765811), the Health and Medical Research Fund (grant no. 13120592) were collected separately, placed in virus transport medium, stored and transported to and a commissioned grant of the Food and Health Bureau and the Theme-based Research the laboratory at 2–8 °C and the virus transport medium was aliquoted and stored Scheme (project no. T11-705/14-N) of the Research Grants Council of the Hong Kong at −70 °C until further analysis. Exhaled breath particles were captured and differ­ SAR Government. We acknowledge colleagues including R. O. P. Fung, A. K. W. Li, T. W. entiated into two size fractions, the coarse fraction containing particles with aerody­ Y. Ng, T. H. C. So, P. Wu and Y. Xie for technical support in preparing and conducting this namic diameter >5 μm (referred to here as ‘respiratory droplets’), which included study and enrolling participants; J. K. M. Chan, S. Y. Ho, Y. Z. Liu and A. Yu for laboratory droplets up to approximately 100 µm in diameter and the fine fraction with particles support; S. Ferguson, W. K. Leung, J. Pantelic, J. Wei and M. Wolfson for technical support ≤5 μm (referred to here as ‘aerosols’) by the G-II bioaerosol collecting device12,15,19. in constructing and maintaining the G-II device; V. J. Fang, L. M. Ho and T. T. K. Lui for In the G-II device, exhaled breath coarse particles >5 μm were collected by a 5-μm setting up the database; and C. W. Y. Cheung, L. F. K. Cheung, P. T. Y. Ching, A. C. H. Lai, slit inertial Teflon impactor and the remaining fine particles ≤5 μm were condensed D. W. Y. Lam, S. S. Y. Lo, A. S. K. Luk and other colleagues at the Outpatient Center and and collected into approximately 170 ml of 0.1% BSA/PBS. Both the impactor and the Infection Control Team of Hong Kong Baptist Hospital for facilitating this study. condensate were stored and transported to the laboratory at 2–8 °C. The virus on the impactor was recovered into 1 ml and the condensate was concentrated into 2 ml of Author contributions 0.1% BSA/PBS, aliquoted and stored at −70 °C until further analysis. In a validation All authors meet the International Committee of Medical Journal Editors criteria for study, the G-II was able to recover over 85% of fine particles >0.05 µm in size and had authorship. The study protocol was drafted by N.H.L.L. and B.J.C. Data were collected comparable collection efficiency of influenza virus as the SKC BioSampler19. by N.H.L.L., E.Y.C.S. and B.J.P.H. Laboratory testing was performed by D.K.W.C. and K.- H.C. Statistical analyses were conducted by N.H.L.L. N.H.L.L. and B.J.C. wrote the first Laboratory testing. Samples collected from the two studies were tested at the same draft of the manuscript, and all authors provided critical review and revision of the text time. Nasal swab samples were first tested by a diagnostic-use viral panel, xTAG and approved the final version. Respiratory Viral Panel (Abbott Molecular) to qualitatively detect 12 common respiratory viruses and subtypes including coronaviruses (NL63, OC43, 229E and Competing interests HKU1), influenza A (nonspecific, H1 and H3) and B viruses, respiratory syncytial B.J.C. consults for Roche and Sanofi Pasteur. The authors declare no other competing virus, parainfluenza virus (types 1–4), adenovirus, human metapneumovirus and interests. enterovirus/rhinovirus. After one or more of the candidate respiratory viruses was detected by the viral panel from the nasal swab, all the samples from the same participant (nasal swab, throat swab, respiratory droplets and aerosols) were then Additional information tested with RT–PCR specific for the candidate virus(es) for determination of virus Extended data is available for this paper at https://doi.org/10.1038/s41591-020-0843-2. concentration in the samples. Infectious influenza virus was identified by viral Supplementary information is available for this paper at https://doi.org/10.1038/ culture using MDCK cells as described previously21, whereas viral culture was not s41591-020-0843-2. performed for coronavirus and rhinovirus. Correspondence and requests for materials should be addressed to B.J.C. Statistical analyses. The primary outcome of the study was virus generation rate Peer review information Alison Farrell was the primary editor on this article and in tidal breathing of participants infected by different respiratory viruses and the managed its editorial process and peer review in collaboration with the rest of the efficacy of face masks in preventing virus dissemination in exhaled breath, separately editorial team. considering the respiratory droplets and aerosols. The secondary outcomes were Reprints and permissions information is available at www.nature.com/reprints.

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Extended Data Fig. 1 | Participant enrolment, randomization of mask intervention and identification of respiratory virus infection.

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Extended Data Fig. 2 | Weekly number of respiratory virus infections identified by RT-PCR in symptomatic individuals who had provided exhaled breath samples (respiratory droplets and aerosols) during the study period. Blue, coronavirus; red, influenza virus; yellow, rhinovirus; green, other respiratory viruses including human metapneumovirus, parainfluenza virus, respiratory syncytial virus and adenovirus; white, no respiratory virus infection identified.

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Extended Data Fig. 3 | Respiratory virus shedding in (a) nasal swab, (b) throat swab, (c) respiratory droplets and (d) aerosols in symptomatic individuals with coronavirus NL63, coronavirus OC43, coronavirus HKU1, influenza A and influenza B virus infection. For nasal swabs and throat swabs, all infected individuals identified by RT-PCR in any collected samples were included: coronavirus NL63 (n = 8), coronavirus OC43 (n = 5), coronavirus HKU1 (n = 4), influenza A virus (n = 31) and influenza B virus (n = 14). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included: coronavirus NL63 (n = 3), coronavirus OC43 (n = 3), coronavirus HKU1 (n = 4), influenza A virus (n = 19) and influenza B virus (n = 6). The box plots indicate the median with the interquartile range (lower and upper hinge) and ± 1.5 × interquartile range from the first and third quartile (lower and upper whisker). Dark blue, coronavirus NL63; light blue, coronavirus OC43; brown, coronavirus HKU1; red, influenza A virus; orange, influenza B virus.

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Extended Data Fig. 4 | See next page for caption.

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Extended Data Fig. 4 | Efficacy of surgical face masks in reducing respiratory virus shedding in respiratory droplets and aerosols of symptomatic individuals with seasonal coronaviruses including (a) coronavirus NL63, (b) coronavirus OC43 and (c) coronavirus HKU1. The figure shows the virus copies per sample collected in nasal swab (red), throat swab (blue), respiratory droplets collected for 30 min while not wearing (dark green) or wearing (light green) a surgical face mask and aerosols collected for 30 min while not wearing (brown) or wearing (orange) a face mask, collected from individuals with acute respiratory symptoms who were positive for coronavirus NL63, coronavirus OC43 and coronavirus HKU1 as determined by RT-PCR in any samples. P values for mask intervention as predictor of log10 virus copies per sample in an unadjusted univariate Tobit regression model which allowed for censoring at the lower limit of detection of the RT-PCR assay are shown, with significant differences in bold. For nasal swabs and throat swabs, all infected individuals were included (coronavirus NL63, n = 8; coronavirus OC43, n = 5; coronavirus HKU1, n = 4). For respiratory droplets and aerosols, numbers of infected individuals who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: coronavirus NL63 (n = 3 and 5), coronavirus OC43 (n = 3 and 4), coronavirus HKU1 (n = 4 and 2). A subset of participants provided exhaled breath samples for both mask interventions (coronavirus NL63, n = 0; coronavirus OC43, n = 2; coronavirus HKU1, n = 2).

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Extended Data Fig. 5 | Efficacy of surgical face masks in reducing respiratory virus shedding in respiratory droplets and aerosols of symptomatic individuals with seasonal influenza viruses including (a) influenza A and (b) influenza B virus. The figure shows the virus copies per sample collected in nasal swab (red), throat swab (blue), respiratory droplets collected for 30 min while not wearing (dark green) or wearing (light green) a surgical face mask and aerosols collected for 30 min while not wearing (brown) or wearing (orange) a face mask, collected from individuals with acute respiratory symptoms who were positive for influenza A and influenza B virus as determined by RT-PCR in any samples. P values for mask intervention as predictor of log10 virus copies per sample in an unadjusted univariate Tobit regression model which allowed for censoring at the lower limit of detection of the RT-PCR assay are shown, with significant differences in bold. For nasal swabs and throat swabs, all infected individuals were included (influenza A virus, n = 31; influenza B virus, n = 14). For respiratory droplets and aerosols, numbers of infected individuals who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: influenza A virus (n = 19 and 19), influenza B virus (n = 6 and 10). A subset of participants provided exhaled breath samples for both mask interventions (influenza A virus, n = 7; influenza B virus, n = 2).

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Extended Data Fig. 6 | Correlation of coronavirus viral shedding between different samples (nasal swab, throat swab, respiratory droplets and aerosols) in symptomatic individuals with seasonal coronavirus infection. For nasal swabs and throat swabs, all infected individuals were included (n = 17). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included (n = 10). r, the Spearman’s rank correlation coefficient.

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Extended Data Fig. 7 | Correlation of influenza viral shedding between different samples (nasal swab, throat swab, respiratory droplets and aerosols) in symptomatic individuals with seasonal influenza infection. For nasal swabs and throat swabs, all infected individuals were included (n = 43). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included (n = 23). r, the Spearman’s rank correlation coefficient.

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Extended Data Fig. 8 | Correlation of rhinovirus viral shedding between different samples (nasal swab, throat swab, respiratory droplets and aerosols) in symptomatic individuals with rhinovirus infection. For nasal swabs and throat swabs, all infected individuals were included (n = 54). For respiratory droplets and aerosols, only infected individuals who provided exhaled breath samples while not wearing a surgical face mask were included (n = 36). r, the Spearman’s rank correlation coefficient.

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Extended Data Fig. 9 | See next page for caption.

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Extended Data Fig. 9 | Respiratory virus shedding in respiratory droplets and aerosols stratified by days from symptom onset for (a) coronavirus, (b) influenza virus or (c) rhinovirus. The figures shows the virus copies per sample collected in nasal swab (red), throat swab (blue), respiratory droplets (dark green) and aerosols (brown) collected for 30 min while not wearing a surgical face mask, stratified by the number of days from symptom onset on which the respiratory droplets and aerosols were collected. For nasal swabs and throat swabs, all infected individuals were included (coronavirus, n = 17; influenza virus, n = 43; rhinovirus, n = 54). For respiratory droplets and aerosols, numbers of infected individuals who provided exhaled breath samples while not wearing or wearing a surgical face mask, respectively were: coronavirus (n = 10 and 11), influenza virus (n = 23 and 28), rhinovirus (n = 36 and 32). A subset of participants provided exhaled breath samples for both mask interventions (coronavirus, n = 4; influenza virus, n = 8; rhinovirus, n = 14). The box plots indicate the median with the interquartile range (lower and upper hinge) and ± 1.5 × interquartile range from the first and third quartile (lower and upper whisker).

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Corresponding author(s): Benjamin John Cowling

Last updated by author(s): Mar 4, 2020 Reporting Summary Nature Research wishes to improve the reproducibility of the work that we publish. This form provides structure for consistency and transparency in reporting. For further information on Nature Research policies, see Authors & Referees and the Editorial Policy Checklist.

Statistics For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section. n/a Confirmed The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one- or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section. A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals)

For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable.

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Our web collection on statistics for biologists contains articles on many of the points above. Software and code Policy information about availability of computer code Data collection No software was used.

Data analysis All analyses were conducted with R version 3.6.0 and the VGAM package 1.1.1. For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information. Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: - Accession codes, unique identifiers, or web links for publicly available datasets - A list of figures that have associated raw data - A description of any restrictions on data availability

Anonymized raw data and R syntax to reproduce all the analyses, figures, tables and supplementary tables in the published article are available at: [Dryad link pending]. October 2018

Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection. Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences

1 For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf nature research | reporting summary Life sciences study design All studies must disclose on these points even when the disclosure is negative. Sample size We estimated a priori the sample size to be 300 participants. The primary outcome of the study was the reduction in the exhaled virus concentration of normal tidal breathing by wearing face mask in terms of total virus by RT-PCR as a proxy for infectious virus particle. We expected that a 1-log reduction in exhaled virus particle by face mask intervention would have a clinically relevant effect in reducing the probability of transmission. Except for influenza, there was no quantitative data available from exhaled breath samples from respiratory virus- infected individuals before the present study. If the standard deviation of exhaled virus concentration was 1 log copies/ml (Milton et al., PLoS Pathog 2013), we would detect a difference of >1 log copies/ml in the mask vs control group as long as we have >15 participants with a specific respiratory virus. For example, if our study included 23 participants with rhinovirus detectable in exhaled breath without a mask, we will have 80% power and 0.05 significance level to identify differences in viral shedding in aerosols of 1.28 log10 copies associated with the use of face masks, assuming a standard deviation of 1.54 log10 copies based on data from nasal and throat swab (Lu et al., J Clin Microbiol 2008). We expected from 300 individuals with ARI, at least 150 to have a respiratory virus, and at least 20-30 to have each of rhinovirus, coronavirus, adenovirus and parainfluenza plus small numbers of other respiratory viruses, assuming the Viral Panel would detect respiratory viruses in 60% of participants including 10% by influenza (since we partly recruited during the influenza seasons) and the other 50% made up of rhinovirus, coronavirus, adenovirus and parainfluenza virus.

Data exclusions As described in the Results section and Supplementary Figure 1, only participants who provided exhaled breath samples and randomized to mask intervention were included; and final analyses were performed only for participants with either coronavirus, influenza virus or rhinovirus infection, which had sufficient sample size for comparison between mask intervention.

Replication Samples from a subset of participants identified with a coronavirus, influenza or rhinovirus infection were re-tested by RT-PCR with consistent results. R syntax is available to reproduce all the analyses, figures, tables and supplementary tables in the published article.

Randomization Prior to the exhaled breath collection, each participant was randomly allocated in a 1:1 ratio to either wearing a surgical face mask or not during the exhaled breath collection using a computer-generated sequence. The allocation was concealed to the study stuff performing the exhaled breath collection before allocation of the mask intervention.

Blinding Blinding to the participant and the study stuff for the mask intervention was not possible. The study staff performing the statistical analyses was also involved in the data collection. We expected there would be minimal bias due to unblinding since data collection for questionnaires was done before randomization to mask intervention, and viral load from a sample measured by RT-PCR is an objective measurement.

Reporting for specific materials, systems and methods We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response. Materials & experimental systems Methods n/a Involved in the study n/a Involved in the study Antibodies ChIP-seq Eukaryotic cell lines Flow cytometry Palaeontology MRI-based neuroimaging Animals and other organisms Human research participants Clinical data

Eukaryotic cell lines Policy information about cell lines Cell line source(s) Madin-Darby Canine Kidney (MDCK) cells

Authentication European Collection of Authenticated Cell Cultures. October 2018 Mycoplasma contamination We confirm that all cell lines tested negative for mycoplasma contamination.

Commonly misidentified lines Nil (See ICLAC register)

2 Human research participants nature research | reporting summary Policy information about studies involving human research participants Population characteristics As described in the Results section, Table 1a and Supplementary Table 1, there were some differences in characteristics of participants with the different viruses. Overall, most participants were younger adults and 5% were age 11-17 years, but there were more children with influenza virus and no children in the subgroup with coronavirus infection. Overall, 59% were female, but there were more females among the subgroup with coronavirus infection. The majority of participants did not have underlying medical conditions and overall 9% had received influenza vaccination for the current season but only 2% among those with influenza virus infection. The majority of participants were sampled within 24–48 or 48–72 hours of illness onset. 24% of participants had a measured fever ≥37.8ºC, with influenza patients more than twice as likely than coronavirus and rhinovirus- infected patients to have a measured fever. Coronavirus-infected participants coughed the most with an average of 17 (SD 30) coughs during the 30-minute exhaled breath collection. The profile of the participants randomized to with-mask vs without-mask groups were similar.

Recruitment As described in the Methods section, participants were recruited year-round from March 2013 through May 2016 in a general outpatient clinic of a private hospital in Hong Kong. As routine practice, clinic staff screened all individuals attending the clinics for respiratory and any other symptoms regardless of the purpose of the visit at the triage. Study staff then approached immediately those who reported at least one of the following symptoms of acute respiratory illness (ARI) for further screening: fever≥37.8ºC, cough, sore throat, runny nose, headache, myalgia and phlegm. Individuals who reported ≥2 ARI symptoms, within 3 days of illness onset and ≥11 years of age were eligible to participate.

Ethics oversight As described in the Methods section, the study protocol was approved by the Institutional Review Board of The University of Hong Kong and the Clinical and Research Ethics Committee of Hong Kong Baptist Hospital. Note that full information on the approval of the study protocol must also be provided in the manuscript.

Clinical data Policy information about clinical studies All manuscripts should comply with the ICMJE guidelines for publication of clinical research and a completed CONSORT checklist must be included with all submissions. Clinical trial registration The present study was not registered in clinical trials registries, as it was a laboratory-based study of detection of viruses in exhaled breath and the effect of wearing surgical facemasks on virus detection. It was not a Phase II/III clinical trial.

Study protocol Not available in clinical trials registries (as above). Study protocol will be made available to editors and peer reviewers if requested.

Data collection As described in the Methods section, participants were recruited year-round from March 2013 through March 2016 in a general outpatient clinic of a private hospital in Hong Kong. Data collection for questionnaires and exhaled breath sample collection was done face-to-face with the participant by trained study staff at the same clinic on the day of participant enrolment.

Outcomes As pre-specified in the study protocol, the primary outcomes of the study were the virus generation rate in the tidal breathing of participants infected by different respiratory viruses, and the efficacy of face mask in preventing virus dissemination in exhaled breath especially at the aerosol fraction. As pre-specified in the study protocol, one of the secondary outcomes was to provide indirect evidence for relative importance of different transmission routes of influenza and other respiratory viruses. In this regard, in the present manuscript we examined the correlation between viral shedding in nose swabs, throat swabs, respiratory droplets and aerosols, and factors affecting viral shedding in respiratory droplets and aerosols. As described in the Discussion section in the present manuscript about the limitation of our study, there was large proportion of participants with undetectable viral shedding in exhaled breath for each of the viruses studied, and therefore we were unable to examine the exhaled respiratory virus reduction proportion by chi-squared test, nor the exhaled respiratory virus reduction volume (i.e. viral load) by t-test and linear regression as pre-specified in the study protocol. Instead, we have used Fisher’s exact test and Tobit regression for the same purposes respectively. October 2018

3 BMJ 2020;369:m1435 doi: 10.1136/bmj.m1435 (Published 9 April 2020) Page 1 of 4

Analysis BMJ: first published as 10.1136/bmj.m1435 on 9 April 2020. Downloaded from ANALYSIS

Face masks for the public during the covid-19 crisis Trisha Greenhalgh and colleagues argue that it is time to apply the precautionary principle

Trisha Greenhalgh professor 1, Manuel B Schmid consultant 2 3, Thomas Czypionka chief health economist 4 5, Dirk Bassler professor 2 3, Laurence Gruer professor 6 7

1Nuffield Department of Primary Care Health Sciences, University of Oxford; 2Neonatal Department, University Hospital of Zurich, Switzerland; 3University of Zurich, Zurich, Switzerland; 4Institute for Advanced Studies, Vienna, Austria; 5London School of Economics, London, UK; 6University of Edinburgh, UK; 7University of Glasgow, UK

The precautionary principle is, according to Wikipedia, “a benefit of respirator masks over standard ones, and also strategy for approaching issues of potential harm when extensive showed that masks were worn less than 50% of the time scientific knowledge on the matter is lacking.” The evidence •A 2011 Cochrane review covering physical interventions base on the efficacy and acceptability of the different types of and including 67 studies (many of poor quality), in which face mask in preventing respiratory infections during epidemics the main relevant study was the 2009 trial described above7 is sparse and contested.1 2 But covid-19 is a serious illness that currently has no known treatment or vaccine and is spreading •A 2010 systematic review of face masks in influenza in an immune naive population. Deaths are rising steeply, and epidemics, which included standard surgical masks and http://www.bmj.com/ health systems are under strain. respirator masks and found some efficacy of masks if worn by those with respiratory symptoms but not if worn by This raises an ethical question: should policy makers apply the asymptomatic individuals.8 precautionary principle now and encourage people to wear face masks on the grounds that we have little to lose and potentially •A 2007 systematic review and expert panel deliberation, something to gain from this measure?3 We believe they should. which acknowledged the difficulties in interpreting evidence and stated: “With the exception of some evidence

Evidence and guidelines from SARS, we did not find any published data that directly on 24 July 2020 by guest. Protected copyright. Evidence based medicine tends to focus predominantly on support the use of masks … by the public.”9 The evidence internal validity—whether primary research studies were “done from SARS was not set out in the paper (so we assume it right”—using tools to assess risk of bias and adequacy of was expert opinion on the panel). statistical analysis. External validity relates to a different Two further systematic reviews have since been released as question: whether findings of primary studies done in a different preprints. Xiao and colleagues reviewed non-pharmaceutical population with a different disease or risk state are relevant to measures for prevention of influenza.10 They identified 10 the current policy question. We argue that there should be a randomised controlled trials published between 1946 and 2018 greater focus on external validity in evaluation of masks. that tested the efficacy of face masks (including standard A rapid search of the literature on the wearing of masks by the surgical masks and commercially produced paper face masks general public during epidemics or pandemics by a team at the designed for the public) for preventing laboratory confirmed University of Galway (E Toomey, personal communication, 29 influenza. A pooled meta-analysis found no significant reduction March 2020) found five peer reviewed systematic reviews: in influenza transmission (relative risk 0.78, 95% confidence •An “empty review” published on 27 March 2020—that is, interval 0.51 to 1.20; I2=30%, P=0.25). They also identified a review showing no randomised trials of masks so far seven studies conducted in households; four provided masks during the covid-19 pandemic4 for all household members, one for the sick member only, and two for household contacts only. None showed a significant •A 2020 systematic review5 comparing standard surgical reduction in laboratory confirmed influenza in the face mask masks and respirator masks, which included a single small arm. The authors concluded: “randomized controlled trials of trial from 2009 of respirator masks, standard masks, and [face masks] did not support a substantial effect on transmission no masks among the general public during an influenza of laboratory-confirmed influenza.”10 epidemic in Australia.6 That trial, which was considered robust, showed a benefit of masks over no masks, but no A preprint of a systematic review published on 6 April 2020 examined whether wearing a face mask or other barrier (goggles,

Correspondence to: T Greenhalgh [email protected]

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ANALYSIS

shield, veil) prevents transmission of respiratory illness such as produced them, but we have no evidence that they are externally coronavirus, rhinovirus, tuberculosis, or influenza.11 It identified valid in the context of covid-19. “The public” here are not 31 eligible studies, including 12 randomised controlled trials. volunteers in someone else’s experiment in a flu outbreak—they

The authors found that overall, mask wearing both in general are people the world over who are trying to stay alive in a deadly BMJ: first published as 10.1136/bmj.m1435 on 9 April 2020. Downloaded from and by infected members within households seemed to produce pandemic. They may be highly motivated to learn techniques small but statistically non-significant reductions in infection for most effective mask use. rates. The authors concluded that “The evidence is not There are good reasons why the public is likely to comply more sufficiently strong to support the widespread use of facemasks closely with mask advice and wider infection control measures 11 as a protective measure against covid-19” and recommended now than the research participants were in the published trials. further high quality randomised controlled trials. These reasons include the fact that SARS-CoV-2 is both more contagious and more serious than the medical scenarios in the Contested interpretations studies on which the conclusion not to use masks was based.17 Similarly, if SARS-CoV-2 vaccination were available and The heterogeneous and somewhat sparse primary literature affordable, it might be used more widely and be more acceptable described above has been inconsistently interpreted by policy than flu vaccination. makers. The World Health Organization, for example, recommends masks only for those with symptoms suggestive Substantial indirect evidence exists to support the argument for of covid-19, stating that masks should otherwise be reserved the public wearing masks in the covid-19 pandemic. The virus for healthcare workers.12 However, elsewhere WHO has been shown to remain viable in the air for several hours 18 acknowledges that the wearing of masks by the general public when released in an aerosol under experimental conditions, has a place in severe pandemics, since even a partial protective and such aerosols seem to be blocked by surgical masks in 19 effect could have a major influence on transmission.13 laboratory experiments. Individuals have been shown to be infectious up to 2.5 days before symptom onset,20 and as many The US Centres for Disease Control and Prevention originally as 50% of infections seem to occur from presymptomatic advised the public against wearing masks during the covid-19 individuals.21 Community prevalence of covid-19 in many pandemic, but this advice was updated on 4 April 2020 (box countries is likely to be high.22 Modelling studies suggest that 1).14 even a small reduction in community transmission could make a major difference to demand elsewhere in the system (eg, for Box 1: CDC advice on use of face masks by the general public14 hospital bed space and ventilators).23 Cover your mouth and nose with a cloth face cover when around others The suggestion that the public should not wear masks because You could spread covid-19 to others even if you do not feel sick healthcare workers need them more is valid up to a point, but Everyone should wear a cloth face cover when they have to go out in public—for example, to the grocery store or to pick up other necessities it is surely an argument for manufacturing more masks, not for http://www.bmj.com/ Cloth face coverings should not be placed on children under age 2 or on denying them to populations who could potentially benefit from anyone who has trouble breathing or is unconscious, incapacitated, or them. Until such masks are available in sufficient numbers, otherwise unable to remove the mask without assistance. cloth masks (washed frequently) as recommended by the CDC The cloth face cover is meant to protect other people in case you are (box 1),14 may be a substitute. Additional research is urgently infected needed to identify how best to overcome problems of poor Do not use a face mask meant for a healthcare worker filtration and moisture retention that have been described. Such Continue to keep about 6 feet (2 m) between yourself and others. The cloth face cover is not a substitute for social distancing studies could determine, for example, the optimum nature of

fabric, thickness (how many layers?), the nature of the outer on 24 July 2020 by guest. Protected copyright. water repellent layer, closeness of fit, and duration to be worn None of the studies mentioned above tested the makeshift cloth before washing. masks that CDC has recommended. To our knowledge, there are no trials of cloth masks in the general public. A three arm trial of cloth masks versus surgical masks versus “standard Precautionary principle practice” in preventing influenza-like illness in healthcare staff Anecdotal evidence is rightly viewed as methodologically found that cloth masks were the least effective, but “standard suspect, but as we contemplate using the precautionary principle, practice” usually involved a surgical face mask and there was we should not ignore such evidence entirely. We should, for no true control arm with no masks.15 example, take account of the high rates of infection (and Various authors have justified not wearing masks on four main substantial mortality) among healthcare and other frontline staff grounds. Firstly, they claim that there is limited evidence that in settings where there are shortages of masks compared with they are effective. Secondly, they argue that trials have shown settings where these staff were better and more consistently 24 that people are unlikely to wear them properly or consistently, protected. We might come to regret dismissing as anecdote which is important since prevention depends on people not the story of a choir practice with 60 people, of whom 45 are 25 repeatedly touching their mask, and on all or most people known to have developed covid-19 and two so far have died. wearing them most of the time. Thirdly, they point out that the Some indirect evidence for the benefits of masks is emerging. trials cited above have also shown that wearing a mask might For example, a longitudinal ecological study from Hong Kong, make people feel safe and hence disregard other important public conducted before and after the introduction of a range of health advice such as hand washing and social distancing.10 non-pharmaceutical measures including masks for the public, Finally, they argue that because of the shortage of masks in the suggested that these seemed to help to contain the pandemic current crisis, the public should not wear them since healthcare (changes were statistically significant for masks and social workers need them more, and public buying could lead to major distancing measures combined, though the effect of masks alone supply chain problems.16 cannot be isolated out).26 There is also analogical evidence from 27 28 The first argument can be challenged on the grounds that the behaviour of viruses with a similar chemical make-up. absence of evidence is not evidence of absence. The second two Given these indirect and circumstantial findings and the arguments may have been internally valid in the trials that seriousness of this outbreak, there is a moral argument that the

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ANALYSIS

public should be given the opportunity to change their behaviour and writing of the paper, and approved the final manuscript. TG and MBS are joint in line with the precautionary principle,3 even when direct, first authors and guarantors. experimental evidence for benefit is not clear cut. Unlike in Competing interests: We have read and understood BMJ policy on declaration of

Australia and the US, where most trials were done, mask interests and have no relevant interests to declare. BMJ: first published as 10.1136/bmj.m1435 on 9 April 2020. Downloaded from wearing has become normalised in some Asian countries, partly Provenance and peer review: Commissioned; not externally peer reviewed. as a protection against polluted air and perhaps also as a response to the SARS and MERS outbreaks. In Japan, Hong 1 Feng S, Shen C, Xia N, Song W, Fan M, Cowling BJ. Rational use of face masks in the Kong, South Korea, and China, for example, mask wearing is COVID-19 pandemic. Lancet Respir Med 2020;S2213-2600(20)30134-X. 10.1016/S2213-2600(20)30134-X 32203710 now the norm. 2 National Health Service (UK). Are face masks useful for preventing coronavirus? 2020. Another argument for using the precautionary principle is that https://www.nhs.uk/conditions/coronavirus-covid-19/common-questions/ 3 European Commission. The precautionary principle: decision making under uncertainty. the world may pay a high price for covid-19 and the “collateral 2017. https://ec.europa.eu/environment/integration/research/newsalert/pdf/precautionary_ damage” risks becoming higher than the direct damage from principle_decision_making_under_uncertainty_FB18_en.pdf. 4 Marasinghe KM. A systematic review investigating the effectiveness of face mask use in the virus. The dangers include increased suicide rates because limiting the spread of COVID-19 among medically not diagnosed individuals: shedding of isolation and economic hopelessness among poorer people light on current recommendations provided to individuals not medically diagnosed with 29 30 covid-19. Version 2. Research Square 2020.[Preprint.] 10.21203/rs.3.rs-16701/v2.https: losing their income or in small companies, civil unrest in //www.researchsquare.com/article/rs-16701/v2. some countries when they consider lockdown, as was seen with 5 Long Y, Hu T, Liu L, etal . Effectiveness of N95 respirators versus surgical masks against Ebola,31 people losing their access to their regular medication,32 influenza: A systematic review and meta-analysis. J Evid Based Med 2020. 10.1111/jebm.12381 32167245 thriving autocratic systems under the pretence of controlling 6 MacIntyre CR, Cauchemez S, Dwyer DE, etal . Face mask use and control of respiratory covid-19,33 34 and domestic violence and family disputes35 36—the virus transmission in households. Emerg Infect Dis 2009;15:233-41. 10.3201/eid1502.081166 19193267 list is long. There are, of course, important counterarguments, 7 Jefferson T, Del Mar CB, Dooley L, etal . Physical interventions to interrupt or reduce the including the possibility of a false sense of security and spread of respiratory viruses. Cochrane Database Syst Rev 2011;7:CD006207. . 10.1002/14651858.CD006207.pub4 21735402 reduction in compliance with other infection control measures. 8 Cowling BJ, Zhou Y, Ip DK, Leung GM, Aiello AE. Face masks to prevent transmission We propose two hypotheses that we believe should be urgently of influenza virus: a systematic review. Epidemiol Infect 2010;138:449-56. 10.1017/S0950268809991658 20092668 tested in natural experiments. The first is that in the context of 9 Aledort JE, Lurie N, Wasserman J, Bozzette SA. Non-pharmaceutical public health covid-19, many people can be taught to use masks properly and interventions for pandemic influenza: an evaluation of the evidence base. BMC Public Health 2007;7:208. 10.1186/1471-2458-7-208 17697389 will do this consistently without abandoning other important 10 Xiao J, Shiu EYC, Gao H, etal . Nonpharmaceutical measures for pandemic influenza in anti-contagion measures. The second is that if political will is nonhealthcare settings-personal protective and environmental measures. Emerg Infect Dis 2020;26. 10.3201/eid2605.190994 32027586 there, mask shortages can be quickly overcome by repurposing 11 Brainard JS, Jones N, Lake I, et al. Facemasks and similar barriers to prevent respiratory manufacturing capacity—something that is already happening illness such as COVID-19: A rapid systematic review. MedRxiv 2020.04.01.20049528 37 [Preprint.] 2020 10.1101/2020.04.01.20049528 informally. 12 World Health Organisation. Advice on the use of masks in the context of covid-19: Interim In conclusion, in the face of a pandemic the search for perfect guidance. 6 Apr 2020. https://www.who.int/publications-detail/advice-on-the-use-of-masks-

in-the-community-during-home-care-and-in-healthcare-settings-in-the-context-of-the- http://www.bmj.com/ evidence may be the enemy of good policy. As with parachutes novel-coronavirus-(2019-ncov)-outbreak. for jumping out of aeroplanes,38 it is time to act without waiting 13 World Health Organisation. Non-pharmaceutical public health measures for mitigating 39 the risk and impact of epidemic and pandemic influenza. 2019. https://www.who.int/ for randomised controlled trial evidence. A recently posted influenza/publications/public_health_measures/publication/en/. preprint of a systematic review came to the same conclusion.40 14 Centers for Disease Control. How to protect yourself. 4 Apr 2020. https://www.cdc.gov/ coronavirus/2019-ncov/prevent-getting-sick/prevention.html?CDC_AA_refVal=https%3A% Masks are simple, cheap, and potentially effective. We believe 2F%2Fwww.cdc.gov%2Fcoronavirus%2F2019-ncov%2Fprepare%2Fprevention.html. that, worn both in the home (particularly by the person showing 15 MacIntyre CR, Seale H, Dung TC, etal . A cluster randomised trial of cloth masks compared symptoms) and also outside the home in situations where with medical masks in healthcare workers. BMJ Open 2015;5:e006577. 10.1136/bmjopen-2014-006577 25903751 meeting others is likely (for example, shopping, public 16 World Health Organisation. Shortage of personal protective equipment endangering health on 24 July 2020 by guest. Protected copyright. transport), they could have a substantial impact on transmission workers worldwide. 2020. https://www.who.int/news-room/detail/03-03-2020-shortage-of- personal-protective-equipment-endangering-health-workers-worldwide with a relatively small impact on social and economic life. 17 Fauci AS, Lane HC, Redfield RR. Covid-19—navigating the uncharted. N Engl J Med 2020;382:1268-9. 10.1056/NEJMe2002387 32109011 Key messages 18 van Doremalen N, Bushmaker T, Morris DH, etal . Aerosol and surface stability of SARS-CoV-2 as compared with SARS-CoV-1. N Engl J Med 2020. The precautionary principle states we should sometimes act without 10.1056/NEJMc2004973 32182409 definitive evidence, just in case 19 Leung NH, Chu DK, Shiu EY, etal . Respiratory virus shedding in exhaled breath and efficacy of face masks (brief communication). Nat Med 2020; [Epub ahead of print.] Whether masks will reduce transmission of covid-19 in the general public 10.1038/s41591-020-0843-2 . is contested 20 Ferretti L, Wymant C, Kendall M, etal . Quantifying SARS-CoV-2 transmission suggests Even limited protection could prevent some transmission of covid-19 and epidemic control with digital contact tracing. Science 2020;eabb6936. save lives 10.1126/science.abb6936 32234805 21 Ganyani T, Kremer C, Chen D, et al. Estimating the generation interval for covid-19 based Because covid-19 is such a serious threat, wearing masks in public should on symptom onset data. medRxiv 2020.03.05.20031815. [Preprint.] be advised 10.1101/2020.03.05.20031815 22 Spellberg B, Haddix M, Lee R, etal . Community prevalence of SARS-CoV-2 among patients with influenzalike illnesses presenting to a Los Angeles medical center in March We thank the members of the covid-19 researchers Google group for a discussion 2020. JAMA 2020. . 10.1001/jama.2020.4958 32232421 23 Hellewell J, Abbott S, Gimma A, etal. Centre for the Mathematical Modelling of Infectious which inspired this paper, though the views expressed in this paper do not reflect Diseases COVID-19 Working Group. Feasibility of controlling COVID-19 outbreaks by those of all group members. We also thank Elaine Toomey of Cochrane Ireland isolation of cases and contacts. Lancet Glob Health 2020;8:e488-96. 10.1016/S2214-109X(20)30074-7 32119825 for sharing unpublished data from an ongoing review of face masks for the general 24 Gulland A. What is viral load and why are so many health workers getting sick? Daily public, and Sebastian Straube from University of Alberta, Canada, as well as two Telegraph 2020 Mar 31. https://www.telegraph.co.uk/global-health/science-and-disease/ viral-load-many-health-workers-getting-sick/. reviewers, Ben Cowling and Ka Hung Chan, for helpful advice on an earlier draft. 25 Read R. A choir decided to go ahead with rehearsal. Now dozens of members have We also thank three members of the public, John Taylor, Jenni Bowley, and Anica COVID-19 and two are dead. Los Angeles Times 2020 Mar 29. https://www.latimes.com/ Alvarez Nishio, for useful feedback which helped us improve the paper. world-nation/story/2020-03-29/coronavirus-choir-outbreak? fbclid=IwAR0XyQu4gxJdPFVJpbZI0sX5EhX2VbQyxjakL1IVvITa-aCTHVaQgaslWss. 26 Cowling BJ, Ali ST, Ng TW, et al. Impact assessment of non-pharmaceutical interventions Contributors and sources: The article was conceived on a professional discussion against COVID-19 and influenza in Hong Kong: an observational study. medRxiv 2020.03.12.20034660. [Preprint.] 10.1101/2020.03.12.20034660https://www.medrxiv.org/ network. MBS wrote the first draft. TG added conceptual insights and coordinated content/10.1101/2020.03.12.20034660v1 shaping of the paper for BMJ. All authors contributed to the development of ideas 27 Leung NH, Chu DK, Shiu EY, etal . Respiratory virus shedding in exhaled breath and efficacy of face masks. Nat Med 2020.10.1038/s41591-020-0843-2 .

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28 Lau JT, Tsui H, Lau M, Yang X. SARS transmission, risk factors, and prevention in Hong 35 Carrega C. Isolation of families for coronavirus raises concerns about domestic violence. Kong. Emerg Infect Dis 2004;10:587-92. 10.3201/eid1004.030628 15200846 ABC News 2020 Mar 20. https://abcnews.go.com/US/isolation-families-coronavirus-raises- 29 Gutman A. Coronavirus demands social distancing. Will that lead to more deaths of concerns-domestic-violence/story?id=69663886 despair? Philadelphia Inquirer 2020 Mar 19. https://www.inquirer.com/health/coronavirus/ 36 Sharon K. Coronavirus complicates already-trying child custody issues. Orange County coronavirus-covid-19-deaths-despair-future-capitalis-angus-deaton-anne-case-20200319. Register 2020 Mar 27. https://www.ocregister.com/2020/03/27/coronavirus-complicates- BMJ: first published as 10.1136/bmj.m1435 on 9 April 2020. Downloaded from html already-trying-child-custody-issues/ 30 Weisbaum H. Millions of Americans will soon run out of money. Here's how to deal with 37 Reagan C. Retailers shift production to make masks, gowns for health-care workers in bills you can't pay. NBC Universal, 2020. https://www.nbcnews.com/better/lifestyle/ coronavirus pandemic. CNBC Online 2020 Mar 26. https://www.cnbc.com/2020/03/26/ coronavirus-collateral-damage-what-do-you-do-when-paycheck-stops-ncna1163671 coronavirus-retailers-make-masksgowns-for-healthcare-workers.html. 31 Nyei A-bI. Beyond the disease: how the Ebola epidemic affected the politics and stability 38 Potts M, Prata N, Walsh J, Grossman A. Parachute approach to evidence based medicine. of the Mano River Basin. Conflict Trends 2016;2:12-9. BMJ 2006;333:701-3. 10.1136/bmj.333.7570.70110.1136/bmj.333.7570.701 17008675 32 D’Amore R. “Collateral damage”: wait times, cancellations hit health care outside of 39 Smith GC, Pell JP. Parachute use to prevent death and major trauma related to covid-19. Global News, 30 Mar 2020. https://globalnews.ca/news/6750377/coronavirus- gravitational challenge: systematic review of randomised controlled trials. Int J Prosthodont canada-essential-health-care/ 2006;19:126-8.16602356 33 Woznicki K. On the edges of democracy: mobilizing health and care as a common good 40 Jefferson T, Jones M, Al Ansari L, et al. Physical interventions to interrupt or reduce the London: openDemocracy 17 Mar 2020. https://www.opendemocracy.net/en/can-europe- spread of respiratory viruses. Part 1: face masks, eye protection and person distancing: make-it/edges-democracy-mobilizing-health-and-care-common-good/ systematic review and meta-analysis. medRxiv 2020.03.30.20047217. [Preprint.] 34 For autocratic regimes, COVID-19 is a window to consolidate power. Newsday 2020 https: 10.1101/2020.03.30.20047217 //www.newsday.co.zw/2020/04/for-autocratic-regimes-covid-19-is-a-window-to-consolidate- Published by the BMJ Publishing Group Limited. For permission to use (where not already power/ granted under a licence) please go to http://group.bmj.com/group/rights-licensing/ permissions http://www.bmj.com/ on 24 July 2020 by guest. Protected copyright.

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◥ whereas 2.97 billion trips were reported by the RESEARCH ARTICLE Ministry of Transport of the People’sRepublic of China (7). To compensate for underreport- CORONAVIRUS ing and reconcile these two numbers, a travel multiplicative factor, q, which is greater than 1, Substantial undocumented infection is included (see supplementary materials). To infer SARS-CoV-2 transmission dynam- facilitates the rapid dissemination of novel ics during the early stage of the outbreak, we simulated observations during 10–23 January coronavirus (SARS-CoV-2) 2020 (i.e., the period before the initiation of travel restrictions) (fig. S1) using an iter- Ruiyun Li1*, Sen Pei2*†, Bin Chen3*, Yimeng Song4, Tao Zhang5, Wan Yang6, Jeffrey Shaman2† ated filter-ensemble adjustment Kalman fil- ter framework (8–10). With this combined Estimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute model-inference system, we estimated the respiratory syndrome–coronavirus 2 (SARS-CoV-2)] infections is critical for understanding the overall trajectories of four model state variables (Si, r u prevalence and pandemic potential of this disease. Here, we use observations of reported infection Ei, Ii ,andIi : the susceptible, exposed, doc- within China, in conjunction with mobility data, a networked dynamic metapopulation model, and umented infected, and undocumented in- Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV-2, including the fected subpopulations in city i, respectively) fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections for each of the 375 cities, while simultaneously were undocumented [95% credible interval (CI): 82–90%] before the 23 January 2020 travel restrictions. inferring six model parameters (Z, D, m, b, a, The transmission rate of undocumented infections per person was 55% the transmission rate of documented and q: the average latency period, the average Downloaded from infections (95% CI: 46–62%), yet, because of their greater numbers, undocumented infections were duration of infection, the transmission reduc- the source of 79% of the documented cases. These findings explain the rapid geographic spread tion factor for undocumented infections, the of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging. transmission rate for documented infections, the fraction of documented infections, and the travel multiplicative factor, respectively).

he novel coronavirus that emerged in in China during the weeks before and after Details of model initialization, including the http://science.sciencemag.org/ Wuhan, China, at the end of 2019, severe the shutdown of travel in and out of Wuhan. initial seeding of exposed and undocumented acute respiratory syndrome–coronavirus 2 We developed a mathematical model that infections, are provided in the supplementary T (SARS-CoV-2), quickly spread to all Chinese simulates the spatiotemporal dynamics of materials. To account for delays in infection provinces and, as of 1 March 2020, to 58 infections among 375 Chinese cities (see sup- confirmation, we also defined a time-to-event other countries (1, 2). Efforts to contain the plementary materials). In the model, we di- observation model using a gamma distribu- virus are ongoing; however, given the many vided infections into two classes: (i) documented tion (see supplementary materials). Specifical- r uncertainties regarding pathogen transmis- infected individuals with symptoms severe ly, for each new case in group Ii , a reporting sibility and virulence, the effectiveness of these enough to be confirmed, i.e., observed infec- delay td (in days) was generated from a gamma efforts is unknown. tions; and (ii) undocumented infected indi- distribution with a mean value of Td.Infitting

The fraction of undocumented but infec- viduals. These two classes of infection have both synthetic and the observed outbreaks, on June 24, 2020 tious cases is a critical epidemiological charac- separate rates of transmission: b, the trans- we performed simulations with the model- teristic that modulates the pandemic potential mission rate due to documented infected in- inference system using different fixed values of an emergent respiratory virus (3–6). These dividuals; and mb, the transmission rate due to of Td (6 days ≤ Td ≤ 10 days) and different max- undocumented infections often go unrecognized undocumented individuals, which is b reduced imum seeding, Seedmax (1500 ≤ Seedmax ≤ 2500) owing to mild, limited, or lack of symptoms and by a factor m. (see supplementary materials) (fig. S2). The best- thus, depending on their contagiousness and Spatial spread of SARS-CoV-2 across cities is fitting model-inference posterior was identified numbers, can expose a far greater portion of the captured by the daily number of people trav- by log likelihood. population to the virus than would otherwise eling from city j to city i and a multiplicative occur. Here, to assess the full epidemic poten- factor. Specifically, daily numbers of travelers Validation of the model-inference framework tial of SARS-CoV-2, we use a model-inference between 375 Chinese cities during the Spring We first tested the model-inference framework framework to estimate the contagiousness Festival period (“Chunyun”) were derived from versus alternate model forms and using syn- and proportion of undocumented infections human mobility data collected by the Tencent thetic outbreaks generated by the model in free location-based service during the 2018 Chunyun simulation. These tests verified the ability of period (1 February–12 March 2018) (7). Chunyun the model-inference framework to accurately 1MRC Centre for Global Infectious Disease Analysis, is a period of 40 days—15 days before and estimate all six target model parameters simul- Department of Infectious Disease Epidemiology, School of 25 days after the Lunar New Year—during taneously (see supplementary methods and Public Health, Faculty of Medicine, Imperial College London, London W2 1PG, UK. 2Department of Environmental Health which there are high rates of travel within figs. S3 to S14). The system could identify a Sciences, Mailman School of Public Health, Columbia China. To estimate human mobility during the variety of parameter combinations and dis- 3 University, New York, NY 10032, USA. Department of Land, 2020 Chunyun period, which began 10 January, tinguish outbreaks generated with high a Air and Water Resources, University of California, Davis, Davis, CA 95616, USA. 4Department of Urban Planning we aligned the 2018 Tencent data on the ba- and low m from those generated with low a and Design, The University of Hong Kong, Hong Kong. sis of relative timing to the Spring Festival. and high m. This parameter identifiability is 5 Ministry of Education Key Laboratory for Earth System Forexample,weusedmobilitydatafrom facilitated by the assimilation of observed case Modeling, Department of Earth System Science, Tsinghua University, Beijing 10084, P. R. China. 6Department of 1 February 2018 to represent human move- data from multiple (375) cities into the model- Epidemiology, Mailman School of Public Health, Columbia ment on 10 January 2020, as these days were inference system and the incorporation of hu- University, New York, NY 10032, USA. similarly distant from the Lunar New Year. man movement into the mathematical model *These authors contributed equally to this work. †Corresponding author. Email: [email protected] During the 2018 Chunyun, 1.73 billion travel structure (see supplementary methods and (S.P.); [email protected] (J.S.) events were captured in the Tencent data, figs. S15 and S16).

Li et al., Science 368, 489–493 (2020) 1 May 2020 1of5 RESEARCH | RESEARCH ARTICLE

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Fig. 1. Best-fit model and sensitivity analysis. Simulation of daily reported cases combination a =0.14andm = 0.55 is indicated by the red x; the dashed box indicates in all cities (A), Wuhan city (B), and Hubei province (C). The blue box and whiskers the 95% credible interval of that estimate. (F) Log likelihood for simulations with show the median, interquartile range, and 95% CIs derived from 300 simulations combinations of (a,m) and all other parameters held constant at Table 1 mean values. using the best-fit model (Table 1). The red x’s are daily reported cases. For each parameter combination, 300 simulations were performed. The best-fit on June 24, 2020

(D) The distribution of estimated Re.(E) The impact of varying a and m on Re with all estimated parameter combination a =0.14andm = 0.55 is indicated by the red x other parameters held constant at Table 1 mean values. The black solid line indicates (the x is plotted at the lower-left corner of its respective heat map pixel, i.e., the pixel parameter combinations of (a,m) yielding Re = 2.38. The estimated parameter with the highest log likelihood); the dashed box indicates the 95% CI of that estimate.

Epidemiological characteristics during 10–23 January 2020 Table 1. Best-fit model posterior estimates of key epidemiological parameters for simulation

We next applied the model-inference frame- with the full metapopulation model during 10–23 January 2020. Seedmax = 2000, Td =9days. work to the observed outbreak before the travel restrictions imposed on 23 January 2020—a total of 801 documented cases throughout Parameter Median (95% CIs) China, as reported by 8 February (1). Figure 1, b −1 Transmission...... rate ( , days ) 1.12 (1.06, 1.19) A to C, shows simulations of reported cases m ...... Relative transmission rate ( ) 0.55 (0.46, 0.62) generated using the best-fitting model pa- ...... Latency period (Z, days) 3.69 (3.30, 3.96) rameter estimates. The distribution of these ...... Infectious period (D, days) 3.47 (3.15, 3.73) stochastic simulations captures the range of a ...... Reporting rate ( ) 0.14 (0.10, 0.18) observed cases well. In addition, the best-fitting ...... Basic reproductive number (Re) 2.38 (2.03, 2.77) model captures the spread of infections with q ...... Mobility factor ( ) 1.36 (1.27, 1.45) the novel coronavirus disease 2019 (COVID-19) to other cities in China (fig. S17). Our median estimate of the effective reproductive num- timates of the reproductive number for this high rate of undocumented infections: 86%. ber, Re—equivalent to the basic reproductive time period (6, 11–15). In addition, the median This finding is independently corroborated number, R0, at the beginning of the epidemic—is estimates for the latency and infectious pe- by the infection rate among foreign nationals 2.38 [95% credible interval (CI): 2.03−2.77], riods are ~3.69 and 3.47 days, respectively. We evacuated from Wuhan (see supplementary indicating that COVID-19 has a high capacity also find that, during 10–23 January, only 14% materials). These undocumented infections for sustained transmission (Table 1 and Fig. (95% CI: 10–18%) of total infections in China are estimated to have been half as contagious 1D). This finding aligns with other recent es- were reported. This estimate reveals a very per individual as reported infections (m =0.55;

Li et al., Science 368, 489–493 (2020) 1 May 2020 2of5 RESEARCH | RESEARCH ARTICLE Downloaded from

Fig. 2. Impact of undocumented infections on the transmission of SARS-CoV-2. Simulations generated using the parameters reported in Table 1 with m = 0.55 (red) and m = 0 (blue) showing daily documented cases in all cities (A), daily documented cases in Wuhan city (B), and the number of cities with ≥10 cumulative documented cases (C). The box and whiskers show the median, interquartile range, and 95% CIs derived from 300 simulations. http://science.sciencemag.org/

Table 2. Best-fit model posterior estimates of key epidemiological parameters for simulation of the model during 24 January–3 February and

24 January–8 February. Seedmax = 2000 on 10 January, Td = 9 days before 24 January, and Td = 6 days between 24 January and 8 February. Travel to and from Wuhan is reduced by 98%, and other intercity travel is reduced by 80%.

24 January–3 February 24 January–8 February Parameter [Median (95% CIs)] [Median (95% CIs)] b −1 Transmission...... rate ( , days ) 0.52 (0.42, 0.72) 0.35 (0.28, 0.45) m ...... Relative transmission rate ( ) 0.50 (0.37, 0.69) 0.43 (0.31, 0.61)

on June 24, 2020 ...... Latency period (Z, days) 3.60 (3.41, 3.84) 3.42 (3.30, 3.65)

...... Infectious period (D, days) 3.14 (2.71, 3.72) 3.31 (2.96, 3.88) a ...... Reporting rate ( ) 0.65 (0.60, 0.69) 0.69 (0.65, 0.72)

...... Effective reproductive number (Re) 1.34 (1.10, 1.67) 0.98 (0.83, 1.16)

95% CI: 0.46–0.62). Other model fittings made January in Wuhan city. Further, 86.2% (95% (Fig. 2C). This finding indicates that conta- using alternate values of Td and Seedmax or CI: 81.5–89.8%) of all infections originated gious, undocumented infections facilitated different distributional assumptions produced from undocumented cases. Nationwide, the the geographic spread of SARS-CoV-2 within similar parameter estimates (figs. S18 to S22), as number of infections during 10–23 January China. did estimations made using an alternate model was 16,829 (95% CI: 3797–30,271), with 86.2% structure with separate average infectious pe- (95% CI: 81.6–89.8%) originating from un- Epidemiological characteristics after riods for undocumented and documented in- documented cases. To further examine the 23 January 2020 fections (see supplementary methods, table S1). impact of contagious, undocumented COVID- We also modeled the transmission of COVID-19 Further sensitivity testing indicated that a and 19 infections on overall transmission and re- in China after 23 January, when greater con- m are uniquely identifiable given the model ported case counts, we generated a set of trol measures were effected. These control structure and abundance of observations used hypothetical outbreaks using the best-fitting measures included travel restrictions im- (see supplementary methods and Fig. 1, E and parameter estimates but with m = 0, i.e., the posed between major cities and Wuhan, self- F). In particular, Fig. 1F shows that the highest undocumented infections are no longer con- quarantine and contact precautions advocated log-likelihood fittings are centered in the 95% tagious (Fig. 2). We find that without trans- by the government, and more available rapid CI estimates for a and m and drop off with dis- mission from undocumented cases, reported testing for infection confirmation (11, 12). tance from the best-fitting solution (a = 0.14 infections during 10–23 January are reduced These measures, along with changes in med- and m = 0.55). by 78.8% across all of China and by 66.1% in ical care–seeking behavior due to increased Using the best-fitting model (Table 1 and Wuhan. Further, there are fewer cities with awareness of the virus and increased personal Fig. 1), we estimated 13,118 (95% CI: 2974– more than 10 cumulative documented cases: protective behavior (e.g., wearing of face masks, 23,435) new COVID-19 infections (documented only one city with more than 10 documented social distancing, self-isolation when sick), like- and undocumented combined) during 10–23 cases versus the 10 observed by 23 January ly altered the epidemiological characteristics

Li et al., Science 368, 489–493 (2020) 1 May 2020 3of5 RESEARCH | RESEARCH ARTICLE of the outbreak after 23 January. To quan- infections (Table 1). This high proportion of thelengthoftimeneededtoeliminatethe tify these differences, we reestimated the sys- undocumented infections, many of which disease locally and prevent a rebound out- tem parameters using the model-inference were likely not severely symptomatic, appears break once control measures are relaxed is framework and city-level daily cases reported to have facilitated the rapid spread of the virus unclear. Moreover, similar control measures between 24 January and 8 February. Given throughout China. Indeed, suppression of the and travel restrictions would have to be im- that intercity mobility was restricted after infectiousness of these undocumented cases plemented outside China to prevent reintro- 23 January, we tested two altered travel scenar- in model simulations reduces the total num- duction of the virus. ios: (i) scenario 1: a 98% reduction of travel in ber of documented cases and the overall spread The results for 10–23 January 2020 deline- and out of Wuhan and an 80% reduction in of SARS-CoV-2 (Fig. 2). In addition, the best- ate the characteristics of SARS-CoV-2 moving travel between all other cities, as indicated by fitting model has a reporting delay of 9 days through a developed country, China, without changes in the Baidu mobility index (16)(table from initial infectiousness to confirmation; major restrictions or control. These findings S2); and (ii) scenario 2: a complete stoppage of in contrast, line-list data for the same 10–23 provide a baseline assessment of the fraction intercity travel (i.e., q to 0) (see supplementary January period indicates an average 6.6-day of undocumented infections and their relative methods for more details). delay from initial manifestation of symptoms infectiousness for such an environment. How- Theresultsofinferenceforthe24January– to confirmation (17). This discrepancy suggests ever, differences in control activity, viral sur- 8 February period are presented in Table 2, that presymptomatic shedding may be typi- veillance and testing, and case definition and figs. S23 to S26, and table S3. As control mea- cal among documented infections. The rela- reporting would likely affect rates of infection sures have continually shifted, we present esti- tive timing of onset and peak of viremia and documentation. Thus, the key findings, that mates for both 24 January–3 February (period 1) shedding versus onset and peak of symptoms 86% of infections went undocumented and that, and 24 January–8 February (period 2). For has been shown to potentially affect outbreak per person, these undocumented infections were both periods, the best-fitting model for sce- control success (18). 55% as contagious as documented infections, Downloaded from nario 1 had a reduced reporting delay, Td,of Our findings also indicate that a radical could shift in other countries with different 6days(versus9daysbefore23January), increase in the identification and isolation of control, surveillance, and reporting practices. consistent with more rapid confirmation of currently undocumented infections would be Our findings underscore the seriousness of infections. Estimates of both the latency and needed to fully control SARS-CoV-2. Increased SARS-CoV-2. The 2009 H1N1 pandemic influ- infectious periods were similar to those made news coverage and awareness of the virus enza virus also caused many mild cases, quickly for 10–23 January; however, a, b,andRe all in the general population have likely already spread globally, and eventually became endemic. http://science.sciencemag.org/ shiftedconsiderably.Thetransmissionrateof prompted increased rates of seeking medi- Presently, there are four endemic coronavirus documented cases, b, dropped to 0.52 (95% CI: cal care for respiratory symptoms. In addi- strains circulating in human populations (229E, 0.42–0.72) during period 1 and to 0.35 (95% CI: tion, awareness among health care providers HKU1, NL63, and OC43). If the novel corona- 0.28–0.45) during period 2, less than half the and public health officials and the availability virus follows the pattern of 2009 H1N1 pan- estimated transmission rate prior to travel of viral identification assays suggest that ca- demic influenza, it will also spread globally and restrictions (Table 2). The fraction of all in- pacity for identifying previously missed infec- become a fifth endemic coronavirus within the fections that were documented, a, was esti- tions has increased. Further, general population human population. mated to be 0.65 (95% CI: 0.60–0.69), i.e., 65% of and government response efforts have in- REFERENCES AND NOTES infections were documented during period 1, creased the use of face masks, restricted travel, 1. National Health Commission of the People’s Republic of China,

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Li et al., Science 368, 489–493 (2020) 1 May 2020 4of5 RESEARCH | RESEARCH ARTICLE

http://virological.org/t/epidemiological-data-from-the-ncov-2019- the data. S.P. performed the analysis. R.L., S.P., W.Y., and J.S. party; obtain authorization from the rights holder before using outbreak-early-descriptions-from-publicly-available-data/337. wrote the first draft of the manuscript. B.C., Y.S., and T.Z. reviewed such material. 18. C. Fraser, S. Riley, R. M. Anderson, N. M. Ferguson, Proc. Natl. and edited the manuscript. Competing interests: J.S. and Acad. Sci. U.S.A. 101,6146–6151 (2004). Columbia University disclose partial ownership of SK Analytics. J.S. SUPPLEMENTARY MATERIALS 19. S. Pei, SenPei-CU/COVID-19: COVID-19, Version 1, Zenodo also reports receiving consulting fees from Merck and BNI. All science.sciencemag.org/content/368/6490/489/suppl/DC1 (2020); http://doi.org/10.5281/zenodo.3699624. other authors declare no competing interests. Data and materials Materials and Methods availability: All code and data are available in the supplementary Figs. S1 to S26 ACKNOWLEDGMENTS materials and posted online at https://github.com/SenPei-CU/ Tables S1 to S3 Funding: This work was supported by U.S. National Institutes of COVID-19 and (19). This work is licensed under a Creative References (20–37) Health (NIH) grants GM110748 and AI145883. The content is solely Commons Attribution 4.0 International (CC BY 4.0) license, which MDAR Reproducibility Checklist the responsibility of the authors and does not necessarily permits unrestricted use, distribution, and reproduction in any Data S1 represent the official views of the National Institute of General medium, provided the original work is properly cited. To view a Medical Sciences, the National Institute of Allergy and Infectious copy of this license, visit https://creativecommons.org/licenses/ 15 February 2020; accepted 12 March 2020 Diseases, or the NIH. Author contributions: R.L., S.P., B.C., W.Y., by/4.0/. This license does not apply to figures/photos/artwork or Published online 16 March 2020 and J.S. conceived of the study. R.L., B.C., Y.S., and T.Z. curated other content included in the article that is credited to a third 10.1126/science.abb3221 Downloaded from http://science.sciencemag.org/

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Li et al., Science 368, 489–493 (2020) 1 May 2020 5of5 Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2) Ruiyun Li, Sen Pei, Bin Chen, Yimeng Song, Tao Zhang, Wan Yang and Jeffrey Shaman

Science 368 (6490), 489-493. DOI: 10.1126/science.abb3221originally published online March 16, 2020

Undetected cases The virus causing coronavirus disease 2019 (COVID-19) has now become pandemic. How has it managed to spread from China to all around the world within 3 to 4 months? Li et al. used multiple sources to infer the proportion of

early infections that went undetected and their contribution to virus spread. The researchers combined data from Downloaded from Tencent, one of the world's largest social media and technology companies, with a networked dynamic metapopulation model and Bayesian inference to analyze early spread within China. They estimate that ∼86% of cases were undocumented before travel restrictions were put in place. Before travel restriction and personal isolation were implemented, the transmission rate of undocumented infections was a little more than half that of the known cases. However, because of their greater numbers, undocumented infections were the source for ∼80% of the documented cases. Immediately after travel restrictions were imposed, ∼65% of cases were documented. These findings help to explain the lightning-fast spread of this virus around the world.

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Science (print ISSN 0036-8075; online ISSN 1095-9203) is published by the American Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. The title Science is a registered trademark of AAAS. Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works The airborne lifetime of small speech droplets and

their potential importance in SARS-CoV-2 transmission BRIEF REPORT

Valentyn Stadnytskyia, Christina E. Baxb, Adriaan Baxa,1, and Philip Anfinruda,1

aLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520; and bPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104

Edited by Axel T. Brunger, Stanford University, Stanford, CA, and approved May 4, 2020 (received for review April 10, 2020) Speech droplets generated by asymptomatic carriers of severe The amount by which a droplet shrinks upon dehydration acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are in- depends on the fraction of nonvolatile matter in the oral fluid, creasingly considered to be a likely mode of disease transmission. which includes electrolytes, sugars, enzymes, DNA, and rem- Highly sensitive laser light scattering observations have revealed nants of dehydrated epithelial and white blood cells. Whereas that loud speech can emit thousands of oral fluid droplets per pure saliva contains 99.5% water when exiting the salivary second. In a closed, stagnant air environment, they disappear from glands, the weight fraction of nonvolatile matter in oral fluid falls the window of view with time constants in the range of 8 to in the 1 to 5% range. Presumably, this wide range results from 14 min, which corresponds to droplet nuclei of ca. 4 μm diameter, differential degrees of dehydration of the oral cavity during or 12- to 21-μm droplets prior to dehydration. These observations normal breathing and speaking and from decreased salivary confirm that there is a substantial probability that normal speak- gland activity with age. Given a nonvolatile weight fraction in the − ing causes airborne virus transmission in confined environments. 1 to 5% range and an assumed density of 1.3 g·mL 1 for that fraction, dehydration causes the diameter of an emitted droplet COVID-19 | speech droplet | independent action hypothesis | respiratory to shrink to about 20 to 34% of its original size, thereby slowing disease | disease transmission down the speed at which it falls (1, 13). For example, if a droplet with an initial diameter of 50 μm shrinks to 10 μm, the speed at − − t has long been recognized that respiratory viruses can be which it falls decreases from 6.8 cm·s 1 to about 0.35 cm·s 1. The transmitted via droplets that are generated by coughing or ’ I distance over which droplets travel laterally from the speaker s MEDICAL SCIENCES sneezing. It is less widely known that normal speaking also mouth during their downward trajectory is dominated by the produces thousands of oral fluid droplets with a broad size dis- total volume and flow velocity of exhaled air (8). The flow ve- ca. μ μ tribution ( 1 m to 500 m) (1, 2). Droplets can harbor a locity varies with phonation (14), while the total volume and variety of respiratory pathogens, including measles (3) and in- droplet count increase with loudness (9). Therefore, in an envi- Mycobacterium tuberculosis fluenza virus (4) as well as (5). High ronment of stagnant air, droplet nuclei generated by speaking viral loads of severe acute respiratory syndrome coronavirus 2 will persist as a slowly descending cloud emanating from the (SARS-CoV-2) have been detected in oral fluids of coronavirus speaker’s mouth, with the rate of descent determined by the − disease 2019 (COVID-19) positive patients (6), including diameter of the dehydrated speech droplet nuclei. asymptomatic ones (7). However, the possible role of small The independent action hypothesis (IAH) states that each μ speech droplet nuclei with diameters of less than 30 m, which virion has an equal, nonzero probability of causing an infection. potentially could remain airborne for extended periods of time Validity of IAH was demonstrated for infection of insect larvae (1, 2, 8, 9), has not been widely appreciated. by baculovirus (15), and of plants by Tobacco etch virus variants In a recent report (10), we used an intense sheet of laser light that carried green fluorescent protein markers (16). IAH applies to visualize bursts of speech droplets produced during repeated to systems where the host is highly susceptible, but the extent to spoken phrases. This method revealed average droplet emission − which IAH is valid for humans and SARS-CoV-2 has not yet rates of ca. 1,000 s 1 with peak emission rates as high as −1 been firmly established. For COVID-19, with an oral fluid av- 10,000 s , with a total integrated volume far higher than in 6 erage virus RNA load of 7 × 10 copies per milliliter (maximum previous reports (1, 2, 8, 9). The high sensitivity of the light of 2.35 × 109 copies per milliliter) (7), the probability that a scattering method in observing medium-sized (10 μm to 100 μm) 50-μm-diameter droplet, prior to dehydration, contains at least droplets, a fraction of which remain airborne for at least 30 s, one virion is ∼37%. For a 10-μm droplet, this probability drops to likely accounts for the large increase in the number of observed 0.37%, and the probability that it contains more than one virion, droplets. Here, we derive quantitative estimates for both the if generated from a homogeneous distribution of oral fluid, is number and size of the droplets that remain airborne. Larger negligible. Therefore, airborne droplets pose a significant risk droplets, which are also abundant but associated with close- proximity direct virus transfer or fomite transmission (11), or only if IAH applies to human virus transmission. Considering which can become resuspended in air at a later point in time that frequent person-to-person transmission has been reported (12), are not considered here. in community and health care settings, it appears likely that IAH According to Stokes’ law, the terminal velocity of a falling droplet scales as the square of its diameter. Once airborne, speech-generated droplets rapidly dehydrate due to evaporation, Author contributions: C.E.B., A.B., and P.A. designed research; V.S., A.B., and P.A. per- formed research; V.S. analyzed data; and C.E.B., A.B., and P.A. wrote the paper. thereby decreasing in size (13) and slowing their fall. The probability that a droplet contains one or more virions scales The authors declare no competing interest. with its initial hydrated volume, that is, as the cube of its di- This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY). ameter, d. Therefore, the probability that speech droplets pass Data deposition: Movies that show the experimental setup and the full 85-minute obser- on an infection when emitted by a virus carrier must take into vation of speech droplet nuclei have been deposited at Zenodo and can be accessed at account how long droplet nuclei remain airborne (proportional https://doi.org/10.5281/zenodo.3770559. −2 to d ) and the probability that droplets encapsulate at least one 1To whom correspondence may be addressed. Email: [email protected] or philip.anfinrud@ 3 virion (proportional to d ), the product of which is proportional nih.gov. to d. First published May 13, 2020.

www.pnas.org/cgi/doi/10.1073/pnas.2006874117 PNAS | June 2, 2020 | vol. 117 | no. 22 | 11875–11877 Downloaded by guest on July 24, 2020 applies to COVID-19 and other highly contagious airborne re- scattered light intensity to the size of the scattering particle be- spiratory diseases, such as influenza and measles. cause the light intensity varies across the sheet. However, the brightest 25% were found to decay more quickly than the dim- Results and Discussion mer fraction, with the two curves reasonably well described by The output from a green (532 nm) Coherent Verdi laser oper- exponential decay times of 8 and 14 min, respectively (Fig. 1A). ating at 4-W optical power was transformed with spherical and These fits indicate that, near time 0, there were, on average, cylindrical optics into a light sheet that is ∼1 mm thick and approximately nine droplet nuclei in the 30-cm3 observation 150 mm tall. This light sheet passed through slits centered on window, with the larger and brighter nuclei (on average) falling opposite sides of a cubic 226-L enclosure. When activated, a to the bottom of the enclosure at faster speeds than the smaller 40-mm, 12-V muffin fan inside the enclosure spatially homoge- and dimmer ones. nizes the distribution of particles in the enclosure. A movie With the assumption that the contents of the box are ho- showing the arrangement is available (17). Movie clips of speech mogenized by the muffin fan at time 0, the average number of droplet nuclei were recorded at a frame rate of 24 Hz with high- droplets found in a single frame near time 0 corresponds to ca. definition resolution (1,920 × 1,080 pixels). The camera lens 66,000 small droplets emitted into the 226-L enclosure, or ca. provided a horizontal field of view of ∼20 cm. Therefore, the 2,600 small droplet nuclei per second of speaking. If the particle volume intercepted by the light sheet and viewed by the camera size distribution were a delta function and the particles were is ∼30 cm3. The total number of particles in the enclosure can be uniformly distributed in the enclosure, the particle count would approximated by multiplying the average number of particles be expected to remain constant until particles from the top of the detected in a single movie frame by the volume ratio of the en- enclosure descend to the top of the light sheet, after which the closure to the visualized sheet, which is ∼7,300. Slow convection particle count would decay linearly to background level. The currents, at speeds of a few centimeters per second, remained for observation that the decay profiles are approximately exponen- the duration of the recording. These convection currents are at- tial points to a substantial heterogeneity in particle sizes, even tributed to a 0.5 °C temperature gradient in the enclosure (bottom after binning them into two separate groups. − to top) that presumably is due to heat dissipated by the iPhone11 The weighted average decay rate (0.085 min 1) of the bright camera, which was attached to the front side of the enclosure. Since and dim fractions of particles (Fig. 1A) translates into a half-life the net air flux across any horizontal plane of the enclosure is zero, in the enclosure of ca. 8 min. Assuming this half-life corresponds this convection does not impact the average rate at which droplet to the time required for a particle to fall 30 cm (half the height of − nuclei fall to the bottom of the enclosure. the box), its terminal velocity is only 0.06 cm·s 1, which corre- With the internal circulation fan turned on, the enclosure was sponds to a droplet nucleus diameter of ∼4 μm. At the relative purged with HEPA-filtered air for several minutes. Then, the humidity (27%) and temperature (23 °C) of our experiment, we purge shutter was closed, the movie clip was started, the speaker expect the droplets to dehydrate within a few seconds. A dehy- port was opened, and the enclosure was “filled” with speech drated particle of 4 μm corresponds to a hydrated droplet of ca. droplets by someone repeating the phrase “stay healthy” for 25 s. 12- to 21-μm diameter, or a total hydrated volume of ∼60 nL This phrase was chosen because the “th” phonation in the word to 320 nL for 25 s of loud speaking. At an average viral load of “healthy” was found to be an efficient generator of oral fluid 7 × 106 per milliliter (7), we estimate that 1 min of loud speaking speech droplets. The internal fan was turned off 10 s after speech generates at least 1,000 virion-containing droplet nuclei that was terminated, and the camera continued recording for 80 min. remain airborne for more than 8 min. These therefore could be The movie clip was analyzed frame by frame to determine the inhaled by others and, according to IAH, trigger a new SARS-CoV-2 number of spots/streaks whose maximum single-pixel intensity infection. exceeded a threshold value of 30. Fig. 1 charts the time- The longest decay constant observed by us corresponds to dependent decrease in the number of scattering particles de- droplets with a hydrated diameter of ≥12 μm when exiting tected. We are not yet able to quantitatively link the observed the mouth. The existence of even smaller droplets has been

AB

Fig. 1. Light scattering observation of airborne speech droplet nuclei, generated by a 25-s burst of repeatedly speaking the phrase “stay healthy” in a loud

voice (maximum 85 dBB at a distance of 30 cm; average 59 dBB). (A) Chart of particle count per frame versus time (smoothed with a 24-s moving average), with the red curve representing the top 25% in scattering brightness and the green curve representing the rest. The bright fraction (red) decays with a time constant of 8 min, and the dimmer fraction (green) decays with a time constant of 14 min. Both exponential decay curves return to their respective back- ground level of ca. 0 (red horizontal dashed line) and 0.4 (green dashed line) counts per frame. Time “0” corresponds to the time the stirring fan was turned off. The 25-s burst of speaking started 36 s before time 0. The black arrow (at 0.5 min) marks the start of the exponential fits. (B) Image of the sum of 144 consecutive frames (spanning 6 s) extracted shortly after the end of the 25-s burst of speaking. The dashed circle marks the needle tip used for focusingthe camera. The full movie recording is available in ref. 17, with time “0” in the graph at time point 3:38 in the movie.

11876 | www.pnas.org/cgi/doi/10.1073/pnas.2006874117 Stadnytskyi et al. Downloaded by guest on July 24, 2020 established by aerodynamic particle sizer (APS) measurements load shows large patient-to-patient variation. Some patients have (2). APS is widely used for detecting aerosol particulates and is viral titers that exceed the average titer of Wölfel et al. by more best suited for particles in the 0.5- to 5-μm range. Morawska than two orders of magnitude (7, 18), thereby increasing the BRIEF REPORT et al. (2) detected as many as 330 particles per second in the 0.8- number of virions in the emitted droplets to well over 100,000 to 5.5-μm range upon sustained “aah” vocalization. Considering per minute of speaking. The droplet nuclei observed in our the short travel time (0.7 s) between exiting the mouth and the present study and previously by APS (2, 9) are sufficiently small APS detector, and the high relative humidity (59%) used in that to reach the lower respiratory tract, which is associated with an study, droplet dehydration may have been incomplete. If it were μ increased adverse disease outcome (19, 20). 75% dehydrated at the detector, an observed 5.5- m particle Our laser light scattering method not only provides real-time would have started as an 8.7-μm droplet when exiting the mouth, μ visual evidence for speech droplet emission, but also assesses well outside the 12- to 21- m range observed above by light their airborne lifetime. This direct visualization demonstrates scattering. This result suggests that APS and light scattering how normal speech generates airborne droplets that can remain measurements form a perfect complement. However, we also note that, even while the smallest droplet nuclei effectively re- suspended for tens of minutes or longer and are eminently ca- main airborne indefinitely and have half-lives that are dominated pable of transmitting disease in confined spaces. by the ventilation rate, at a saliva viral load of 7 × 106 copies per Data Availability Statement. All raw data used for analysis are milliliter, the probability that a 1-μm droplet nucleus (scaled back to its originally hydrated 3-μm size) contains a virion is available in ref. 17. only 0.01%. ACKNOWLEDGMENTS. We thank Bernhard Howder for technical support, Our current setup does not detect every small particle in each Clemens Wendtner, William A. Eaton, Roland Netz, and Steven Chu for in- frame of the movie, and our reported values are therefore con- sightful comments. This work was supported by the Intramural Research Pro- servative lower limit estimates. We also note that the saliva viral gram of the National Institute of Diabetes and Digestive and Kidney Diseases.

1. J. P. Duguid, The size and the duration of air-carriage of respiratory droplets and 10. P. Anfinrud, V. Stadnytskyi, C. E. Bax, A. Bax, Visualizing speech-generated oral fluid droplet-nuclei. J. Hyg. (Lond.) 44, 471–479 (1946). droplets with laser light scattering. N. Engl. J. Med., 10.1056/NEJMc2007800 (2020). 2. L. Morawska et al., Size distribution and sites of origin of droplets expelled from the 11. T. Raymond, Review of aerosol transmission of Influenza A virus. Emerging Infect. Dis. human respiratory tract during expiratory activities. J. Aerosol Sci. 40, 256–269 (2009). J. 12, 1657–1662 (2006). 3. L. Liljeroos, J. T. Huiskonen, A. Ora, P. Susi, S. J. Butcher, Electron cryotomography of 12. Y. Liu et al., Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals. Nature, measles virus reveals how matrix protein coats the ribonucleocapsid within intact 10.1038/s41586-020-2271-3 (2020). MEDICAL SCIENCES virions. Proc. Natl. Acad. Sci. U.S.A. 108, 18085–18090 (2011). 13. W. F. Wells, On air-borne infection—Study II droplets and droplet nuclei. Am. J. Hyg. 4. J. Yan et al.; EMIT Consortium, Infectious virus in exhaled breath of symptomatic 20, 611–618 (1934). seasonal influenza cases from a college community. Proc. Natl. Acad. Sci. U.S.A. 115, 14. H. Traunmüller, A. Eriksson, Acoustic effects of variation in vocal effort by men, 1081–1086 (2018). women, and children. J. Acoust. Soc. Am. 107, 3438–3451 (2000). 5. K. P. Fennelly et al., Variability of infectious aerosols produced during coughing by 15. M. P. Zwart et al., An experimental test of the independent action hypothesis in virus- patients with pulmonary tuberculosis. Am. J. Respir. Crit. Care Med. 186, 450–457 insect pathosystems. Proc. Biol. Sci. 276, 2233–2242 (2009). (2012). 16. M. P. Zwart, J. A. Daròs, S. F. Elena, One is enough: In vivo effective population size is 6. J. F.-W. Chan et al., Improved molecular diagnosis of COVID-19 by the novel, highly dose-dependent for a plant RNA virus. PLoS Pathog. 7, e1002122 (2011). sensitive and specific COVID-19-RdRp/Hel real-time reverse transcription-polymerase 17. V. Stadnytskyi, P. Anfinrud, C. E. Bax, A. Bax, The airborne lifetime of small speech chain reaction assay validated in vitro and with clinical specimens. J. Clin. Microbiol. droplets and their potential importance to SARS-CoV-2 transmission. Zenodo. https:// 58, e00310-20 (2020). doi.org/10.5281/zenodo.3770559. Deposited 10 April 2020. 7. R. Wölfel et al., Virological assessment of hospitalized patients with COVID-2019. 18. C. Rothe et al., Transmission of 2019-nCoV infection from an asymptomatic contact in Nature, 10.1038/s41586-020-2196-x (2020). Germany. N. Engl. J. Med. 382, 970–971 (2020). 8. C. Y. H. Chao et al., Characterization of expiration air jets and droplet size distribu- 19. R. Tellier, Y. Li, B. J. Cowling, J. W. Tang, Recognition of aerosol transmission of in- tions immediately at the mouth opening. J. Aerosol Sci. 40, 122–133 (2009). fectious agents: A commentary. BMC Infect. Dis. 19, 101 (2019). 9. S. Asadi et al., Aerosol emission and superemission during human speech increase 20. R. J. Thomas, Particle size and pathogenicity in the respiratory tract. Virulence 4, 847– with voice loudness. Sci. Rep. 9, 2348 (2019). 858 (2013).

Stadnytskyi et al. PNAS | June 2, 2020 | vol. 117 | no. 22 | 11877 Downloaded by guest on July 24, 2020 Goldman Sachs Research Face Masks and GDP

29 JUN 2020 TOPICS: COVID-19 | ECONOMIC OUTLOOKS

New US coronavirus cases have risen sharply in recent weeks, leading investors to worry that renewed lockdowns will again depress economic activity. But since the first infection wave in March and April, it has become clear that broad lockdowns are not the only way to lower virus transmission, and many governments have started to require the wearing of face masks in public settings. Should the United States follow suit with a national mandate? This is inherently a political decision, but we can use our analytical tools to answer three questions that are relevant to it. First, how effective is a face mask mandate in increasing face mask usage? Second, does increased face mask usage lower virus transmission, and if so by how much? And third, how economically valuable is a face mask mandate in terms of reducing the need for broad lockdowns with their well-documented negative effects on GDP?

• The sharp increase in confirmed coronavirus cases in the US Sun Belt has led investors to worry about renewed broad lockdowns with large negative effects on GDP. But there are also other ways to reduce infections, including stringent bans on large gatherings and greater use of face masks. • In particular, we argue that a national face mask mandate could partially substitute for renewed lockdowns. We start by showing that a national mandate would likely increase face mask usage meaningfully, especially in states such as Florida and Texas where masks remain largely voluntary to date. • We then investigate the link between face masks and coronavirus outcomes. Our analysis includes 1) a US regional panel in which we relate the growth rate of infections and fatalities to the introduction of state face mask mandates, 2) a large country-level cross section in which we relate cumulative infections and fatalities to the lag between the onset of spread and the introduction of a face mask mandate, and 3) a smaller country-level panel in which we relate the growth rate of infections and fatalities to lagged mask usage. • We find that face masks are associated with significantly better coronavirus outcomes. Since this is true across all three of our models and the results are robust to the inclusion of a number of control variables, it seems to reflect a largely causal impact of masks rather than correlation with other factors (such as reduced mobility or avoidance of large gatherings). Our baseline estimate is that a national mandate could raise the percentage of people who wear masks by 15pp and cut the daily growth rate of confirmed cases by 1.0pp to 0.6%. • Finally, we translate our results into GDP terms by asking how much our Effective Lockdown Index (ELI) would need to increase in order to cut infections by as much as a national mask mandate, and then converting the ELI impact into a GDP impact using the estimated cross- country relationship between the two. These calculations imply that a face mask mandate could potentially substitute for lockdowns that would otherwise subtract nearly 5% from GDP.

Face Masks and GDP [1]

New US coronavirus cases have risen sharply in recent weeks, with most of the deterioration concentrated in the “Sun Belt,” including Florida, Texas, Arizona, and California. This has led investors to worry that renewed lockdowns will again depress economic activity. By our estimates, the increase in our Effective Lockdown Index (ELI)—a combination of official restrictions and actual social distancing data—subtracted 17% from US GDP between January and April, and other countries with even more aggressive restrictions saw even larger economic effects.

Since the first infection wave in March and April, however, it has become clear that broad lockdowns are not the only way to lower virus transmission significantly. For one thing, public health experts have long believed that bans on large gatherings can bring disproportionate benefits. This belief has only grown with a multitude of studies documenting the importance of “super spreader” events, such as those associated with the Shinjeonji Church in South Korea, the Austrian ski resort Ischgl, various European soccer matches, and the celebrations in New Orleans for Mardi Gras.

A more abrupt shift has occurred in the official view on face masks. As late as March 30, the World Health Organization advised that there was “no specific evidence to suggest that the wearing of masks by the mass population has any potential benefit.”[2] Since then, however, the public health community’s thinking has changed dramatically and many governments have started to require the wearing of face masks.

Should the United States follow these countries and adopt a national face mask mandate? This is inherently a political decision, but we can use our analytical tools to answer three questions that are relevant to it. First, how effective is a face mask mandate in increasing face mask usage? Second, does increased face mask usage lower virus transmission, and if so by how much? And third, how economically valuable is a face mask mandate in terms of reducing the need for broad lockdowns with their well-documented negative effects on GDP?

Face Mask Mandates and Usage

At present, the United States is among the less restrictive countries with respect to face mask mandates. The federal government did issue a national “recommendation” to wear masks in public settings in April, and many state and local governments have taken more stringent measures. However, a recommendation is not a mandate and the governors of both Florida and Texas—the two most heavily affected large states—recently reiterated their opposition to a statewide mask mandate. By contrast, many European countries now have national mask mandates in place, as shown in Exhibit 1, and much of East Asia has strong social norms of mask wearing when sick and during pandemics.

What about actual mask usage? In this respect, the US scores somewhat better than one might expect, at least when looking at the national self-reported average. As shown in Exhibit 2, the share of respondents saying that they wear a face mask in public is nearly 90% in East Asia, 80% in Southern Europe, just below 70% in the US and Germany, 30% in the UK, and as low as 10% in Scandinavia. Most countries, including the US, have seen large increases in self-reported mask usage since the start of the pandemic.

However, the national data don’t tell the full story. As shown in Exhibit 3, face mask usage is highest in the Northeast, where the virus situation has improved dramatically in recent months, and generally lower in the South, where the numbers have deteriorated.[3] For example, only about 40% of respondents in Arizona say that they “always” wear face masks in public, compared with nearly 80% in Massachusetts.

How effective would a national mask mandate be in pushing mask usage to Southern European or East Asian levels? To investigate this, we turn to a statistical event study that relates the adoption of mask mandates across US states to subsequent changes in self- reported mask usage.

We analyze the impact of face mask mandates issued by 20 US states plus DC between April 8 and June 24 in a state panel. We collect the announcement dates of mask mandates from a study in Health Affairs by Wei Lyu and George Wehby and construct statewide time series of face mask usage outside the home using YouGov Covid-19 Behaviour Tracker respondent-level data. We regress state-level mask usage on various event time dummies around the announcement and include state fixed effects and time fixed effects.[4]

Exhibit 4 shows our estimates of a large and highly significant impact of mandates on mask usage. We estimate that statewide mask mandates gradually raise the percentage of people who “always” or “frequently” wear masks by around 25pp in the 30+ days after signing (left panel). The percent of respondents who “always” wear masks rises by nearly 40pp 30+ days after, reflecting some people switching from “frequently” and other categories to “always” (right panel).

Exhibit 4 suggests that a national mask mandate could increase US face mask usage by statistically significant and economically large amounts, especially in states such as Florida and Texas that currently don’t have a comprehensive mandate and are seeing some of the worst outbreaks. Specifically, we estimate that a national mandate would increase the national average share of people who “always” or “frequently” wear masks by 15pp. This estimate is based on two assumptions. First, we assume that states that currently don’t have a mandate—which account for 50% of the population—experience a 25pp rise in mask usage in line with the average response to statewide mandates. Second, we assume that states which already have a state mandate see a 5pp increase in mask usage because of increased focus on the issue.

Face Masks and Virus Outcomes

Approach 1: US County Panel Does increased face mask usage lower virus transmission, and if so by how much? To investigate this, we turn to three statistical approaches relating face mask usage and mandates to virus spread and fatalities.

Our first approach extends our event study analysis of US state-level mandates to the impact on the growth rate of infections and fatalities. Specifically, we regress county-level growth rates of infections and fatalities on event time dummies around the announcement and control for state fixed effects, time fixed effects, and a rich set of county-level controls.[5] As shown in Exhibit 5, we estimate that face mask mandates have large and highly statistically significant effects on health outcomes. Our estimates imply that mask mandates lower the infection growth rate by 1.3pp in the 11-15 days after announcement. Relative to the 5.4% average infection growth rate prior to announcement, the growth rate of infections is cut by 25%. We also estimate significant and somewhat larger declines in the growth rate of COVID-19 fatalities of 2.4pp in the 11-15 days after announcement and of 3.7pp in the 21-29 days after.

Approach 2: Large Country Cross-Section Our second approach is a large country cross section in which we relate cumulative case counts and fatalities to the lag between the onset of spread and the introduction of a face mask mandate, building on a study by Christopher Leffler and co-authors.

Exhibit 6 presents the descriptive relationships graphically by plotting the length of the outbreak before masks were widely adopted against cumulative cases per capita (left panel) and cumulative fatalities per capita (right panel). We measure the start of the outbreak as the day of the first fatality. Both graphs show a positive and statistically significant slope, indicating that countries which took longer to reach widespread mask usage (whether by policy or cultural norms) suffered more virus cases and fatalities. The better fit for fatalities than cases likely reflects the relatively better measurement of fatalities.

To formalize this finding, Exhibit 7 presents cross-sectional regression models of log cases and log fatalities for around 125 countries. In both regressions, we find statistically significant negative effects of masks on cumulative cases and fatalities after including controls such as the obesity rate, population density, age structure, and testing policy. Our numerical estimates are that cumulative cases grow 17.3% per week without a mask mandate but only 7.3% with a mask mandate, and that cumulative fatalities grow 29% per week without a mask mandate but only 16% with a mask mandate.

Approach 3: Country Panel Our third approach consists of a smaller country panel in which we relate the daily growth rate of infections and fatalities to lagged self-reported mask usage, plus a number of control variables. There are three main results, illustrated in Exhibit 8.

First, face masks have a large negative impact on infections and fatalities, controlling for population density and income inequality (columns 1 and 4). This negative and significant impact of face masks is robust to controlling for our Effective Lockdown Index (ELI), the share of the population that say they avoid crowded public places (columns 2 and 5), and country and time fixed effects (columns 3 and 6). Our estimates suggest that a 25pp increase in the self-reported mask usage, for instance as a result of a mask mandate, lowers the growth rate of cumulative cases by 1.9pp and the growth rate of cumulative fatalities by 0.8pp.[6]

Second, the share of respondents that avoid crowded public places also has a large and highly significant negative impact on infections and fatalities. This not only suggests a significant role for “super spreader” events, but also strengthens our main results because it implies that the face mask result is not just driven by the correlation between face masks and other risky activities.

Third, the virus impact of mask usage is large, not just in absolute terms but also relative to the effect of economically costly shutdowns (as measured by our ELI). In fact, the coefficients on the percentage of self-reported mask usage are slightly bigger than those on the ELI, which is interesting as both variables are on a 0-100 scale.

The Impact of a Mandate on Infections

Before we translate our statistical results into a baseline estimate of the impact of face mask mandates on virus outcomes, we need to address two potential concerns about our analysis up front.

The first concern is that the correlation between face masks and virus outcomes might reflect the effect of other unobserved forms of cautious behavior that are correlated with mask mandates or usage, instead of a truly causal effect of masks. But there are some reasons to believe that this type of bias in not a big issue for our analysis. Not only do we obtain remarkably similar estimates across our three approaches, but we also control for a number of other observable forms of cautious behavior. Specifically, our cross-country results on masks include our Effective Lockdown Index among the explanatory variables, and they are largely unchanged when we include the share of respondents who say they stay home from work, don’t touch objects, improve personal hygiene, avoid contact with tourists, avoid raw meat, and don’t send their children to school.[7]

The second potential concern is that our main results are based on confirmed infections, which can be distorted by a lack of testing. However, it is important to note that this would, if anything, lead to an understatement of the effect assuming that increases in testing are positively correlated with increases in mask usage. Moreover, we control for testing regime indicators in our cross-sectional regression, and we obtain generally similar estimates for fatalities—which are better measured—across all three of our approaches.

So what is a reasonable baseline estimate of the impact of a US national mask mandate on the growth rate of confirmed infections? To generate such an estimate, we apply our country panel results separately to two groups of US states, namely ones with and without a state-level mask mandate in place.

States that currently don’t have a state-level mandate account for 40% of US total confirmed cases, 45% of US GDP, half of the population, and two-thirds of new infections. This group has also experienced an average daily growth rate in confirmed infections of 2.9% in the past 7 days. Based on our analysis of state-level mandates, we estimate that a national mask mandate would raise mask usage by 25pp in these states. Our country panel shows that a 25pp increase in self-reported mask usage lowers the infection growth rate by 1.9pp (or just over 60%). The national mandate could therefore lower the daily growth rate in the group of states without a mandate from 2.9% to just over 1%.

States that currently do have a mandate have experienced a lower average daily growth rate in confirmed infections of 0.8% in the past 7 days. Combined with our assumption that a national mandate would lead to a smaller increase in mask usage of 5pp through extra awareness in this group of states, our country panel suggests a 0.4pp decline in the infection growth rate to 0.4-0.5%.

Combining the estimates for these two groups of states, we estimate that a national mandate could cut the national average growth rate of infections by nearly 1.0pp to 0.6- 0.7%.

The Impact of a Mandate on GDP

If a face mask mandate meaningfully lowers coronavirus infections, it could be valuable not only from a public health perspective but also from an economic perspective because it could substitute for renewed lockdowns that would otherwise hit GDP.

How big is this potential effect? To generate an answer, we proceed in two steps. First, we use our cross-country panel analysis to ask how much our effective lockdown index (ELI) would need to increase in order to lower the daily case growth rate by 1.0pp, i.e. the estimated impact of a national face mask mandate. The answer is an increase in our ELI of 16pp.

Second, we ask how much a 16pp ELI increase would subtract from the level of GDP. As shown in Exhibit 9, the cross-country relationship implies that such an increase might reduce GDP by just under 5%.

Thus, the upshot of our analysis is that a national face mask mandate could potentially substitute for renewed lockdowns that would otherwise subtract nearly 5% from GDP. It is important to recognize that this estimate is quite uncertain because it is based on a number of statistical relationships that are all measured with error. Despite the numerical uncertainty, however, our analysis suggests that the economic benefit from a face mask mandate and increased face mask usage could be sizable.

So will the US adopt a national face mask mandate? This is uncertain, partly because masks have become such a politically and culturally charged issue. However, even in the absence of a national mandate, state and local authorities might well broaden mandates in ways that ultimately mimic the impact of a national mandate. Either way, our analysis suggests that the economy could benefit significantly from such moves, especially when compared with the alternative of a return to broader lockdowns.

Jan Hatzius

Daan Struyven

Isabella Rosenberg

1 We thank Sid Bhushan and Dan Milo for valuable help with this report. 2 See Jaqueline Howard, “WHO stands by recommendation to not wear masks if you are not sick,” CNN, March 30, 2020. 3 As an aside, note that Minnesota has the lowest self-reported rate of mask usage among larger states in the US. This is interesting because the state is home to a large population of Scandinavian-Americans and Scandinavia has some of the lowest rates of face mask usage in the world. 4 Our mask usage regressions are weighted by state population, focus on states with more than 4 million people (given the small samples in the respondent-level data) and use robust standard errors at the state level. Our sample starts on April 2nd when respondent-level data become available. We also control for cumulative cases per million and cumulative deaths per million. 5 The county-level controls are population density, median house value, median household income, homeownership, pollution, maximum summer temperature, and maximum winter temperature, educational attainment, mean Body Mass Index, and the share of population over 65. We use county population weights and cluster robust standard errors at the state level. Our sample covers 2,373 counties and extends from March 31 to June 24. See Lyu and Wehby (2020). 6 Relative to the sample average growth rates of 3.8% and 2.8%, these estimates imply that a mask mandate raising mask usage by 25pp cuts the growth rates of infections and fatalities by nearly one half and one quarter respectively. 7 The cross-country panel and cross-county panel results are also robust to controlling for the lagged levels of fatalities and infections per capita, which helps address the concern that the mask effects pick up the impact of other forms of unobserved cautious behavior in response to the size of the outbreak.

Annals of Internal Medicine LETTERS

RETRACTION

Notice of Retraction: Effectiveness of Surgical and Cotton Masks in Blocking SARS-CoV-2 According to recommendations by the editors of Annals of Internal Medicine, we are retracting our article, “Effective- ness of Surgical and Cotton Masks in Blocking SARS-CoV-2. A Controlled Comparison in 4 Patients,” which was published on Annals.org on 6 April 2020 (1). We had not fully recognized the concept of limit of de- tection (LOD) of the in-house reverse transcriptase polymer- ase chain reaction used in the study (2.63 log copies/mL), and we regret our failure to express the values below LOD as “

Seongman Bae, MD Min-Chul Kim, MD Ji Yeun Kim, PhD Hye-Hee Cha, BS Joon Seo Lim, PhD Jiwon Jung, MD Min-Jae Kim, MD Dong Kyu Oh, MD Mi-Kyung Lee, MD Seong-Ho Choi, MD Minki Sung, PhD Sang-Bum Hong, MD Jin-Won Chung, MD Sung-Han Kim, MD doi:10.7326/L20-0745

Reference 1. Bae S, Kim MC, Kim JY, et al. Effectiveness of surgical and cotton masks in blocking SARS-CoV-2: a controlled comparison in 4 patients. Ann Intern Med. 6 April 2020. [Epub ahead of print]. [PMID: 32251511] doi:10.7326/M20 -1342

This article was published at Annals.org on 2 June 2020.

Annals.org Annals of Internal Medicine © 2020 American College of Physicians Annals of Internal Medicine LETTERS

OBSERVATION:BRIEF RESEARCH REPORT cotton mask, and again with no mask. A separate petri dish was used for each of the 5 coughing episodes. Mask surfaces were swabbed with aseptic Dacron swabs in the following Effectiveness of Surgical and Cotton Masks in Blocking sequence: outer surface of surgical mask, inner surface of sur- SARS–CoV-2: A Controlled Comparison in 4 Patients gical mask, outer surface of cotton mask, and inner surface of cotton mask. Background: During respiratory viral infection, face masks The median viral loads of nasopharyngeal and saliva sam- are thought to prevent transmission (1). Whether face masks ples from the 4 participants were 5.66 log copies/mL and 4.00 worn by patients with coronavirus disease 2019 (COVID-19) prevent contamination of the environment is uncertain (2, 3). log copies/mL, respectively. The median viral loads after A previous study reported that surgical masks and N95 masks coughs without a mask, with a surgical mask, and with a cot- were equally effective in preventing the dissemination of in- ton mask were 2.56 log copies/mL, 2.42 log copies/mL, and fluenza virus (4), so surgical masks might help prevent trans- 1.85 log copies/mL, respectively. All swabs from the outer mission of severe acute respiratory syndrome–coronavirus 2 mask surfaces of the masks were positive for SARS–CoV-2, (SARS–CoV-2). However, the SARS–CoV-2 pandemic has con- whereas most swabs from the inner mask surfaces were neg- tributed to shortages of both N95 and surgical masks, and ative (Table). cotton masks have gained interest as a substitute. Discussion: Neither surgical nor cotton masks effectively Objective: To evaluate the effectiveness of surgical and filtered SARS–CoV-2 during coughs by infected patients. Prior cotton masks in filtering SARS–CoV-2. evidence that surgical masks effectively filtered influenza virus Methods and Findings: The institutional review boards of (1) informed recommendations2020 that patients with confirmed 2 hospitals in Seoul, South Korea, approved the protocol, and or suspected COVID-19 should wear face masks to prevent we invited patients with COVID-19 to participate. After provid- transmission (2). However, the size and concentrations of ing informed consent, patients were admitted to negative SARS–CoV-2 in aerosols generated during coughing are un- pressure isolation rooms. We compared disposable surgical known. Oberg and Brousseau (3) demonstrated that surgical masks (180 mm × 90 mm, 3 layers [inner surface mixed with masks did not exhibit adequate filter performance against polypropylene and polyethylene, polypropylene filter, and aerosols measuring 0.9, 2.0, and 3.1 μm in diameter. Lee and polypropylene outer surface], pleated, bulk packaged in card- colleagues (4)JUNE showed that particles 0.04 to 0.2 μm can pen- board; KM Dental Mask, KM Healthcare Corp) with reusable etrate surgical masks. The size of the SARS–CoV particle from 100% cotton masks (160 mm × 135 mm, 2 layers, individually the 2002–20042 outbreak was estimated as 0.08 to 0.14 μm (5); packaged in plastic; Seoulsa). assuming that SARS-CoV-2 has a similar size, surgical masks A petri dish (90 mm × 15 mm) containing 1 mL of viral are unlikely to effectively filter this virus. transport media (sterile phosphate-buffered saline with bo- Of note, we found greater contamination on the outer vine serum albumin, 0.1%; penicillin, 10 000 U/mL; streptomy- ONthan the inner mask surfaces. Although it is possible that virus cin, 10 mg; and amphotericin B, 25 μg) was placed approxi- particles may cross from the inner to the outer surface be- mately 20 cm from the patients' mouths. Patients were cause of the physical pressure of swabbing, we swabbed the instructed to cough 5 times each onto a petri dish while wear- outer surface before the inner surface. The consistent finding ing the following sequence of masks: no mask, surgical mask, of virus on the outer mask surface is unlikely to have been

Table. SARS–CoV-2 Viral Load in Patient Samples, Petri Dishes, and Mask Surfaces

Characteristic Patient 1 Patient 2 Patient 3 Patient 4 (Hospital A) (Hospital A) (Hospital B) (Hospital B) Age, y 61 62 35 82 Sex Male Female Male Female Clinical diagnosis Pneumonia Upper respiratory infection Upper respiratory infection Pneumonia with ARDS Symptom onset before admission, d 24* 4 5 10 Timing of the mask test, hospital days 84 2 14 Viral load, log copies/mLRETRACTED Nasopharyngeal swab 7.68 5.42 5.98 3.57 Saliva 4.29 2.59 5.91 3.51 Petri dish Coughing without a mask (before control) 3.53 2.14 2.52 ND Coughing with a surgical mask 3.26 1.80 2.21 ND Coughing with a cotton mask 2.27 ND 1.42 ND Coughing without a mask (after control) 3.23 2.06 2.64 2.44 Mask surface Outer surface of surgical mask 2.21 2.11 2.63 2.59 Inner surface of surgical mask ND ND 2.00 ND Outer surface of cotton mask 2.76 2.66 3.61 2.58 Inner surface of cotton mask ND ND 3.70 ND ARDS = acute respiratory distress syndrome; ND = not detected; SARS–CoV-2 = severe acute respiratory syndrome–coronavirus 2. * Transferred from the other hospital.

This article was published at Annals.org on 6 April 2020.

Annals.org Annals of Internal Medicine © 2020 American College of Physicians 1 LETTERS caused by experimental error or artifact. The mask's aerody- Minki Sung, PhD namic features may explain this finding. A turbulent jet due to Sejong University, Seoul, South Korea air leakage around the mask edge could contaminate the outer surface. Alternatively, the small aerosols of SARS–CoV-2 Sang-Bum Hong, MD generated during a high-velocity cough might penetrate the Asan Medical Center, University of Ulsan College of Medicine, masks. However, this hypothesis may only be valid if the Seoul, South Korea coughing patients did not exhale any large-sized particles, which would be expected to be deposited on the inner sur- Jin-Won Chung, MD face despite high velocity. These observations support the im- Chung-Ang University Hospital, Seoul, South Korea portance of hand hygiene after touching the outer surface of masks. Sung-Han Kim, MD This experiment did not include N95 masks and does not Asan Medical Center, University of Ulsan College of Medicine, reflect the actual transmission of infection from patients with Seoul, South Korea COVID-19 wearing different types of masks. We do not know whether masks shorten the travel distance of droplets during Note: Authors indicated with an asterisk (Drs. Bae, M.-C. Kim, and J.Y. coughing. Further study is needed to recommend whether Kim) contributed equally to this article. face masks decrease transmission of virus from asymptomatic Acknowledgment: The authors thank patients who participated in individuals or those with suspected COVID-19 who are not this study. coughing. 2020 In conclusion, both surgical and cotton masks seem to be Financial Support: By a grant from the Government-wide R&D Fund ineffective in preventing the dissemination of SARS–CoV-2 Project for Infectious Disease Research (GFID), Republic of Korea from the coughs of patients with COVID-19 to the environ- (grant HG18C0037). ment and external mask surface. Disclosures: None. Forms can be viewed at www.acponline.org /authors/icmje/ConflictOfInterestForms.do?msNum=M20-1342. Seongman Bae, MD* JUNE Asan Medical Center, University of Ulsan College of Medicine, Reproducible Research Statement: Study protocol, statistical Seoul, South Korea code, and data set: Available from Dr. Sung-Han Kim (e-mail, [email protected]).2 Min-Chul Kim, MD* Chung-Ang University Hospital, Seoul, South Korea Corresponding Author: Sung-Han Kim, MD, Department of Infec- tious Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea; e-mail, [email protected]. Ji Yeun Kim, PhD* ON Hye-Hee Cha, BS doi:10.7326/M20-1342 Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea References 1. Johnson DF, Druce JD, Birch C, et al. A quantitative assessment of the Joon Seo Lim, PhD efficacy of surgical and N95 masks to filter influenza virus in patients with acute Clinical Research Center, Asan Institute for Life Sciences, Asan influenza infection. Clin Infect Dis. 2009;49:275-277. [PMID: 19522650] doi:10 Medical Center, University of Ulsan College of Medicine, .1086/600041 Seoul, South Korea 2. Feng S, Shen C, Xia N, et al. Rational use of face masks in the COVID-19 pandemic. Lancet Respir Med. 20 March 2020. [Epub ahead of print]. [PMID: Jiwon Jung, MD 32203710] doi:10.1016/S2213-2600(20)30134-X 3. Oberg T, Brosseau LM. Surgical mask filter and fit performance. Am J Infect Min-Jae Kim, MD Control. 2008;36:276-282. [PMID: 18455048] doi:10.1016/j.ajic.2007.07.008 Dong Kyu Oh, MD 4. Lee SA, Grinshpun SA, Reponen T. Respiratory performance offered by N95 Asan Medical Center, University of Ulsan College of Medicine, respirators and surgical masks: human subject evaluation with NaCl aerosol Seoul, South KoreaRETRACTED representing bacterial and viral particle size range. Ann Occup Hyg. 2008;52: 177-185. [PMID: 18326870] doi:10.1093/annhyg/men005 Mi-Kyung Lee, MD 5. Ksiazek TG, Erdman D, Goldsmith CS, et al; SARS Working Group. A novel Seong-Ho Choi, MD coronavirus associated with severe acute respiratory syndrome. N Engl J Med. Chung-Ang University Hospital, Seoul, South Korea 2003;348:1953-1966. [PMID: 12690092]

2 Annals of Internal Medicine Annals.org