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A Modelling Study medRxiv preprint doi: https://doi.org/10.1101/2020.07.03.20144949; this version posted July 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . The projected impact of mitigation and suppression strategies on the COVID-19 epidemic in Senegal: A modelling study Hayley A Thompson1, Aminata Mboup2, Badara Cisse3, 4, Shevanthi Nayagam1,5, Oliver J Watson1, Charles Whittaker1, Patrick G T Walker1, Azra C Ghani1*, Souleymane Mboup2 With the Imperial College COVID-19 Response Team. 1. MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK 2. IRESSEF: Institut de Recherche en Santé de Surveillance Epidemiologique et de Formations, Dakar, Senegal 3. London School of Hygiene and Tropical Medicine, London, UK 4. National Ethics Committee, Ministry of Health, Senegal. 5. Division of Digestive Diseases, Imperial College London, London, UK. *Corresponding authors: Prof Azra Ghani, MRC Centre for Global Infectious Disease Analysis, Imperial College London, London W2 1PG, UK [email protected] NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2020.07.03.20144949; this version posted July 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Abstract Background Physical distancing measures that reduce social contacts have formed a key part of national COVID-19 containment and mitigation strategies. Many Sub-Saharan African nations are now facing increasing numbers of cases of COVID-19 and there is a need to understand what levels of measures may be required to successfully reduce transmission. Methods We collated epidemiological data along with information on key COVID-19 specific response policies and health system capacity estimates for services needed to treat COVID-19 patients in Senegal. We calibrated an age-structured SEIR model to these data to capture transmission dynamics accounting for demography, contact patterns, hospital capacity and disease severity. We simulated the impact of mitigation and suppression strategies focussed on reducing social contact rates. Results Senegal acted promptly to contain the spread of SARS-CoV-2 and as a result has reduced the reproduction number from 1.9 (95% CI 1.7-2.2) to 1.3 (95% CI 1.2-1.5), which has slowed but not fully interrupted transmission. We estimate that continued spread is likely to peak in October, and to overwhelm the healthcare system with an estimated 77,400 deaths (95% CI 55,270-100,700). Further reductions in contact rates to suppress transmission (Rt<1) could significantly reduce this burden on healthcare services and improve overall health outcomes. Conclusions Our results demonstrate that Senegal has already significantly reduced transmission. Enhanced physical distancing measures and rapid scale up of hospital capacity is likely to be needed to reduce mortality and protect healthcare infrastructure from high levels of demand. 2 medRxiv preprint doi: https://doi.org/10.1101/2020.07.03.20144949; this version posted July 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Background COVID-19 disease, caused by the SARS-CoV-2 virus, represents an unprecedented public health emergency. Since the emergence of the virus in China at the end of 2019, worldwide spread has been rapid, with 7,823,289 cases and 431,541 deaths reported as of 15th June 2020.1 The growing burden of COVID-19 in Sub Saharan Africa (SSA) is of particular concern given the relative lack of availability of healthcare. Experience to date has highlighted the substantial pressure COVID-19 epidemics place on health systems, leading to huge demand for therapeutic oxygen and mechanical ventilators, sufficient to overwhelm even comparatively well-resourced settings such as the US where there are an estimated 20-31 intensive care unit (ICU) beds per 100,000 people. In contrast, recent estimates suggest less than 1 ICU bed and 1 ventilator per 100,000 people across SSA.2 In Senegal, following the identification of an imported case, the government set up a response plan covering the period February to July 2020 with several modular phases depending on the epidemiological situation at the time. As of 15th June, Senegal had recorded 5,173 confirmed cases, making it the fourth worst affected country in the Western African region.3 Prevention and control measures taken have included closure of the international airport (20th March) and the declaration of a state of emergency (23rd March) which included the closure of schools and mosques, banning of large public gatherings, travel restrictions and strengthening control over borders.4 In addition, funding for a multisectoral surveillance action/response plan was established. This plan aims to encourage people to adopt the right behaviours through communication strategies but also to strengthen the health system and initiate processes for monitoring activities. Initial testing was slow to scale-up, but now includes testing at health-centres and in the wider community in identified geographical hotspots, alongside contact tracing with isolation of confirmed symptomatic and asymptomatic cases, a total of 62,763 tests have been conducted since early March.3 Previous modelling work has highlighted that despite the younger populations in SSA, a combination of lower quality healthcare and large intergenerational family structures could result in significant morbidity and mortality unless the epidemic is swiftly brought under control.5,6 Whilst generic insights can be obtained from such modelling, country-specific models can be helpful during the early phase of the epidemic in order to guide changes in public health policy. Studies that have examined the potential epidemic trajectory in Senegal specifically are limited, with only two studies published that consider the current emergency measures and their impact on the transmission of the virus.7,8 Both of these studies estimate a significant final epidemic size with between 25-50% of the population infected, however neither of these studies address the impact that health systems capacity can have on COVID- 19 related mortality.5,7 Here we describe the current epidemiological situation using data collected from across the country. We calibrate a dynamical model of COVID-19 transmission to these data to 3 medRxiv preprint doi: https://doi.org/10.1101/2020.07.03.20144949; this version posted July 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . investigate the potential impact of different mitigation and suppression strategies on mortality and health system capacity and explore possible future trajectories of the still nascent epidemic in Senegal. Methods Epidemiological Data and Statistical Analysis We The growth rate from the early phase of an outbreak can be linked to the initial reproduction number.9 We used the R package earlyR to estimate the reproduction number during the early phase of the outbreak in Senegal, noting we are using the date of a reported case as symptom onset data is not available.10,11 Mathematical Model We use a stochastic age-structured SEIR model (Additional file 1: Figure S1) described in Walker et al, available in the form of an R package.6 The model explicitly captures passage through different healthcare settings and includes both age-specific patterns of mixing (derived from contact surveys carried out in SSA and disease severity.12,13 In brief, upon infection, individuals enter a period of latent infection, after which they either develop mild infection (symptomatic or asymptomatic) or severe disease (pneumonia or acute respiratory distress) that requires hospitalisation. Severe cases either require treatment with high-pressure oxygen (captured here as hospital beds) or develop more severe disease that requires intensive care treatment and mechanical ventilation (captured here as ICU beds). The probabilities of an infected individual developing mild infection or severe disease are age dependent and based on estimates of the age-specific severity of COVID-19 from China and the UK.13 All those who recover from infection are assumed to be immune to re-infection for the duration of the epidemic. Within the model, hospital and ICU bed occupancy is dynamically tracked, with infected individuals requiring care assigned to either receive or not receive a bed based on those available at the given timepoint. Not receiving the appropriate care due to healthcare capacity being exceeded is assumed to increase the risk of mortality (Additional file 1: Figure S2, Table S1). To capture the impacts of a potentially weaker healthcare system on treatment outcomes we model the probability of dying across all age groups in non-severe cases that require and receive hospital treatment with high pressure oxygen as 20-30%, and 60% if this oxygen support is not available (Additional file 1: Table S1). See Walker et al for full model description.6 To parameterise capacity constraints, we use local estimates of healthcare capacity – of which there are 407 general hospital beds with oxygen supply and 35 ICU beds with mechanical ventilation available in the 5 major hospitals in Senegal.14 4 medRxiv preprint doi: https://doi.org/10.1101/2020.07.03.20144949; this version posted July 4, 2020.
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