COVID-19 Incubation Period and Considerations for Travellers
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Risk Factors, Seroprevalence and Infectivity of Hepatitis B Virus
ISSN: 2474-3658 Ogbonna et al. J Infect Dis Epidemiol 2021, 7:186 DOI: 10.23937/2474-3658/1510186 Volume 7 | Issue 1 Journal of Open Access Infectious Diseases and Epidemiology Research ArticlE Risk Factors, Seroprevalence and Infectivity of Hepatitis B Virus amongst Children Resident in Orphanages in a Developing Country Chioma Paulina Ogbonna, MBBS, FMCPaed1, Christian Chukwukere Ogoke, MBBS, FWACP2* , Anthony Nnaemeka Ikefuna, MBBS, FMCPaed, FRCP3,4, Tochukwu 1 Check for Chukwukadibia Ezeofor, MBBS, FMCpaed, FRCP , Emeka Charles Nwolisa, MBBS, updates FWACP, FRCP5, Franklin Chime Emerenini, MBBch, FMCpaed1, and Christopher Bismarck Eke MBBS, FWACP4,6 1Consultant Paediatrician, Department of Paediatrics, Federal Medical Centre, Owerri, Nigeria 2Paediatric Neurology Unit, Department of Paediatrics, King Fahad Central Hospital, Abu Arish 82666, Kingdom of Saudi Arabia 3Professor of Paediatrics, Faculty of Medical Sciences, Department of Paediatrics, University of Nigeria, Nigeria 4Consultant Paediatrician, University of Nigeria Teaching Hospital, Nigeria 5Chief Consultant Paediatrician, Federal Medical Centre, Owerri, Nigeria 6Senior Lecturer, Department of Paediatrics, University of Nigeria, Nigeria *Corresponding authors: Dr. Christian Chukwukere Ogoke, Paediatric Neurology Unit, Department of Paediatrics, King Fahad Central Hospital, Abu Arish 82666, Kingdom of Saudi Arabia Abstract Results: Seroprevalence of HBsAg in children in orphanag- es was 20.0% versus 10.7% in the controls (P = 0.031). In- Background: Hepatitis B infection (HBV) remains a signifi- fectivity of HBV was higher in subjects (42.9%) than controls cant clinical and public health problem and is hyperendemic (20.0%) (P = 0.245). Sharing of towel (P = 0.014) sharing of in Nigeria. In highly endemic regions, infections spread from barbing devices (P = 0.001) and circumcision (P = 0.005) mother to child, or by horizontal transmission, with the bur- were the significant risk factors for Hepatitis B virus infec- den of infection being highest in under-fives. -
Scientific Committee Animal Health and Animal Welfare
EUROPEAN COMMISSION HEALTH and CONSUMER PROTECTION DIRECTORATE-GENERAL Directorate C - Scientific Opinions C2 - Management of scientific committees; scientific co-operation and networks Diagnostic Techniques and Vaccines for Foot-and-Mouth Disease, Classical Swine Fever, Avian Influenza and some other important OIE List A Diseases Report of the Scientific Committee on Animal Health and Animal Welfare Adopted 24-25th April 2003 TABLE OF CONTENTS 1. ABBREVIATIONS.....................................................................................................6 2. MANDATE.................................................................................................................9 3. BACKGROUND.........................................................................................................9 4. PREAMBLE..............................................................................................................10 5. RECENT DEVELOPMENTS IN THE DIAGNOSIS OF INFECTIOUS DISEASES ................................................................................................................14 5.1. Introduction .....................................................................................................14 5.2. Screening of animal products ..........................................................................19 5.3. Nucleic acid amplification methods ................................................................19 5.3.1. Extraction of nucleic acid from the test sample ................................20 5.3.2. Target amplification -
The Comparative Clinical Performance of Four SARS-Cov-2 Rapid Antigen Tests and Their Correlation to Infectivity in Vitro
Journal of Clinical Medicine Article The Comparative Clinical Performance of Four SARS-CoV-2 Rapid Antigen Tests and Their Correlation to Infectivity In Vitro Niko Kohmer 1,†, Tuna Toptan 1,† , Christiane Pallas 1, Onur Karaca 1, Annika Pfeiffer 1 , Sandra Westhaus 1, Marek Widera 1 , Annemarie Berger 1, Sebastian Hoehl 1 , Martin Kammel 2,3, Sandra Ciesek 1,4,5,*,‡ and Holger F. Rabenau 1,*,‡ 1 Institute for Medical Virology, University Hospital, Goethe University Frankfurt, 60596 Frankfurt, Germany; [email protected] (N.K.); [email protected] (T.T.); [email protected] (C.P.); [email protected] (O.K.); [email protected] (A.P.); [email protected] (S.W.); [email protected] (M.W.); [email protected] (A.B.); [email protected] (S.H.) 2 Institut fuer Qualitaetssicherung in der Virusdiagnostik-IQVD der GmbH, 14129 Berlin, Germany; [email protected] 3 INSTAND Gesellschaft zur Foerderung der Qualitaetssicherung in Medizinischen Laboratorien e.V., 40223 Duesseldorf, Germany 4 German Centre for Infection Research, External Partner Site, 60323 Frankfurt, Germany 5 Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), Branch Translational Medicine and Pharmacology, 60596 Frankfurt, Germany * Correspondence: [email protected] (S.C.); [email protected] (H.F.R.); Tel.: +49-696-301-5219 (S.C.); Tel.: +49-696-301-5312 (H.F.R.) † These authors contributed equally to this work. ‡ These authors contributed equally to this work. Abstract: Citation: Kohmer, N.; Toptan, T.; Due to globally rising numbers of severe acute respiratory syndrome coronavirus 2 (SARS- Pallas, C.; Karaca, O.; Pfeiffer, A.; CoV-2) infections, resources for real-time reverse-transcription polymerase chain reaction (rRT-PCR)- Westhaus, S.; Widera, M.; Berger, A.; based testing have been exhausted. -
Inferring the Association Between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-Cov-2
viruses Article Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2 Shi Zhao 1,2,* , Jingzhi Lou 1, Marc K. C. Chong 1,2 , Lirong Cao 1,2 , Hong Zheng 1, Zigui Chen 3 , Renee W. Y. Chan 4,5,6,7 , Benny C. Y. Zee 1,2 , Paul K. S. Chan 3 and Maggie H. Wang 1,2,* 1 JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; [email protected] (J.L.); [email protected] (M.K.C.C.); [email protected] (L.C.); [email protected] (H.Z.); [email protected] (B.C.Y.Z.) 2 CUHK Shenzhen Research Institute, Shenzhen 518000, China 3 Department of Microbiology, Chinese University of Hong Kong, Hong Kong, China; [email protected] (Z.C.); [email protected] (P.K.S.C.) 4 Department of Pediatrics, Chinese University of Hong Kong, Hong Kong, China; [email protected] 5 Hong Kong Hub of Pediatric Excellence, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China 6 CUHK-UMCU Joint Research Laboratory of Respiratory Virus & Immunobiology, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China 7 Li Ka Shing Institute of Health Sciences, Faculty of Medicine, Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China * Correspondence: [email protected] (S.Z.); [email protected] (M.H.W.) Abstract: As COVID-19 is posing a serious threat to global health, the emerging mutation in SARS- CoV-2 genomes, for example, N501Y substitution, is one of the major challenges against control of the Citation: Zhao, S.; Lou, J.; Chong, pandemic. -
The Global Case-Fatality Rate of COVID-19 Has Been Declining Since May 2020
Am. J. Trop. Med. Hyg., 104(6), 2021, pp. 2176–2184 doi:10.4269/ajtmh.20-1496 Copyright © 2021 by The American Society of Tropical Medicine and Hygiene The Global Case-Fatality Rate of COVID-19 Has Been Declining Since May 2020 Mohammad Nayeem Hasan,1† Najmul Haider,2† Florian L. Stigler,3 Rumi Ahmed Khan,4 David McCoy,5 Alimuddin Zumla,6,7 Richard A. Kock,2 and Md. Jamal Uddin1 1Department of Statistics, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh; 2The Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, United Kingdom; 3Austrian Sickness Fund, Vienna, Austria; 4Department of Critical Care Medicine, Orlando Regional Medical Centre, Orlando, Florida; 5Institute of Population Health Sciences, Barts and London Medical and Dental School, Queen Mary University of London, London, United Kingdom; 6Department of Infection, Division of Infection and Immunity, Centre for Clinical Microbiology, Royal Free Campus, University College London, London, United Kingdom; 7National Institute for Health Research Biomedical Research Centre, University College London Hospitals, London, United Kingdom Abstract. The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO’s daily situation reports dated January 1 to December 31, 2020. We performed three time-series models [simple exponential smoothing, auto-regressive integrated moving average, and automatic forecasting time- series (Prophet)] to identify the global trend of rCFR for COVID-19. We used beta regression models to investigate the association between the rCFR and potential predictors of each country and reported incidence rate ratios (IRRs) of each variable. -
STI Screening Timetable
Patient Education Information from University Health Center’s STI Screening Clinic Page 1 of 1 STI Screening Timetable How long until STI (sexually transmitted infection) screening tests turn positive? How long until STI symptoms might show up? The time between infection and a positive test, or between infection and symptoms, is variable and depends on many factors, including the behavior of the infectious agent, how and where the body is infected, and the state of a person’s immune system and personal health. Many STIs don’t have any symptoms. The incubation period times listed in the chart below are averages only. If you have further questions or concerns, you can schedule an appointment with a clinician at 541-346-2770. STI screening test Window period (time from exposure until Incubation period (time between exposure and screening test turns positive) when symptoms appear) Chlamydia (urine specimen or swab of 1 week most of the time Often no symptoms vagina, rectum, throat) 2 weeks catches almost all 1-3 weeks on average Gonorrhea (urine specimen on swab of 1 week most of the time Often no symptoms, especially vaginal vagina, rectum, throat) 2 weeks catches almost all infections usually within 2-8 days but can be up to 2 weeks Syphilis (blood test, RPR) 1 month catches most Often symptoms too mild to notice 3 months catches almost all 10-90 days average 21 days HIV (oral cheek swab) 1 month catches most Sometimes mild body aches and fever within 1-2 3 months catches almost all weeks then can be months to years HIV (blood test, antigen/antibody -
Incubation Period and Other Epidemiological
Journal of Clinical Medicine Article Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data 1, 1, 1 1 Natalie M. Linton y , Tetsuro Kobayashi y, Yichi Yang , Katsuma Hayashi , Andrei R. Akhmetzhanov 1 , Sung-mok Jung 1 , Baoyin Yuan 1, Ryo Kinoshita 1 and Hiroshi Nishiura 1,2,* 1 Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan; [email protected] (N.M.L.); [email protected] (T.K.); [email protected] (Y.Y.); katsuma5miff[email protected] (K.H.); [email protected] (A.R.A.); [email protected] (S.-m.J.); [email protected] (B.Y.); [email protected] (R.K.) 2 Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan * Correspondence: [email protected]; Tel.: +81-11-706-5066 These authors contributed equally to this work. y Received: 25 January 2020; Accepted: 10 February 2020; Published: 17 February 2020 Abstract: The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2–14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. -
Infectivity of Severe Acute Respiratory Syndrome Coronavirus 2 in Children Compared with Adults
Early release, published at www.cmaj.ca on April 9, 2021. Subject to revision. RESEARCH Infectivity of severe acute respiratory syndrome coronavirus 2 in children compared with adults Jared Bullard MD, Duane Funk MD, Kerry Dust PhD, Lauren Garnett BSc, Kaylie Tran BSc, Alex Bello PhD, James E. Strong MD PhD, Santina J. Lee MD, Jillian Waruk PhD, Adam Hedley BSc, David Alexander PhD, Paul Van Caeseele MD, Carla Loeppky PhD, Guillaume Poliquin MD PhD n Cite as: CMAJ 2021. doi: 10.1503/cmaj.210263; early-released April 9, 2021 ABSTRACT BACKGROUND: The role of children in the infective dose (TCID50/mL) between adults (p < 0.001). The median TCID50/mL transmission and community spread of adults and children. was significantly lower in children aged severe acute respiratory syndrome coro- 11–17 years (316, interquartile range navirus 2 (SARS-CoV-2) is unclear. We RESULTS: Among 305 samples positive [IQR] 178–2125) than adults (5620, IQR aimed to quantify the infectivity of SARS- for SARS-CoV-2 by RT-PCR, 97 samples 1171 to 17 800, p < 0.001). Cycle thresh- CoV-2 in nasopharyngeal samples from were from children aged 10 years or old was an accurate predictor of posi- children compared with adults. younger, 78 were from children aged tive culture in both children and adults 11–17 years and 130 were from adults (area under the receiver-operator curve, METHODS: We obtained nasopharyngeal (≥ 18 yr). Viral growth in culture was 0.87, 95% CI 0.81–0.93 v. 0.89, 95% CI swabs from adult and pediatric cases of present in 31% of samples, including 18 0.83–0.96, p = 0.6). -
A Practical Approach to Biological Assay Validation
A Practical Approach to Biological Assay Validation Joke Ederveen Sponsored by the Dutch Ministry of Housing, Spatial Planning and the Environment (VROM) 2010 Progress report number 08090 A Practical Approach to Biological Assay Validation Author: J.C. Ederveen Contact: Joke Ederveen Progress, Project Management & Engineering P.O. Box 60; 2130 AB Hoofddorp, the Netherlands Tel. +31 23 563 5016 / +31 6 4637 7226 [email protected] www.progress-pme.nl Steering committee: Dr. D.A. Bleijs, RIVM, GMO Office, Bilthoven Dr. N.A. Kootstra, Academic Medical Center, University of Amsterdam Drs. D. Louz, RIVM, GMO Office, Bilthoven Drs. P.C. van Mourik, Sanquin Pharmaceutical Services, Amsterdam Dr. B.P.H. Peeters, Central Veterinary Institute, Lelystad Ing. A.L.M. Wassenaar, RIVM, GMO Office, Bilthoven Dr. G. van Willigen, Leiden University Medical Center Sponsor: This report has been ordered and sponsored by the Dutch Ministry of Housing, Spatial Planning and the Environment (VROM). Acknowledgement: The assistance of Dr. M.A.N. Rits in the preparation of this manuscript is highly appreciated. Hoofddorp, May 2010 A Practical Approach to Biological Assay Validation Summary This report is written from the perspective that 'validation‘ is a familiar concept, but in practice often interpreted and applied in different ways amongst scientists, government officials involved in authorizing experimental laboratory work, and inspectors. The document is meant as practical guide for the execution and implementation of biological assay validation in laboratory research. Extensive literature on the subject of assay validation is available, but its content is often too abstract or not specific enough or not useful for the aimed type of research. -
Using Proper Mean Generation Intervals in Modeling of COVID-19
ORIGINAL RESEARCH published: 05 July 2021 doi: 10.3389/fpubh.2021.691262 Using Proper Mean Generation Intervals in Modeling of COVID-19 Xiujuan Tang 1, Salihu S. Musa 2,3, Shi Zhao 4,5, Shujiang Mei 1 and Daihai He 2* 1 Shenzhen Center for Disease Control and Prevention, Shenzhen, China, 2 Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China, 3 Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria, 4 The Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China, 5 Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China In susceptible–exposed–infectious–recovered (SEIR) epidemic models, with the exponentially distributed duration of exposed/infectious statuses, the mean generation interval (GI, time lag between infections of a primary case and its secondary case) equals the mean latent period (LP) plus the mean infectious period (IP). It was widely reported that the GI for COVID-19 is as short as 5 days. However, many works in top journals used longer LP or IP with the sum (i.e., GI), e.g., >7 days. This discrepancy will lead to overestimated basic reproductive number and exaggerated expectation of Edited by: infection attack rate (AR) and control efficacy. We argue that it is important to use Reza Lashgari, suitable epidemiological parameter values for proper estimation/prediction. Furthermore, Institute for Research in Fundamental we propose an epidemic model to assess the transmission dynamics of COVID-19 Sciences, Iran for Belgium, Israel, and the United Arab Emirates (UAE). -
Malaria and COVID-19: Common and Different Findings
Tropical Medicine and Infectious Disease Viewpoint Malaria and COVID-19: Common and Different Findings Francesco Di Gennaro 1 , Claudia Marotta 1,*, Pietro Locantore 2, Damiano Pizzol 3 and Giovanni Putoto 1 1 Operational Research Unit, Doctors with Africa CUAMM, 35121 Padova, Italy; [email protected] (F.D.G.); [email protected] (G.P.) 2 Institute of Endocrinology, Università Cattolica del Sacro Cuore, 00168 Rome, Italy; [email protected] 3 Italian Agency for Development Cooperation, Khartoum 79371, Sudan; [email protected] * Correspondence: [email protected] or [email protected] Received: 31 July 2020; Accepted: 3 September 2020; Published: 6 September 2020 Abstract: Malaria and COVID-19 may have similar aspects and seem to have a strong potential for mutual influence. They have already caused millions of deaths, and the regions where malaria is endemic are at risk of further suffering from the consequences of COVID-19 due to mutual side effects, such as less access to treatment for patients with malaria due to the fear of access to healthcare centers leading to diagnostic delays and worse outcomes. Moreover, the similar and generic symptoms make it harder to achieve an immediate diagnosis. Healthcare systems and professionals will face a great challenge in the case of a COVID-19 and malaria syndemic. Here, we present an overview of common and different findings for both diseases with possible mutual influences of one on the other, especially in countries with limited resources. Keywords: malaria; SARS-CoV-2; COVID-19; preparedness; Africa; emergency; pandemic 1. Background On 11 March 2020, the WHO declared the outbreak of SARS-CoV-2 to be a pandemic infection. -
Prediction of the Incubation Period for COVID-19 and Future Virus Disease Outbreaks Ayal B
Gussow et al. BMC Biology (2020) 18:186 https://doi.org/10.1186/s12915-020-00919-9 RESEARCH ARTICLE Open Access Prediction of the incubation period for COVID-19 and future virus disease outbreaks Ayal B. Gussow†, Noam Auslander*†, Yuri I. Wolf and Eugene V. Koonin* Abstract Background: A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. At the time of the COVID-19 pandemic, optimization of quarantine regimes becomes paramount for public health, societal well- being, and global economy. However, biological factors that determine the duration of the virus incubation period remain poorly understood. Results: We demonstrate a strong positive correlation between the length of the incubation period and disease severity for a wide range of human pathogenic viruses. Using a machine learning approach, we develop a predictive model that accurately estimates, solely from several virus genome features, in particular, the number of protein-coding genes and the GC content, the incubation time ranges for diverse human pathogenic RNA viruses including SARS-CoV-2. The predictive approach described here can directly help in establishing the appropriate quarantine durations and thus facilitate controlling future outbreaks. Conclusions: The length of the incubation period in viral diseases strongly correlates with disease severity, emphasizing the biological and epidemiological importance of the incubation period. Perhaps, surprisingly, incubation times of pathogenic RNA viruses can be accurately predicted solely from generic features of virus genomes. Elucidation of the biological underpinnings of the connections between these features and disease progression can be expected to reveal key aspects of virus pathogenesis.