Por favor, use este identificador para citar o enlazar este ítem:
http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/197| Inferring the number of COVID-19 cases from recently reported deaths | |
| Yang Liu Carl Pearson Nikos Bosse Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group Rosalind M Eggo Adam J Kucharski John Edmunds Kevin van Zandvoort Tim Russell Christopher Jarvis Amy Gimma Sam Abbott Hamish Gibbs Thibaut Jombart Sebastian Funk Samuel Clifford | |
| Novel Coronavirus | |
| Acceso Abierto | |
| Atribución | |
| 10.1101/2020.03.10.20033761 | |
| We estimate the number of COVID-19 cases from newly reported deaths in a population without previous reports. Our results suggest that by the time a single death occurs, hundreds to thousands of cases are likely to be present in that population. This suggests containment via contact tracing will be challenging at this point, and other response strategies should be considered. Our approach is implemented in a publicly available, user-friendly, online tool. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The named authors (TJ, SA, AG, CIJ, , TWR, KvZ, SC, SF, HG, YL, CP, NIB, RME, AJK, WJE) had the following sources of funding: TJ, CIJ and AG receive funding from the Global Challenges Research Fund (GCRF) project RECAP managed through RCUK and ESRC (ES/P010873/1). TJ receives funding from the UK Public Health Rapid Support Team funded by the United Kingdom Department of Health and Social Care. TJ receives funding from the National Institute for Health Research - Health Protection Research Unit for Modelling Methodology. SA and SF were funded by the Wellcome Trust (grant number: 210758/Z/18/Z), TWR and AJK were funded by the Wellcome Trust (grant number: 206250/Z/17/Z), SC was funded by the Wellcome Trust (grant number: 208812/Z/17/Z), and RME was funded by HDR UK (grant number: MR/S003975/1). KvZ is supported by the Elrhas Research for Health in Humanitarian Crises (R2HC) Programme. The R2HC programme is funded by the UK Government (DFID), the Wellcome Trust, and the UK National Institute for Health Research (NIHR). HG is funded by the Department of Health and Social Care using UK Aid funding and is managed by the NIHR. YL receives funding from the National Institute for Health (grant number: 16/137/109) and from the Bill and Melinda Gates Foundation (grant number: INV-003174). The UK Public Health Rapid Support Team is funded by UK aid from the Department of Health and Social Care and is jointly run by Public Health England and the London School of Hygiene & Tropical Medicine. The University of Oxford and Kings College London are academic partners. The views expressed in this publication are those of the authors and not necessarily those of the National Health Service, the National Institute for Health Research or the Department of Health and Social Care. ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Our model is implemented in a publicly-available web-application (see link provided). <https://cmmid.github.io/visualisations/inferring-covid19-cases-from-deaths> | |
| Cold Spring Harbor Laboratory Press | |
| 2020 | |
| Preimpreso | |
| https://www.medrxiv.org/content/10.1101/2020.03.10.20033761v1 | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
Cargar archivos:
| Fichero | Tamaño | Formato | |
|---|---|---|---|
| inferring the number of covid.pdf | 265.4 kB | Adobe PDF | Visualizar/Abrir |