Inferring the number of COVID-19 cases from recently reported deaths [version 1; peer review: 2 approved]
Título
Inferring the number of COVID-19 cases from recently reported deaths [version 1; peer review: 2 approved]
Autor
Yang Liu, Thibaut Jombart, Sebastian Funk, W. John Edmunds, Adam J. Kucharski, Sam Clifford, Rosalind M. Eggo, Carl A B Pearson, Hamish Gibbs, Kevin van Zandvoort, Sam Abbott, Christopher I. Jarvis, Amy Gimma, Nikos I Bosse, Timothy W Russell, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group
Descripción
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.
Fecha
2020
Identificador
DOI: 10.12688/wellcomeopenres.15786.1
Fuente
Wellcome Open Research
Editor
Wellcome
Cobertura
Science, Medicine
Archivos
Colección
Citación
Yang Liu, Thibaut Jombart, Sebastian Funk, W. John Edmunds, Adam J. Kucharski, Sam Clifford, Rosalind M. Eggo, Carl A B Pearson, Hamish Gibbs, Kevin van Zandvoort, Sam Abbott, Christopher I. Jarvis, Amy Gimma, Nikos I Bosse, Timothy W Russell, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, “Inferring the number of COVID-19 cases from recently reported deaths [version 1; peer review: 2 approved],” SOCICT Open, consulta 18 de abril de 2026, https://www.socictopen.socict.org/items/show/3630.
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