Jombart, T, Abbott, S, Gimma, A, Zandvoort, K, Clifford, S, Jarvis, C, Russell, T, Funk, S, Gibbs, H, Eggo, RM, Kucharski, AJ, CMMID COVID-19 Working Group and Edmunds, WJ. 2020. Inferring COVID-19 cases from deaths of confirmed cases. [Online]. CMMID Repository. Available from: https://cmmid.github.io/visualisations/inferring-covid19-cases-from-deaths
Jombart, T, Abbott, S, Gimma, A, Zandvoort, K, Clifford, S, Jarvis, C, Russell, T, Funk, S, Gibbs, H, Eggo, RM, Kucharski, AJ, CMMID COVID-19 Working Group and Edmunds, WJ. Inferring COVID-19 cases from deaths of confirmed cases [Internet]. CMMID Repository; 2020. Available from: https://cmmid.github.io/visualisations/inferring-covid19-cases-from-deaths
Jombart, T, Abbott, S, Gimma, A, Zandvoort, K, Clifford, S, Jarvis, C, Russell, T, Funk, S, Gibbs, H, Eggo, RM, Kucharski, AJ, CMMID COVID-19 Working Group and Edmunds, WJ (2020). Inferring COVID-19 cases from deaths of confirmed cases. [Data Collection]. CMMID Repository. https://cmmid.github.io/visualisations/inferring-covid19-cases-from-deaths
Description
Aim: To estimate the numbers of circulating COVID-19 cases from recently reported deaths, in places where surveillance has not revealed COVID-19 infections yet.
Rationale: Deaths of COVID-19 cases are indicative of wider circulation of the disease in a population. As the delay from onset to death and the case fatality ratio (CFR) have been characterised, we can infer the likely date of onset of a death, and the number of other cases (1/CFR) that had onset at the same time. From there, we use a branching process model to simulate epidemic growth, and derive estimates of the likely number of cases at present.
Keywords
Data capture method | Simulation |
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Date (Date published in a 3rd party system) | 3 March 2020 |
Language(s) of written materials | English |
Data Creators | Jombart, T, Abbott, S, Gimma, A, Zandvoort, K, Clifford, S, Jarvis, C, Russell, T, Funk, S, Gibbs, H, Eggo, RM, Kucharski, AJ, CMMID COVID-19 Working Group and Edmunds, WJ |
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LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology |
Research Centre | Centre for the Mathematical Modelling of Infectious Diseases |
Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
Date Deposited | 22 Apr 2020 15:38 |
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Last Modified | 20 Aug 2021 14:37 |
Publisher | CMMID Repository |