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COVID-19 and the Difficulty of Inferring Epidemiological Parameters from Clinical Data

Published time: 28 May 2020

Authors: Simon N Wood, Ernst C Wit, Matteo Fasiolo, Peter J Green

Keywords: Covid-19, Global Health, Public Health


Abstract

Knowing the infection fatality ratio (IFR) is crucial for epidemic management: for immediate planning, for balancing the life-years saved against those lost to the consequences of management, and for considering the ethics of paying substantially more to save a life-year from the epidemic than from other diseases. Impressively, Robert Verity and colleagues1 rapidly assembled case data and used statistical modelling to infer the IFR for COVID-19. We have attempted an in-depth statistical review of their paper, eschewing statistical nit-picking, but attempting to identify the extent to which the (necessarily compromised) data are more informative about the IFR than are the modelling assumptions. First, the data.


COVID-19 and the difficulty of inferring epidemiological parameters from clinical data

 

Reference: https://doi.org/10.1016/S1473-3099(20)30437-0

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