Author: Roques, Lionel; Klein, Etienne; Papaix, Julien; Sar, Antoine; Soubeyrand, Samuel
Title: Using early data to estimate the actual infection fatality ratio from COVID-19 in France Cord-id: dqg8fkca Document date: 2020_3_24
ID: dqg8fkca
Snippet: Background. The number of screening tests carried out in France and the methodology used to target the patients tested do not allow for a direct computation of the actual number of cases and the infection fatality ratio (IFR). The main objective was to estimate the actual number of people infected with COVID-19 during the observation window in France and to deduce the IFR. Methods. We develop a 'mechanistic-statistical' approach coupling a SIR epidemiological model describing the unobserved epid
Document: Background. The number of screening tests carried out in France and the methodology used to target the patients tested do not allow for a direct computation of the actual number of cases and the infection fatality ratio (IFR). The main objective was to estimate the actual number of people infected with COVID-19 during the observation window in France and to deduce the IFR. Methods. We develop a 'mechanistic-statistical' approach coupling a SIR epidemiological model describing the unobserved epidemiological dynamics, a probabilistic model describing the data acquisition process and a statistical inference method. Results. The actual number of infected cases in France is probably higher than the observations: we find here a factor x 8 (95%-CI: 5-12) which leads to an IFR in France of 0.5% (95%-CI: 0.3-0.8) based on hospital death counting data. Adjusting for the number of deaths in nursing homes, we obtain an IFR of 0.8% (95%-CI: 0.45-1.25). Conclusions. This IFR is consistent with previous findings in China (0.66%) and in the UK (0.9%) and lower than the value previously computed on the Diamond Princess cruse ship data (1.3%).
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