Using Early Data to Estimate the Actual Infection Fatality Ratio from COVID-19 in France

Abstract

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 of this work is to estimate the actual number of people infected with COVID-19 and to deduce the IFR during the observation window in France. 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. The actual number of infected cases in France is probably higher than the observations: we find here a factor ×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). 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%).

Predicting the number of reported and unreported cases for the COVID-19 epidemics in China, South Korea, Italy, France, Germany and United Kingdom

“…In future work we will apply our methods to other countries and regions within countries in an effort to better understand the evolution of COVID-19 epidemics. In Cotta et al, 2020 , Roques et al, 2020 Bayesian’s method has been used successfully. Such a method could be used here as well, and that is left for future work.…”

“…Such a method is general and may probably be applied to other situations (patch models etc …). In future work, we can also incorporate the number of tests (see Roques et al, 2020 ) which may significantly improve our understanding of COVID-19 epidemics.…”

COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s)

“…Several modelling approaches have already been proposed to forecast COVID-19 epidemics, most of them relying on standard epidemiological models of the SIR (Susceptible-Infected-Removed) type and their extensions [4][5][6][7][8][9][10]. These models generally include compartments corresponding to the dead fraction of the population and can hence be used to predict the temporal evolution of mortality due to COVID-19, in which we are interested here.…”

SARS-CoV-2 Persistence: Data Summary up to Q2 2020

“…Among the physical treatments, the first to be considered is heat (dry steam) for 30 min, also used according to the Koch Institute prescriptions for sanitizing surgical masks [23,44,45].…”