A Bayesian estimate of the COVID-19 infection fatality ratio in Brazil based on a random seroprevalence survey

Abstract

We infer the infection fatality ratio (IFR) of SARS-CoV-2 in Brazil by combining three datasets. We compute the prevalence via the population-based seroprevalence survey EPICOVID19-BR. For the fatalities we obtain the absolute number using the public Painel Coronavírus dataset and the age-relative number using the public SIVEP-Gripe dataset. The time delay between the development of antibodies and subsequent fatality is estimated via the SIVEP-Gripe dataset. We obtain the IFR via Bayesian inference for each survey stage and 27 federal states. We include the effect of fading IgG antibody levels by marginalizing over the time after contagion at which the test gives a negative result with a flat prior on the interval [40, 80] days. We infer a country-wide average IFR (maximum posterior and 95% CI) of 0.97% (0.82–1.14%) and age-specific IFR: 0.028% (0.024–0.036%) [< 30 years], 0.21% (0.17–0.25%) [30–49 years], 1.06% (0.88–1.31%) [50–69 years], 2.9% (2.5–3.7%) [≥ 70 years].