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

Background:A number of estimates of the infection fatality ratio (IFR) of SARS-CoV-2 in different countries have been published. In Brazil, the fragile political situation, together with socioeconomic and ethnic diversity, could result in substantially different IFR estimates. Methods:We infer the IFR in Brazil in 2020 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 for each survey stage and 27 federal states. We include the effect of fading IgG antibody levels by marginalizing over the test detectability time window. Results:We infer a country-wide average IFR (maximum posterior and 95% CI) of 1.03% (0.88–1.22%) and age-specific IFRs of 0.032% (0.023–0.041%) [< 30 years], 0.22% (0.18–0.27%) [30–49 years], 1.2% (1.0–1.5%) [50–69 years], and 3.0% (2.4–3.9%) [[Formula: see text] 70 years]. We find that the fatality ratio in the country increased significantly at the end of June 2020, likely due to the increased strain on the health system. Conclusions: Our IFR estimate is based on data and does not rely on extrapolating models. This estimate sets a baseline value with which future medications and treatment protocols may be confronted.