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Estimated prevalence of Covid-19 in Brazil with probabilistic bias correction

Bibliographic Data

ID5167053
AuthorsErik Alencar De Figueiredo (0000-0002-3479-3665), Démerson André Polli (0000-0002-5904-2315), Bernardo Borba De Andrade (0000-0003-4688-9733)
Year2021
Volume37
Issue9
Publication date2021-01-01
Open AccessYes
TypeARTICLE
PublisherFapUNIFESP (SciELO) (PUBLISHER)
DOI10.1590/0102-311x00290120
SciELOS0102-311X2021000905008
LanguageEN
References cited8

Using data collected by the Brazilian National Household Sample Survey - COVID-19 (PNAD-COVID19) and semi-Bayesian modelling developed by Wu et al., we have estimated the effect of underreporting of COVID-19 cases in Brazil as of December 2020. The total number of infected individuals is about 3 to 8 times the number of cases reported, depending on the state. Confirmed cases are at 3.1% of the total population and our estimate of total cases is at almost 15% of the approximately 212 million Brazilians as of 2020. The method we adopted from Wu et al., with slight modifications in prior specifications, applies bias corrections to account for incomplete testing and imperfect test accuracy. Our estimates, which are comparable to results obtained by Wu et al. for the United States, indicate that projections from compartmental models (such as SEIR models) tend to overestimate the number of infections and that there is considerable regional heterogeneity (results are presented by state

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