Estimated prevalence of COVID-19 in Brazil with probabilistic bias correction
Abstract: 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 a...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz
2021-10-01
|
| Series: | Cadernos de Saúde Pública |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2021000905008&tlng=en |
| _version_ | 1798020002062794752 |
|---|---|
| author | Erik Alencar de Figueiredo Démerson André Polli Bernardo Borba de Andrade |
| author_facet | Erik Alencar de Figueiredo Démerson André Polli Bernardo Borba de Andrade |
| author_sort | Erik Alencar de Figueiredo |
| collection | DOAJ |
| description | Abstract: 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). |
| first_indexed | 2024-04-11T16:49:46Z |
| format | Article |
| id | doaj.art-37b1d138dcd2447886f96afb060b5463 |
| institution | Directory Open Access Journal |
| issn | 1678-4464 |
| language | English |
| last_indexed | 2024-04-11T16:49:46Z |
| publishDate | 2021-10-01 |
| publisher | Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz |
| record_format | Article |
| series | Cadernos de Saúde Pública |
| spelling | doaj.art-37b1d138dcd2447886f96afb060b54632022-12-22T04:13:28ZengEscola Nacional de Saúde Pública, Fundação Oswaldo CruzCadernos de Saúde Pública1678-44642021-10-0137910.1590/0102-311x00290120Estimated prevalence of COVID-19 in Brazil with probabilistic bias correctionErik Alencar de Figueiredohttps://orcid.org/0000-0002-3479-3665Démerson André Pollihttps://orcid.org/0000-0002-5904-2315Bernardo Borba de Andradehttps://orcid.org/0000-0003-4688-9733Abstract: 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).http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2021000905008&tlng=enHerd ImmunitySelection BiasQuantitative Analysis |
| spellingShingle | Erik Alencar de Figueiredo Démerson André Polli Bernardo Borba de Andrade Estimated prevalence of COVID-19 in Brazil with probabilistic bias correction Cadernos de Saúde Pública Herd Immunity Selection Bias Quantitative Analysis |
| title | Estimated prevalence of COVID-19 in Brazil with probabilistic bias correction |
| title_full | Estimated prevalence of COVID-19 in Brazil with probabilistic bias correction |
| title_fullStr | Estimated prevalence of COVID-19 in Brazil with probabilistic bias correction |
| title_full_unstemmed | Estimated prevalence of COVID-19 in Brazil with probabilistic bias correction |
| title_short | Estimated prevalence of COVID-19 in Brazil with probabilistic bias correction |
| title_sort | estimated prevalence of covid 19 in brazil with probabilistic bias correction |
| topic | Herd Immunity Selection Bias Quantitative Analysis |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2021000905008&tlng=en |
| work_keys_str_mv | AT erikalencardefigueiredo estimatedprevalenceofcovid19inbrazilwithprobabilisticbiascorrection AT demersonandrepolli estimatedprevalenceofcovid19inbrazilwithprobabilisticbiascorrection AT bernardoborbadeandrade estimatedprevalenceofcovid19inbrazilwithprobabilisticbiascorrection |