Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , , , , , |
Tipo de documento: | preprint |
Idioma: | por |
Título da fonte: | SciELO Preprints |
Texto Completo: | https://preprints.scielo.org/index.php/scielo/preprint/view/41 |
Resumo: | COVID-19 is a disease produced by the virus SARS-CoV-2. This virus has spread quickly throughout the world, leading the World Health Organization to first classify COVID-19 as an international health emergency and, subsequently declaring it pandemic. The number of confirmed cases, as April 11, surpassed 1,700,000, but this figure does not reflect the real prevalence of COVID-19 in the population, as in many countries tests are almost exclusively performed in people with symptoms, particularly severe cases. In order to properly assess the magnitude of the problem and to contribute to the design of evidence-based policies for fighting COVID-19, one must accurately estimate the prevalence of infection in the population. The present study is aimed at estimating the prevalence of infected individuals in the state of Rio Grande do Sul, Brazil, to document how fast the infection is spreading, and to estimate the proportion of infected people who present or presented symptoms, as well as the proportion of asymptomatic infections. Four repeated serological surveys will be conducted in probability samples in nine sentinel cities every two weeks, representing all regions of the State. Tests will be performed in 4,500 participants in each survey, totaling 18,000 interviews. Interviews and tests will be conducted at the participants’ household. A rapid test for the detection of antibodies will be used; the test was validated prior to the beginning of the fieldwork. |
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Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveysEvolução da prevalência de infecção por COVID-19 no Rio Grande do Sul: inquéritos sorológicos seriadosCOVID-19infectionprevalencepopulation-based studyBrazilCOVID-19 is a disease produced by the virus SARS-CoV-2. This virus has spread quickly throughout the world, leading the World Health Organization to first classify COVID-19 as an international health emergency and, subsequently declaring it pandemic. The number of confirmed cases, as April 11, surpassed 1,700,000, but this figure does not reflect the real prevalence of COVID-19 in the population, as in many countries tests are almost exclusively performed in people with symptoms, particularly severe cases. In order to properly assess the magnitude of the problem and to contribute to the design of evidence-based policies for fighting COVID-19, one must accurately estimate the prevalence of infection in the population. The present study is aimed at estimating the prevalence of infected individuals in the state of Rio Grande do Sul, Brazil, to document how fast the infection is spreading, and to estimate the proportion of infected people who present or presented symptoms, as well as the proportion of asymptomatic infections. Four repeated serological surveys will be conducted in probability samples in nine sentinel cities every two weeks, representing all regions of the State. Tests will be performed in 4,500 participants in each survey, totaling 18,000 interviews. Interviews and tests will be conducted at the participants’ household. A rapid test for the detection of antibodies will be used; the test was validated prior to the beginning of the fieldwork.A COVID-19 é uma doença produzida pelo vírus SARS-CoV-2. Esse vírus se espalhou rapidamente pelo mundo, o que levou a Organização Mundial da Saúde a classificar a COVID-19 como uma emergência de saúde internacional e, posteriormente, declará-la uma pandemia. O número de casos confirmados, no dia 11 de abril de 2020, já passa de 1.700.000, porém esses dados não refletem a real prevalência de COVID-19 na população, visto que, em muitos países, os testes são quase que exclusivamente realizados em pessoas com sintomas, especialmente os mais graves. Para definir políticas de enfrentamento, é essencial dispor de dados sobre a prevalência real de infecção na população. Os objetivos principais desse estudo são avaliar a proporção de indivíduos já infectados pelo SARS-CoV-2 no Rio Grande do Sul, analisar a velocidade de expansão da infecção e estimar o percentual de infectados com e sem sintomas. Serão realizados quatro inquéritos sorológicos repetidos a cada 15 dias, com amostragem probabilística de nove cidades sentinela, em todas as sub-regiões do Estado. Os testes serão realizados em 4.500 indivíduos em cada inquérito, totalizando 18.000 entrevistas. As entrevistas e testes ocorrerão no âmbito domiciliar. Serão utilizados testes rápidos para detecção de anticorpos, validados previamente ao início da coleta de dados.SciELO PreprintsSciELO PreprintsSciELO Preprints2020-04-16info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/4110.1590/SciELOPreprints.41porhttps://preprints.scielo.org/index.php/scielo/article/view/41/83Copyright (c) 2020 Pedro Hallal, Bernardo Horta, Aluisio Barros, Odir Dellagostin, Fernando Hartwig, Lúcia Pellanda, Cláudio Struchiner, Marcelo Burattini; Mariângela Silveira; Ana Menezes, Fernando Barros, Cesar Victorahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessHallal, PedroHorta, BernardoBarros, AluisioDellagostin, OdirHartwig, FernandoPellanda, LúciaStruchiner, CláudioBurattini, MarceloSilveira, MariângelaMenezes, AnaBarros, FernandoVictora, Cesarreponame:SciELO Preprintsinstname:SciELOinstacron:SCI2020-04-13T10:30:13Zoai:ops.preprints.scielo.org:preprint/41Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2020-04-13T10:30:13SciELO Preprints - SciELOfalse |
dc.title.none.fl_str_mv |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys Evolução da prevalência de infecção por COVID-19 no Rio Grande do Sul: inquéritos sorológicos seriados |
title |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys |
spellingShingle |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys Hallal, Pedro COVID-19 infection prevalence population-based study Brazil |
title_short |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys |
title_full |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys |
title_fullStr |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys |
title_full_unstemmed |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys |
title_sort |
Trends in the prevalence of COVID-19 infection in Rio Grande do Sul, Brazil: repeated serological surveys |
author |
Hallal, Pedro |
author_facet |
Hallal, Pedro Horta, Bernardo Barros, Aluisio Dellagostin, Odir Hartwig, Fernando Pellanda, Lúcia Struchiner, Cláudio Burattini, Marcelo Silveira, Mariângela Menezes, Ana Barros, Fernando Victora, Cesar |
author_role |
author |
author2 |
Horta, Bernardo Barros, Aluisio Dellagostin, Odir Hartwig, Fernando Pellanda, Lúcia Struchiner, Cláudio Burattini, Marcelo Silveira, Mariângela Menezes, Ana Barros, Fernando Victora, Cesar |
author2_role |
author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Hallal, Pedro Horta, Bernardo Barros, Aluisio Dellagostin, Odir Hartwig, Fernando Pellanda, Lúcia Struchiner, Cláudio Burattini, Marcelo Silveira, Mariângela Menezes, Ana Barros, Fernando Victora, Cesar |
dc.subject.por.fl_str_mv |
COVID-19 infection prevalence population-based study Brazil |
topic |
COVID-19 infection prevalence population-based study Brazil |
description |
COVID-19 is a disease produced by the virus SARS-CoV-2. This virus has spread quickly throughout the world, leading the World Health Organization to first classify COVID-19 as an international health emergency and, subsequently declaring it pandemic. The number of confirmed cases, as April 11, surpassed 1,700,000, but this figure does not reflect the real prevalence of COVID-19 in the population, as in many countries tests are almost exclusively performed in people with symptoms, particularly severe cases. In order to properly assess the magnitude of the problem and to contribute to the design of evidence-based policies for fighting COVID-19, one must accurately estimate the prevalence of infection in the population. The present study is aimed at estimating the prevalence of infected individuals in the state of Rio Grande do Sul, Brazil, to document how fast the infection is spreading, and to estimate the proportion of infected people who present or presented symptoms, as well as the proportion of asymptomatic infections. Four repeated serological surveys will be conducted in probability samples in nine sentinel cities every two weeks, representing all regions of the State. Tests will be performed in 4,500 participants in each survey, totaling 18,000 interviews. Interviews and tests will be conducted at the participants’ household. A rapid test for the detection of antibodies will be used; the test was validated prior to the beginning of the fieldwork. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-04-16 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/preprint info:eu-repo/semantics/publishedVersion |
format |
preprint |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/preprint/view/41 10.1590/SciELOPreprints.41 |
url |
https://preprints.scielo.org/index.php/scielo/preprint/view/41 |
identifier_str_mv |
10.1590/SciELOPreprints.41 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/article/view/41/83 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO |
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SCI |
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SciELO Preprints |
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SciELO Preprints |
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SciELO Preprints - SciELO |
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