Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.lana.2022.100397 http://hdl.handle.net/11449/248200 |
Resumo: | Background: Vaccines developed between 2020 and 2021 against the SARS-CoV-2 virus were designed to diminish the severity and prevent deaths due to COVID-19. However, estimates of the effectiveness of vaccination campaigns in achieving these goals remain a methodological challenge. In this work, we developed a Bayesian statistical model to estimate the number of deaths and hospitalisations averted by vaccination of older adults (above 60 years old) in Brazil. Methods: We fit a linear model to predict the number of deaths and hospitalisations of older adults as a function of vaccination coverage in this group and casualties in younger adults. We used this model in a counterfactual analysis, simulating alternative scenarios without vaccination or with faster vaccination roll-out. We estimated the direct effects of COVID-19 vaccination by computing the difference between hypothetical and realised scenarios. Findings: We estimated that more than 165,000 individuals above 60 years of age were not hospitalised due to COVID-19 in the first seven months of the vaccination campaign. An additional contingent of 104,000 hospitalisations could have been averted if vaccination had started earlier. We also estimated that more than 58 thousand lives were saved by vaccinations in the period analysed for the same age group and that an additional 47 thousand lives could have been saved had the Brazilian government started the vaccination programme earlier. Interpretation: Our estimates provided a lower bound for vaccination impacts in Brazil, demonstrating the importance of preventing the suffering and loss of older Brazilian adults. Once vaccines were approved, an early vaccination roll-out could have saved many more lives, especially when facing a pandemic. Funding: The Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–Brazil (Finance Code 001 to F.M.D.M. and L.S.F.), Conselho Nacional de Desenvolvimento Científico e Tecnológico – Brazil (grant number: 315854/2020-0 to M.E.B., 141698/2018-7 to R.L.P.d.S., 313055/2020-3 to P.I.P., 311832/2017-2 to R.A.K.), Fundação de Amparo à Pesquisa do Estado de São Paulo – Brazil (contract number: 2016/01343-7 to R.A.K.), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro – Brazil (grant number: E-26/201.277/2021 to L.S.B.) and Inova Fiocruz/Fundação Oswaldo Cruz – Brazil (grant number: 48401485034116) to L.S.B., O.G.C. and M.G.d.F.C. The funding agencies had no role in the conceptualization of the study. |
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Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysisBayesian modelCOVID-19DeathsHospitalisationPandemicSARS-CoV-2Background: Vaccines developed between 2020 and 2021 against the SARS-CoV-2 virus were designed to diminish the severity and prevent deaths due to COVID-19. However, estimates of the effectiveness of vaccination campaigns in achieving these goals remain a methodological challenge. In this work, we developed a Bayesian statistical model to estimate the number of deaths and hospitalisations averted by vaccination of older adults (above 60 years old) in Brazil. Methods: We fit a linear model to predict the number of deaths and hospitalisations of older adults as a function of vaccination coverage in this group and casualties in younger adults. We used this model in a counterfactual analysis, simulating alternative scenarios without vaccination or with faster vaccination roll-out. We estimated the direct effects of COVID-19 vaccination by computing the difference between hypothetical and realised scenarios. Findings: We estimated that more than 165,000 individuals above 60 years of age were not hospitalised due to COVID-19 in the first seven months of the vaccination campaign. An additional contingent of 104,000 hospitalisations could have been averted if vaccination had started earlier. We also estimated that more than 58 thousand lives were saved by vaccinations in the period analysed for the same age group and that an additional 47 thousand lives could have been saved had the Brazilian government started the vaccination programme earlier. Interpretation: Our estimates provided a lower bound for vaccination impacts in Brazil, demonstrating the importance of preventing the suffering and loss of older Brazilian adults. Once vaccines were approved, an early vaccination roll-out could have saved many more lives, especially when facing a pandemic. Funding: The Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–Brazil (Finance Code 001 to F.M.D.M. and L.S.F.), Conselho Nacional de Desenvolvimento Científico e Tecnológico – Brazil (grant number: 315854/2020-0 to M.E.B., 141698/2018-7 to R.L.P.d.S., 313055/2020-3 to P.I.P., 311832/2017-2 to R.A.K.), Fundação de Amparo à Pesquisa do Estado de São Paulo – Brazil (contract number: 2016/01343-7 to R.A.K.), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro – Brazil (grant number: E-26/201.277/2021 to L.S.B.) and Inova Fiocruz/Fundação Oswaldo Cruz – Brazil (grant number: 48401485034116) to L.S.B., O.G.C. and M.G.d.F.C. The funding agencies had no role in the conceptualization of the study.Instituto de Física Teórica Universidade Estadual PaulistaObservatório COVID-19 BRInstituto de Física ‘Gleb Wataghin’ and Instituto de Biologia Universidade Estadual de CampinasFundação Oswaldo Cruz Programa de Computação CientíficaCentro de Matemática Computação e Cognição Universidade Federal do ABCInstituto de Biociências Universidade de São PauloInstituto de Física Teórica Universidade Estadual PaulistaUniversidade Estadual Paulista (UNESP)Observatório COVID-19 BRUniversidade Estadual de Campinas (UNICAMP)Programa de Computação CientíficaUniversidade Federal do ABC (UFABC)Universidade de São Paulo (USP)Ferreira, Leonardo Souto [UNESP]Darcie Marquitti, Flavia MariaPaixão da Silva, Rafael Lopes [UNESP]Borges, Marcelo EduardoFerreira da Costa Gomes, MarceloCruz, Oswaldo GonçalvesKraenkel, Roberto André [UNESP]Coutinho, Renato MendesPrado, Paulo InácioBastos, Leonardo Soares2023-07-29T13:37:16Z2023-07-29T13:37:16Z2023-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.lana.2022.100397Lancet Regional Health - Americas, v. 17.2667-193Xhttp://hdl.handle.net/11449/24820010.1016/j.lana.2022.1003972-s2.0-85146326558Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengLancet Regional Health - Americasinfo:eu-repo/semantics/openAccess2023-07-29T13:37:17Zoai:repositorio.unesp.br:11449/248200Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:24:48.096101Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis |
title |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis |
spellingShingle |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis Ferreira, Leonardo Souto [UNESP] Bayesian model COVID-19 Deaths Hospitalisation Pandemic SARS-CoV-2 |
title_short |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis |
title_full |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis |
title_fullStr |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis |
title_full_unstemmed |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis |
title_sort |
Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis |
author |
Ferreira, Leonardo Souto [UNESP] |
author_facet |
Ferreira, Leonardo Souto [UNESP] Darcie Marquitti, Flavia Maria Paixão da Silva, Rafael Lopes [UNESP] Borges, Marcelo Eduardo Ferreira da Costa Gomes, Marcelo Cruz, Oswaldo Gonçalves Kraenkel, Roberto André [UNESP] Coutinho, Renato Mendes Prado, Paulo Inácio Bastos, Leonardo Soares |
author_role |
author |
author2 |
Darcie Marquitti, Flavia Maria Paixão da Silva, Rafael Lopes [UNESP] Borges, Marcelo Eduardo Ferreira da Costa Gomes, Marcelo Cruz, Oswaldo Gonçalves Kraenkel, Roberto André [UNESP] Coutinho, Renato Mendes Prado, Paulo Inácio Bastos, Leonardo Soares |
author2_role |
author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Observatório COVID-19 BR Universidade Estadual de Campinas (UNICAMP) Programa de Computação Científica Universidade Federal do ABC (UFABC) Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Ferreira, Leonardo Souto [UNESP] Darcie Marquitti, Flavia Maria Paixão da Silva, Rafael Lopes [UNESP] Borges, Marcelo Eduardo Ferreira da Costa Gomes, Marcelo Cruz, Oswaldo Gonçalves Kraenkel, Roberto André [UNESP] Coutinho, Renato Mendes Prado, Paulo Inácio Bastos, Leonardo Soares |
dc.subject.por.fl_str_mv |
Bayesian model COVID-19 Deaths Hospitalisation Pandemic SARS-CoV-2 |
topic |
Bayesian model COVID-19 Deaths Hospitalisation Pandemic SARS-CoV-2 |
description |
Background: Vaccines developed between 2020 and 2021 against the SARS-CoV-2 virus were designed to diminish the severity and prevent deaths due to COVID-19. However, estimates of the effectiveness of vaccination campaigns in achieving these goals remain a methodological challenge. In this work, we developed a Bayesian statistical model to estimate the number of deaths and hospitalisations averted by vaccination of older adults (above 60 years old) in Brazil. Methods: We fit a linear model to predict the number of deaths and hospitalisations of older adults as a function of vaccination coverage in this group and casualties in younger adults. We used this model in a counterfactual analysis, simulating alternative scenarios without vaccination or with faster vaccination roll-out. We estimated the direct effects of COVID-19 vaccination by computing the difference between hypothetical and realised scenarios. Findings: We estimated that more than 165,000 individuals above 60 years of age were not hospitalised due to COVID-19 in the first seven months of the vaccination campaign. An additional contingent of 104,000 hospitalisations could have been averted if vaccination had started earlier. We also estimated that more than 58 thousand lives were saved by vaccinations in the period analysed for the same age group and that an additional 47 thousand lives could have been saved had the Brazilian government started the vaccination programme earlier. Interpretation: Our estimates provided a lower bound for vaccination impacts in Brazil, demonstrating the importance of preventing the suffering and loss of older Brazilian adults. Once vaccines were approved, an early vaccination roll-out could have saved many more lives, especially when facing a pandemic. Funding: The Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–Brazil (Finance Code 001 to F.M.D.M. and L.S.F.), Conselho Nacional de Desenvolvimento Científico e Tecnológico – Brazil (grant number: 315854/2020-0 to M.E.B., 141698/2018-7 to R.L.P.d.S., 313055/2020-3 to P.I.P., 311832/2017-2 to R.A.K.), Fundação de Amparo à Pesquisa do Estado de São Paulo – Brazil (contract number: 2016/01343-7 to R.A.K.), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro – Brazil (grant number: E-26/201.277/2021 to L.S.B.) and Inova Fiocruz/Fundação Oswaldo Cruz – Brazil (grant number: 48401485034116) to L.S.B., O.G.C. and M.G.d.F.C. The funding agencies had no role in the conceptualization of the study. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07-29T13:37:16Z 2023-07-29T13:37:16Z 2023-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.lana.2022.100397 Lancet Regional Health - Americas, v. 17. 2667-193X http://hdl.handle.net/11449/248200 10.1016/j.lana.2022.100397 2-s2.0-85146326558 |
url |
http://dx.doi.org/10.1016/j.lana.2022.100397 http://hdl.handle.net/11449/248200 |
identifier_str_mv |
Lancet Regional Health - Americas, v. 17. 2667-193X 10.1016/j.lana.2022.100397 2-s2.0-85146326558 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Lancet Regional Health - Americas |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1808129198458404864 |