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Estimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysis

dc.contributor.authorFerreira, Leonardo Souto [UNESP]
dc.contributor.authorDarcie Marquitti, Flavia Maria
dc.contributor.authorPaixão da Silva, Rafael Lopes [UNESP]
dc.contributor.authorBorges, Marcelo Eduardo
dc.contributor.authorFerreira da Costa Gomes, Marcelo
dc.contributor.authorCruz, Oswaldo Gonçalves
dc.contributor.authorKraenkel, Roberto André [UNESP]
dc.contributor.authorCoutinho, Renato Mendes
dc.contributor.authorPrado, Paulo Inácio
dc.contributor.authorBastos, Leonardo Soares
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionObservatório COVID-19 BR
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionPrograma de Computação Científica
dc.contributor.institutionUniversidade Federal do ABC (UFABC)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2023-07-29T13:37:16Z
dc.date.available2023-07-29T13:37:16Z
dc.date.issued2023-01-01
dc.description.abstractBackground: 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.en
dc.description.affiliationInstituto de Física Teórica Universidade Estadual Paulista
dc.description.affiliationObservatório COVID-19 BR
dc.description.affiliationInstituto de Física ‘Gleb Wataghin’ and Instituto de Biologia Universidade Estadual de Campinas
dc.description.affiliationFundação Oswaldo Cruz Programa de Computação Científica
dc.description.affiliationCentro de Matemática Computação e Cognição Universidade Federal do ABC
dc.description.affiliationInstituto de Biociências Universidade de São Paulo
dc.description.affiliationUnespInstituto de Física Teórica Universidade Estadual Paulista
dc.identifierhttp://dx.doi.org/10.1016/j.lana.2022.100397
dc.identifier.citationLancet Regional Health - Americas, v. 17.
dc.identifier.doi10.1016/j.lana.2022.100397
dc.identifier.issn2667-193X
dc.identifier.scopus2-s2.0-85146326558
dc.identifier.urihttp://hdl.handle.net/11449/248200
dc.language.isoeng
dc.relation.ispartofLancet Regional Health - Americas
dc.sourceScopus
dc.subjectBayesian model
dc.subjectCOVID-19
dc.subjectDeaths
dc.subjectHospitalisation
dc.subjectPandemic
dc.subjectSARS-CoV-2
dc.titleEstimating the impact of implementation and timing of the COVID-19 vaccination programme in Brazil: a counterfactual analysisen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0002-9023-0031 0000-0002-9023-0031[1]
unesp.author.orcid0000-0003-0510-3992 0000-0003-0510-3992[2]
unesp.author.orcid0000-0002-9416-6145 0000-0002-9416-6145[3]
unesp.author.orcid0000-0002-5807-3064[4]
unesp.author.orcid0000-0003-4693-5402 0000-0003-4693-5402[5]
unesp.author.orcid0000-0002-3289-3195 0000-0002-3289-3195[6]
unesp.author.orcid0000-0001-5602-5184 0000-0001-5602-5184[7]
unesp.author.orcid0000-0002-2828-8558 0000-0002-2828-8558[8]
unesp.author.orcid0000-0002-7174-5005 0000-0002-7174-5005[9]
unesp.author.orcid0000-0002-1406-0122 0000-0002-1406-0122[10]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Física Teórica (IFT), São Paulopt

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