Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply

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dc.contributorDiretoria Técnicapt_BR
dc.contributor.authorAmaku, Marcospt_BR
dc.contributor.authorCovas, Dimas Tadeupt_BR
dc.contributor.authorCoutinho, Francisco Antonio Bezerrapt_BR
dc.contributor.authorAzevedo, Raymundo Soarespt_BR
dc.contributor.authorMassad, Eduardopt_BR
dc.date.accessioned2021-08-17T19:43:31Z-
dc.date.available2021-08-17T19:43:31Z-
dc.date.issued2021pt_BR
dc.identifier.citationAmaku M, Covas DT, Coutinho FAB, Azevedo RS, Massad E. Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply. Theor. Biol. Med. Model.. 2021 July;18:14. doi:10.1186/s12976-021-00143-0.pt_BR
dc.identifier.urihttps://repositorio.butantan.gov.br/handle/butantan/3914-
dc.description.abstractBackground At the moment we have more than 177 million cases and 3.8 million deaths (as of June 2021) around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far. Methods We propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus disease (COVID-19) on the number of cases and deaths due to the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations. Results The model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths will occur by the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, for each month of delay the number of deaths increases monotonically in a logarithmic fashion, for both the State of Sao Paulo and Brazil as a whole. Conclusions Our model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.pt_BR
dc.description.sponsorshipUniversidade de São Paulo (USP)pt_BR
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.description.sponsorshipFundação Butantanpt_BR
dc.format.extent14pt_BR
dc.language.isoEnglishpt_BR
dc.relation.ispartofTheoretical Biology & Medical Modellingpt_BR
dc.rightsOpen Accesspt_BR
dc.titleModelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supplypt_BR
dc.typeArticlept_BR
dc.identifier.doi10.1186/s12976-021-00143-0pt_BR
dc.identifier.urlhttps://doi.org/10.1186/s12976-021-00143-0pt_BR
dc.contributor.externalUniversidade de São Paulo (USP)pt_BR
dc.contributor.externalFundação Getulio Vargas (FGV)pt_BR
dc.contributor.externalThe London School of Hygiene & Tropical Medicine (LSHTM)pt_BR
dc.identifier.citationvolume18pt_BR
dc.subject.keywordCOVID-19pt_BR
dc.subject.keywordSARS-CoV-2pt_BR
dc.subject.keywordMathematical Modelspt_BR
dc.subject.keywordVaccinespt_BR
dc.relation.ispartofabbreviatedTheor. Biol. Med. Model.pt_BR
dc.identifier.citationabntv. 18, 14, jul. 2021pt_BR
dc.identifier.citationvancouver2021 July;18:14pt_BR
dc.contributor.butantanCovas, Dimas Tadeu|:Diretor|:Diretoria Técnicapt_BR
dc.sponsorship.butantanUniversidade de São Paulo (USP)¦¦pt_BR
dc.sponsorship.butantanConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)¦¦pt_BR
dc.sponsorship.butantanFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)¦¦pt_BR
dc.sponsorship.butantanFundação Butantan¦¦pt_BR
dc.identifier.bvsccBR78.1pt_BR
dc.identifier.bvsdbIBProdpt_BR
dc.description.dbindexedYespt_BR
item.grantfulltextembargo_29990101-
item.languageiso639-1English-
item.openairetypeArticle-
item.fulltextCom Texto completo-
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