Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply
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DC Field | Value | Language |
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dc.contributor | Diretoria Técnica | pt_BR |
dc.contributor.author | Amaku, Marcos | pt_BR |
dc.contributor.author | Covas, Dimas Tadeu | pt_BR |
dc.contributor.author | Coutinho, Francisco Antonio Bezerra | pt_BR |
dc.contributor.author | Azevedo, Raymundo Soares | pt_BR |
dc.contributor.author | Massad, Eduardo | pt_BR |
dc.date.accessioned | 2021-08-17T19:43:31Z | - |
dc.date.available | 2021-08-17T19:43:31Z | - |
dc.date.issued | 2021 | pt_BR |
dc.identifier.citation | Amaku 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.uri | https://repositorio.butantan.gov.br/handle/butantan/3914 | - |
dc.description.abstract | Background 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.sponsorship | (USP) Universidade de São Paulo | pt_BR |
dc.description.sponsorship | (CNPq) Conselho Nacional de Desenvolvimento Científico e Tecnológico | pt_BR |
dc.description.sponsorship | (FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo | pt_BR |
dc.format.extent | 14 | pt_BR |
dc.language.iso | English | pt_BR |
dc.relation.ispartof | Theoretical Biology & Medical Modelling | pt_BR |
dc.rights | Open access | pt_BR |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | pt_BR |
dc.title | Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply | pt_BR |
dc.type | Article | pt_BR |
dc.rights.license | CC BY | pt_BR |
dc.identifier.doi | 10.1186/s12976-021-00143-0 | pt_BR |
dc.identifier.url | https://doi.org/10.1186/s12976-021-00143-0 | pt_BR |
dc.contributor.external | (USP) Universidade de São Paulo | pt_BR |
dc.contributor.external | (FGV) Fundação Getulio Vargas | pt_BR |
dc.contributor.external | (LSHTM) The London School of Hygiene & Tropical Medicine | pt_BR |
dc.identifier.citationvolume | 18 | pt_BR |
dc.subject.keyword | COVID-19 | pt_BR |
dc.subject.keyword | SARS-CoV-2 | pt_BR |
dc.subject.keyword | Mathematical Models | pt_BR |
dc.subject.keyword | vaccines | pt_BR |
dc.relation.ispartofabbreviated | Theor. Biol. Med. Model. | pt_BR |
dc.identifier.citationabnt | v. 18, 14, jul. 2021 | pt_BR |
dc.identifier.citationvancouver | 2021 July;18:14 | pt_BR |
dc.contributor.butantan | Covas, Dimas Tadeu|:Diretor|:Diretoria Técnica | pt_BR |
dc.sponsorship.butantan | Universidade de São Paulo (USP)¦¦ | pt_BR |
dc.sponsorship.butantan | (CNPq) Conselho Nacional de Desenvolvimento Científico e Tecnológico¦¦ | pt_BR |
dc.sponsorship.butantan | (FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo¦¦ | pt_BR |
dc.sponsorship.butantan | Fundação Butantan¦¦ | pt_BR |
dc.identifier.bvscc | BR78.1 | pt_BR |
dc.identifier.bvsdb | IBProd | pt_BR |
dc.description.dbindexed | Yes | pt_BR |
item.grantfulltext | open | - |
item.fulltext | Com Texto completo | - |
item.openairetype | Article | - |
item.languageiso639-1 | English | - |
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