A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
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DC Field | Value | Language |
---|---|---|
dc.contributor | Diretoria Técnica | pt_BR |
dc.contributor.author | Tang, Yuanji | pt_BR |
dc.contributor.author | Serdan, Tamires D. A. | pt_BR |
dc.contributor.author | Alecrim, Amanda L. | pt_BR |
dc.contributor.author | Souza, Diego R. | pt_BR |
dc.contributor.author | Nacano, Bruno R. M. | pt_BR |
dc.contributor.author | Silva, Flaviano L. R. | pt_BR |
dc.contributor.author | Silva, Eliane B. | pt_BR |
dc.contributor.author | Poma, Sarah O. | pt_BR |
dc.contributor.author | Gennari-Felipe, Matheus | pt_BR |
dc.contributor.author | Iser-Bem, Patrícia N. | pt_BR |
dc.contributor.author | Masi, Laureane N. | pt_BR |
dc.contributor.author | Tang, Sherry | pt_BR |
dc.contributor.author | Levada-Pires, Adriana C. | pt_BR |
dc.contributor.author | Hatanaka, Elaine | pt_BR |
dc.contributor.author | Cury-Boaventura, Maria F. | pt_BR |
dc.contributor.author | Borges, Fernanda T. | pt_BR |
dc.contributor.author | Pithon-Curi, Tania C. | pt_BR |
dc.contributor.author | Curpertino, Marli C. | pt_BR |
dc.contributor.author | Fiamoncini, Jarlei | pt_BR |
dc.contributor.author | Leandro, Carol Gois | pt_BR |
dc.contributor.author | Gorjao, Renata | pt_BR |
dc.contributor.author | Curi, Rui | pt_BR |
dc.contributor.author | Hirabara, Sandro Massao | pt_BR |
dc.date.accessioned | 2021-09-03T16:51:00Z | - |
dc.date.available | 2021-09-03T16:51:00Z | - |
dc.date.issued | 2021 | pt_BR |
dc.identifier.citation | Tang Y, Serdan TD.A., Alecrim AL., Nacano BR.M., Silva FL.R., Silva EB., et al. A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil. Sci. Rep.. 2021 Aug;11:16400. doi:10.1038/s41598-021-95815-9. | pt_BR |
dc.identifier.uri | https://repositorio.butantan.gov.br/handle/butantan/3920 | - |
dc.description.abstract | We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic. | pt_BR |
dc.description.sponsorship | (FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo | pt_BR |
dc.description.sponsorship | (CAPES) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior | pt_BR |
dc.description.sponsorship | (CNPq) Conselho Nacional de Desenvolvimento Científico e Tecnológico | pt_BR |
dc.description.sponsorship | (JSGMF) John Simon Guggenheim Memorial Foundation | pt_BR |
dc.description.sponsorship | (UNICSUL) Universidade Cruzeiro do Sul | pt_BR |
dc.format.extent | 16400 | pt_BR |
dc.language.iso | English | pt_BR |
dc.relation.ispartof | Scientific Reports | pt_BR |
dc.rights | Open access | pt_BR |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | pt_BR |
dc.title | A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil | pt_BR |
dc.type | Article | pt_BR |
dc.rights.license | CC BY | pt_BR |
dc.identifier.doi | 10.1038/s41598-021-95815-9 | pt_BR |
dc.identifier.url | https://doi.org/10.1038/s41598-021-95815-9 | pt_BR |
dc.contributor.external | Applied NanoFemto Technologies | pt_BR |
dc.contributor.external | (UNICSUL) Universidade Cruzeiro do Sul | pt_BR |
dc.contributor.external | Kaiser Southern California Permanente Medical Group | pt_BR |
dc.contributor.external | (FADIP) Faculdade Dinâmica do Vale do Piranga | pt_BR |
dc.contributor.external | (UFV) Universidade Federal de Viçosa | pt_BR |
dc.contributor.external | (USP) Universidade de São Paulo | pt_BR |
dc.contributor.external | (FoRC) Food Research Center | pt_BR |
dc.contributor.external | (UFPE) Universidade Federal de Pernambuco | pt_BR |
dc.identifier.citationvolume | 11 | pt_BR |
dc.subject.keyword | Computational models | pt_BR |
dc.subject.keyword | epidemiology | pt_BR |
dc.subject.keyword | Viral infection | pt_BR |
dc.relation.ispartofabbreviated | Sci Rep | pt_BR |
dc.identifier.citationabnt | v. 11, 16400, ago. 2021 | pt_BR |
dc.identifier.citationvancouver | 2021 Aug;11:16400 | pt_BR |
dc.contributor.butantan | Curi, Rui|:Outros|:Diretoria Técnica | pt_BR |
dc.sponsorship.butantan | (FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo¦¦16/14529-1 | pt_BR |
dc.sponsorship.butantan | (FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo¦¦18/09868-7 | pt_BR |
dc.sponsorship.butantan | (FAPESP) Fundação de Amparo à Pesquisa do Estado de São Paulo¦¦2020/09107-6 | pt_BR |
dc.sponsorship.butantan | (CAPES) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior¦¦ | pt_BR |
dc.sponsorship.butantan | (CNPq) Conselho Nacional de Desenvolvimento Científico e Tecnológico¦¦ | pt_BR |
dc.sponsorship.butantan | (JSGMF) John Simon Guggenheim Memorial Foundation¦¦ | pt_BR |
dc.sponsorship.butantan | (UNICSUL) Universidade Cruzeiro do Sul¦¦ | pt_BR |
dc.identifier.bvscc | BR78.1 | pt_BR |
dc.identifier.bvsdb | IBProd | pt_BR |
dc.description.dbindexed | Yes | pt_BR |
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item.languageiso639-1 | English | - |
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