A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means

Detalhes bibliográficos
Autor(a) principal: Alves, Henrique José de Paula
Data de Publicação: 2020
Outros Autores: Fernandes, Felipe Augusto, Lima, Kelly Pereira de, Batista, Ben Dêivide de Oliveira, Fernandes, Tales Jesus
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/46704
Resumo: COVID-19 is an infection caused by the SARS-CoV-2 coronavirus, its first records were in the Chinese city of Wuhan in December 2019, and was considered by the World Health Organization (WHO) to be a worldwide pandemic in March 2020. In Brazil, COVID-19 spread to 27 states (UFs). As a result, decision-making to decrease the speed of transmission was based on WHO recommendations, where the main one is social isolation. However, due to the heterogeneity of the population in each of the UFs, the pandemic spread differently. Thus, it is interesting to group UFs by similarity due to some characteristics, and thus, observe the measures to combat COVID-19 carried out in each of these groups. The aim of this study was to group UFs using cluster analysis using the non-hierarchical k-means method considering the epidemiological coefficients such as incidence, prevalence, and lethality. The data were obtained from the website of the Ministry of Health of Brazil and consisted of the variables number of cases and new and accumulated deaths in UFs, in addition to the population at risk. For cluster analysis, the database was divided into three chronological periods for the three coefficients under study. With the cluster analysis, it was possible to verify the stratification of UFs according to their similarities in relation to COVID-19. Thus,the stratification of incidence, prevalence, and lethality by UFs can present itself as an additional resource to signal which places and which measures should be adopted and where these measures were effective.
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spelling A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-meansThe COVID-19 pandemic in Brazil: an application of the k-means clustering methodLa pandemia de COVID-19 en Brasil: una aplicación del método de agrupamiento de k-mediasCOVID-19Sars-CoV-2CoronavirusClustersCOVID-19 is an infection caused by the SARS-CoV-2 coronavirus, its first records were in the Chinese city of Wuhan in December 2019, and was considered by the World Health Organization (WHO) to be a worldwide pandemic in March 2020. In Brazil, COVID-19 spread to 27 states (UFs). As a result, decision-making to decrease the speed of transmission was based on WHO recommendations, where the main one is social isolation. However, due to the heterogeneity of the population in each of the UFs, the pandemic spread differently. Thus, it is interesting to group UFs by similarity due to some characteristics, and thus, observe the measures to combat COVID-19 carried out in each of these groups. The aim of this study was to group UFs using cluster analysis using the non-hierarchical k-means method considering the epidemiological coefficients such as incidence, prevalence, and lethality. The data were obtained from the website of the Ministry of Health of Brazil and consisted of the variables number of cases and new and accumulated deaths in UFs, in addition to the population at risk. For cluster analysis, the database was divided into three chronological periods for the three coefficients under study. With the cluster analysis, it was possible to verify the stratification of UFs according to their similarities in relation to COVID-19. Thus,the stratification of incidence, prevalence, and lethality by UFs can present itself as an additional resource to signal which places and which measures should be adopted and where these measures were effective.A COVID-19 é uma infecçãocausada pelo coronavírus SARS-CoV-2,sendo que seus primeiros registros foram na cidade chinesa de Wuhan em dezembro de 2019, e foi considerada pela OrganizaçãoMundial da Saúde (OMS)uma pandemia mundial em março de 2020. No Brasil, a COVID-19se espalhouatingindo as 27 unidades federativas (UFs). Com isso, as tomadas de decisõespara diminuir a velocidade de transmissão forambaseadasnas recomendações da OMS, onde a principal é isolamento social. Entretanto, devido a heterogeneidade da população emcada uma das UFs, a pandemia se difundiu de forma distinta. Deste modo, é interessante fazer o agrupamento das UFs por similaridade devido algumas características,e assim,observar as medidas de combate a COVID-19 realizadas em cada um desse grupos.Oobjetivo deste estudo foi agrupar as UFs usando análise de cluster pelo método não-hierárquico k-means considerando os coeficientes epidemiológicos como incidência, prevalência e letalidade. Os dados foram obtidos do sitedo Ministério da Saúde do Brasil e foi constituído pelas variáveis número de casos e óbitos novos e acumulados nas UFs, além da população em risco. Para análise de cluster a base de dados foi dividida em três períodos cronológicospara os três coeficientes em estudo. Com a análise de cluster foi possível verificar a estratificação da UFs conforme suas similaridades em relação a COVID-19. Assim, a estratificação da incidência, prevalência e letalidadepor UFs pode se apresentar como um recurso adicional para sinalizar quais locais e quais medidasdeverãoser adotadase onde essas medidas foram eficazes.Research, Society and Development2021-07-09T16:45:21Z2021-07-09T16:45:21Z2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfALVES, H. J. de P. et al. A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means. Research, Society and Development, [S. l.], v. 9, n.10, e5829109059, 2020. DOI: 10.33448/rsd-v9i10.9059.http://repositorio.ufla.br/jspui/handle/1/46704Research, Society and Developmentreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessAlves, Henrique José de PaulaFernandes, Felipe AugustoLima, Kelly Pereira deBatista, Ben Dêivide de OliveiraFernandes, Tales Jesuspor2021-07-09T16:45:22Zoai:localhost:1/46704Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-07-09T16:45:22Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
The COVID-19 pandemic in Brazil: an application of the k-means clustering method
La pandemia de COVID-19 en Brasil: una aplicación del método de agrupamiento de k-medias
title A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
spellingShingle A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
Alves, Henrique José de Paula
COVID-19
Sars-CoV-2
Coronavirus
Clusters
title_short A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
title_full A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
title_fullStr A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
title_full_unstemmed A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
title_sort A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means
author Alves, Henrique José de Paula
author_facet Alves, Henrique José de Paula
Fernandes, Felipe Augusto
Lima, Kelly Pereira de
Batista, Ben Dêivide de Oliveira
Fernandes, Tales Jesus
author_role author
author2 Fernandes, Felipe Augusto
Lima, Kelly Pereira de
Batista, Ben Dêivide de Oliveira
Fernandes, Tales Jesus
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Alves, Henrique José de Paula
Fernandes, Felipe Augusto
Lima, Kelly Pereira de
Batista, Ben Dêivide de Oliveira
Fernandes, Tales Jesus
dc.subject.por.fl_str_mv COVID-19
Sars-CoV-2
Coronavirus
Clusters
topic COVID-19
Sars-CoV-2
Coronavirus
Clusters
description COVID-19 is an infection caused by the SARS-CoV-2 coronavirus, its first records were in the Chinese city of Wuhan in December 2019, and was considered by the World Health Organization (WHO) to be a worldwide pandemic in March 2020. In Brazil, COVID-19 spread to 27 states (UFs). As a result, decision-making to decrease the speed of transmission was based on WHO recommendations, where the main one is social isolation. However, due to the heterogeneity of the population in each of the UFs, the pandemic spread differently. Thus, it is interesting to group UFs by similarity due to some characteristics, and thus, observe the measures to combat COVID-19 carried out in each of these groups. The aim of this study was to group UFs using cluster analysis using the non-hierarchical k-means method considering the epidemiological coefficients such as incidence, prevalence, and lethality. The data were obtained from the website of the Ministry of Health of Brazil and consisted of the variables number of cases and new and accumulated deaths in UFs, in addition to the population at risk. For cluster analysis, the database was divided into three chronological periods for the three coefficients under study. With the cluster analysis, it was possible to verify the stratification of UFs according to their similarities in relation to COVID-19. Thus,the stratification of incidence, prevalence, and lethality by UFs can present itself as an additional resource to signal which places and which measures should be adopted and where these measures were effective.
publishDate 2020
dc.date.none.fl_str_mv 2020
2021-07-09T16:45:21Z
2021-07-09T16:45:21Z
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 ALVES, H. J. de P. et al. A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means. Research, Society and Development, [S. l.], v. 9, n.10, e5829109059, 2020. DOI: 10.33448/rsd-v9i10.9059.
http://repositorio.ufla.br/jspui/handle/1/46704
identifier_str_mv ALVES, H. J. de P. et al. A pandemia da COVID-19 no Brasil: uma aplicação do método de clusterização k-means. Research, Society and Development, [S. l.], v. 9, n.10, e5829109059, 2020. DOI: 10.33448/rsd-v9i10.9059.
url http://repositorio.ufla.br/jspui/handle/1/46704
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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