Dinâmica espacial da Covid-19 no Estado do Maranhão

Detalhes bibliográficos
Autor(a) principal: ALVES, Jordana Maria Freitas
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFMA
Texto Completo: https://tedebc.ufma.br/jspui/handle/tede/tede/3560
Resumo: Covid-19, a disease caused by the SARS-CoV-2 coronavirus, elevated to pandemic level in March 2020, has raised health concerns due to the significant indicators of morbidity and mortality observed. Since it is a recent disease, it is essential to know its epidemiological behavior and regions of prevalence. Spatial analysis methods are efficient for the identification of risk areas, providing subsidies for the optimization of public health policies. The objective of this study was to analyze the spatial distribution of cases and deaths caused by Covid-19 in the state of Maranhão. We carried out an ecological study of the spatial distribution of cases (incidence) and deaths (mortality and lethality), using as unit of analysis the municipalities of Maranhão. The study population included all cases reported in the state of Maranhão between 20.03.2020 and 07.07.2021 and all deaths recorded in the period from 29.03.2020 to 07.07.2021, totaling 323,043 cases and 9,225 deaths. The data were collected from the database of the Maranhão State Department of Health (SES). The population estimates correspond to the year 2020 obtained through the meshes of the Brazilian Institute of Geography and Statistics (IBGE). Incidence, mortality and lethality rates were estimated for the 217 municipalities of Maranhão with the elaboration of thematic maps using the QGis software. The spatial dependence was identified through the Global Moran Index and the delimitation of risk clusters through the Local Moran Index, using the GeoDa software. The results show that the municipalities with the highest incidence per 100,000 inhabitants were: Lagoa do Mato (17,940.5), Feira Nova do Maranhão (17,810.0), Igarapé Grande (14,788.8) and São Raimundo das Mangabeiras (11,375.1) and the lowest incidence in Boa Vista do Gurupi (178.95). In the analysis of mortality per 100,000 inhabitants, the highest rates were in Campestre do Maranhão (304.4), Imperatriz (303.1), João Lisboa (235.9) and Porto Franco (224.1). In relation to lethality, the highest rates were in Boa Vista do Gurupi (26.6%), Paço do Lumiar (21.2%), and Viana (11.9%). The health indicators showed positive spatial autocorrelation, being the Global Moran indexes of incidence 0.328, mortality 0.348 and lethality 0.161, with p < 0.05. The high- risk clusters for incidence, mortality and lethality were detected located, respectively, in the Central and Southern mesoregion, the Northern mesoregion and the Western maranhense mesoregion. It is concluded that the cases and deaths of Covid-19 were heterogeneously distributed in the municipalities, with positive spatial autocorrelation and formation of high- risk clusters for incidence, mortality and lethality, with areas of predominance, influenced by the intermunicipal flow of people, limited access and availability of health services. The local social and demographic characteristics of the municipalities should be considered in future investigations for a better understanding of the dynamics of the disease, as well as to verify whether the health services are satisfactorily organized and sensitive to the local reality. The findings of this study can contribute to the strengthening of health policies to combat the pandemic, by providing subsidies for the development of strategies aimed at reducing the indicators.
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spelling CALDAS, Arlene de Jesus Mendeshttp://lattes.cnpq.br/7214761052240294CALDAS, Arlene de Jesus Mendeshttp://lattes.cnpq.br/7214761052240294VASCONCELOS, Vitor Vieirahttp://lattes.cnpq.br/8151243279050980SANTOS NETO, Marcelinohttp://lattes.cnpq.br/2762193275718620http://lattes.cnpq.br/5988795618477040ALVES, Jordana Maria Freitas2022-05-10T14:21:39Z2022-02-24ALVES, Jordana Maria Freitas. Dinâmica espacial da Covid-19 no Estado do Maranhão. 2022. 86 f. Dissertação (Programa de Pós-Graduação em Enfermagem/CCBS) - Universidade Federal do Maranhão, São Luís, 2022.https://tedebc.ufma.br/jspui/handle/tede/tede/3560Covid-19, a disease caused by the SARS-CoV-2 coronavirus, elevated to pandemic level in March 2020, has raised health concerns due to the significant indicators of morbidity and mortality observed. Since it is a recent disease, it is essential to know its epidemiological behavior and regions of prevalence. Spatial analysis methods are efficient for the identification of risk areas, providing subsidies for the optimization of public health policies. The objective of this study was to analyze the spatial distribution of cases and deaths caused by Covid-19 in the state of Maranhão. We carried out an ecological study of the spatial distribution of cases (incidence) and deaths (mortality and lethality), using as unit of analysis the municipalities of Maranhão. The study population included all cases reported in the state of Maranhão between 20.03.2020 and 07.07.2021 and all deaths recorded in the period from 29.03.2020 to 07.07.2021, totaling 323,043 cases and 9,225 deaths. The data were collected from the database of the Maranhão State Department of Health (SES). The population estimates correspond to the year 2020 obtained through the meshes of the Brazilian Institute of Geography and Statistics (IBGE). Incidence, mortality and lethality rates were estimated for the 217 municipalities of Maranhão with the elaboration of thematic maps using the QGis software. The spatial dependence was identified through the Global Moran Index and the delimitation of risk clusters through the Local Moran Index, using the GeoDa software. The results show that the municipalities with the highest incidence per 100,000 inhabitants were: Lagoa do Mato (17,940.5), Feira Nova do Maranhão (17,810.0), Igarapé Grande (14,788.8) and São Raimundo das Mangabeiras (11,375.1) and the lowest incidence in Boa Vista do Gurupi (178.95). In the analysis of mortality per 100,000 inhabitants, the highest rates were in Campestre do Maranhão (304.4), Imperatriz (303.1), João Lisboa (235.9) and Porto Franco (224.1). In relation to lethality, the highest rates were in Boa Vista do Gurupi (26.6%), Paço do Lumiar (21.2%), and Viana (11.9%). The health indicators showed positive spatial autocorrelation, being the Global Moran indexes of incidence 0.328, mortality 0.348 and lethality 0.161, with p < 0.05. The high- risk clusters for incidence, mortality and lethality were detected located, respectively, in the Central and Southern mesoregion, the Northern mesoregion and the Western maranhense mesoregion. It is concluded that the cases and deaths of Covid-19 were heterogeneously distributed in the municipalities, with positive spatial autocorrelation and formation of high- risk clusters for incidence, mortality and lethality, with areas of predominance, influenced by the intermunicipal flow of people, limited access and availability of health services. The local social and demographic characteristics of the municipalities should be considered in future investigations for a better understanding of the dynamics of the disease, as well as to verify whether the health services are satisfactorily organized and sensitive to the local reality. The findings of this study can contribute to the strengthening of health policies to combat the pandemic, by providing subsidies for the development of strategies aimed at reducing the indicators.A Covid-19, doença causada pelo coronavírus SARS-CoV-2, elevada a nível de pandemia em março de 2020, tem trazido preocupações sanitárias em função dos expressivos indicadores de morbimortalidade observados. Por tratar-se de uma doença recente, é essencial conhecer seu comportamento epidemiológico e regiões de predominância. Métodos de análise espacial são eficientes para a identificação das áreas de risco, fornecendo subsídios para a otimização de políticas públicas de saúde. O objetivo desse estudo foi analisar a distribuição espacial dos casos e óbitos causados pela Covid-19 no estado do Maranhão. Realizou-se estudo ecológico da distribuição espacial de casos (incidência) e óbitos (mortalidade e letalidade), tendo como unidade de análise os municípios maranhenses. A população do estudo incluiu todos os casos notificados no estado do Maranhão entre 20.03.2020 e 07.07.2021 e todos os óbitos registrados no período de 29.03.2020 a 07.07.2021, totalizando 323.043 casos e 9.225 óbitos. Os dados foram coletados a partir do banco de dados da Secretaria de Estado da Saúde (SES) do Maranhão. As estimativas populacionais correspondem ao ano de 2020 obtidas por meio das malhas do Instituto Brasileiro de Geografia e Estatística (IBGE). Foram estimadas as taxas de incidência, mortalidade e letalidade para os 217 municípios maranhenses com elaboração de mapas temáticos utilizando o software QGis. A dependência espacial foi identificada por meio do Índice de Moran Global e a delimitação dos clusters de risco por meio do Índice de Moran Local, utilizando o software GeoDa. Os resultados apontam que os municípios com as maiores incidências por 100 mil habitantes foram: Lagoa do Mato (17.940,5), Feira Nova do Maranhão (17.810,0), Igarapé Grande (14.788,8) e São Raimundo das Mangabeiras (11.375,1) e menor incidência em Boa Vista do Gurupi (178,95). Na análise da mortalidade por 100 mil habitantes, as maiores taxas foram em Campestre do Maranhão (304,4), Imperatriz (303,1), João Lisboa (235,9) e Porto Franco (224,1). Em relação à letalidade, as maiores taxas foram em Boa Vista do Gurupi (26,6%), Paço do Lumiar (21,2%) e Viana (11,9%). Os indicadores de saúde apresentaram autocorrelação espacial positiva, sendo os índices de Moran Global de incidência 0,328, de mortalidade 0,348 e de letalidade 0,161, com p < 0,05. Foram detectados os clusters de alto risco para incidência, mortalidade e letalidade localizados, respectivamente, na mesorregião Centro e Sul, na mesorregião Norte e na mesorregião Oeste maranhense. Conclui- se que os casos e óbitos da Covid-19 distribuíram-se de forma heterogênea nos municípios, com autocorrelação espacial positiva e formação de clusters de alto risco para incidência, mortalidade e letalidade, com áreas de predominância, influenciadas pelo fluxo intermunicipal de pessoas, limitação do acesso e disponibilidade dos serviços de saúde. As características locais, sociais e demográficas dos municípios devem ser consideradas em investigações futuras para um melhor entendimento da dinâmica da doença, assim como para verificar se os serviços de saúde estão organizados de forma satisfatória e se são sensíveis à realidade local. Os achados desse estudo podem contribuir para o fortalecimento das políticas de saúde de combate à pandemia, por fornecerem subsídios para a elaboração de estratégias que visem à redução dos indicadores.Submitted by Jonathan Sousa de Almeida (jonathan.sousa@ufma.br) on 2022-05-10T14:21:39Z No. of bitstreams: 1 JORDANAMARIAFREITASALVES.pdf: 244503 bytes, checksum: 5ce6b134f46458ef4cf3df677e2a5b42 (MD5)Made available in DSpace on 2022-05-10T14:21:39Z (GMT). No. of bitstreams: 1 JORDANAMARIAFREITASALVES.pdf: 244503 bytes, checksum: 5ce6b134f46458ef4cf3df677e2a5b42 (MD5) Previous issue date: 2022-02-24FAPEMAapplication/pdfporUniversidade Federal do MaranhãoPROGRAMA DE PÓS-GRADUAÇÃO EM ENFERMAGEM/CCBSUFMABrasilDEPARTAMENTO DE ENFERMAGEM/CCBSCovid-19;indicadores de saúde;análise espacial.Covid-19;health indicators;spatial analysis.Enfermagem de Doenças ContagiosasCiências da SaúdeDinâmica espacial da Covid-19 no Estado do MaranhãoSpatial dynamics of Covid-19 in the state of MaranhãoDocumento sob sigilo. Prazo provável para disponibilização total: 24/02/2025. Motivo do sigilo: publicação de artigoinfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFMAinstname:Universidade Federal do Maranhão (UFMA)instacron:UFMAORIGINALJORDANAMARIAFREITASALVES.pdfJORDANAMARIAFREITASALVES.pdfapplication/pdf244503http://tedebc.ufma.br:8080/bitstream/tede/3560/2/JORDANAMARIAFREITASALVES.pdf5ce6b134f46458ef4cf3df677e2a5b42MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82255http://tedebc.ufma.br:8080/bitstream/tede/3560/1/license.txt97eeade1fce43278e63fe063657f8083MD51tede/35602023-05-16 12:57:26.252oai:tede2: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Biblioteca Digital de Teses e Dissertaçõeshttps://tedebc.ufma.br/jspui/PUBhttp://tedebc.ufma.br:8080/oai/requestrepositorio@ufma.br||repositorio@ufma.bropendoar:21312023-05-16T15:57:26Biblioteca Digital de Teses e Dissertações da UFMA - Universidade Federal do Maranhão (UFMA)false
dc.title.por.fl_str_mv Dinâmica espacial da Covid-19 no Estado do Maranhão
dc.title.alternative.eng.fl_str_mv Spatial dynamics of Covid-19 in the state of Maranhão
title Dinâmica espacial da Covid-19 no Estado do Maranhão
spellingShingle Dinâmica espacial da Covid-19 no Estado do Maranhão
ALVES, Jordana Maria Freitas
Covid-19;
indicadores de saúde;
análise espacial.
Covid-19;
health indicators;
spatial analysis.
Enfermagem de Doenças Contagiosas
Ciências da Saúde
title_short Dinâmica espacial da Covid-19 no Estado do Maranhão
title_full Dinâmica espacial da Covid-19 no Estado do Maranhão
title_fullStr Dinâmica espacial da Covid-19 no Estado do Maranhão
title_full_unstemmed Dinâmica espacial da Covid-19 no Estado do Maranhão
title_sort Dinâmica espacial da Covid-19 no Estado do Maranhão
author ALVES, Jordana Maria Freitas
author_facet ALVES, Jordana Maria Freitas
author_role author
dc.contributor.advisor1.fl_str_mv CALDAS, Arlene de Jesus Mendes
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/7214761052240294
dc.contributor.referee1.fl_str_mv CALDAS, Arlene de Jesus Mendes
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/7214761052240294
dc.contributor.referee2.fl_str_mv VASCONCELOS, Vitor Vieira
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/8151243279050980
dc.contributor.referee3.fl_str_mv SANTOS NETO, Marcelino
dc.contributor.referee3Lattes.fl_str_mv http://lattes.cnpq.br/2762193275718620
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/5988795618477040
dc.contributor.author.fl_str_mv ALVES, Jordana Maria Freitas
contributor_str_mv CALDAS, Arlene de Jesus Mendes
CALDAS, Arlene de Jesus Mendes
VASCONCELOS, Vitor Vieira
SANTOS NETO, Marcelino
dc.subject.por.fl_str_mv Covid-19;
indicadores de saúde;
análise espacial.
topic Covid-19;
indicadores de saúde;
análise espacial.
Covid-19;
health indicators;
spatial analysis.
Enfermagem de Doenças Contagiosas
Ciências da Saúde
dc.subject.eng.fl_str_mv Covid-19;
health indicators;
spatial analysis.
dc.subject.cnpq.fl_str_mv Enfermagem de Doenças Contagiosas
Ciências da Saúde
description Covid-19, a disease caused by the SARS-CoV-2 coronavirus, elevated to pandemic level in March 2020, has raised health concerns due to the significant indicators of morbidity and mortality observed. Since it is a recent disease, it is essential to know its epidemiological behavior and regions of prevalence. Spatial analysis methods are efficient for the identification of risk areas, providing subsidies for the optimization of public health policies. The objective of this study was to analyze the spatial distribution of cases and deaths caused by Covid-19 in the state of Maranhão. We carried out an ecological study of the spatial distribution of cases (incidence) and deaths (mortality and lethality), using as unit of analysis the municipalities of Maranhão. The study population included all cases reported in the state of Maranhão between 20.03.2020 and 07.07.2021 and all deaths recorded in the period from 29.03.2020 to 07.07.2021, totaling 323,043 cases and 9,225 deaths. The data were collected from the database of the Maranhão State Department of Health (SES). The population estimates correspond to the year 2020 obtained through the meshes of the Brazilian Institute of Geography and Statistics (IBGE). Incidence, mortality and lethality rates were estimated for the 217 municipalities of Maranhão with the elaboration of thematic maps using the QGis software. The spatial dependence was identified through the Global Moran Index and the delimitation of risk clusters through the Local Moran Index, using the GeoDa software. The results show that the municipalities with the highest incidence per 100,000 inhabitants were: Lagoa do Mato (17,940.5), Feira Nova do Maranhão (17,810.0), Igarapé Grande (14,788.8) and São Raimundo das Mangabeiras (11,375.1) and the lowest incidence in Boa Vista do Gurupi (178.95). In the analysis of mortality per 100,000 inhabitants, the highest rates were in Campestre do Maranhão (304.4), Imperatriz (303.1), João Lisboa (235.9) and Porto Franco (224.1). In relation to lethality, the highest rates were in Boa Vista do Gurupi (26.6%), Paço do Lumiar (21.2%), and Viana (11.9%). The health indicators showed positive spatial autocorrelation, being the Global Moran indexes of incidence 0.328, mortality 0.348 and lethality 0.161, with p < 0.05. The high- risk clusters for incidence, mortality and lethality were detected located, respectively, in the Central and Southern mesoregion, the Northern mesoregion and the Western maranhense mesoregion. It is concluded that the cases and deaths of Covid-19 were heterogeneously distributed in the municipalities, with positive spatial autocorrelation and formation of high- risk clusters for incidence, mortality and lethality, with areas of predominance, influenced by the intermunicipal flow of people, limited access and availability of health services. The local social and demographic characteristics of the municipalities should be considered in future investigations for a better understanding of the dynamics of the disease, as well as to verify whether the health services are satisfactorily organized and sensitive to the local reality. The findings of this study can contribute to the strengthening of health policies to combat the pandemic, by providing subsidies for the development of strategies aimed at reducing the indicators.
publishDate 2022
dc.date.accessioned.fl_str_mv 2022-05-10T14:21:39Z
dc.date.issued.fl_str_mv 2022-02-24
dc.type.driver.fl_str_mv Documento sob sigilo. Prazo provável para disponibilização total: 24/02/2025. Motivo do sigilo: publicação de artigo
info:eu-repo/semantics/masterThesis
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format masterThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv ALVES, Jordana Maria Freitas. Dinâmica espacial da Covid-19 no Estado do Maranhão. 2022. 86 f. Dissertação (Programa de Pós-Graduação em Enfermagem/CCBS) - Universidade Federal do Maranhão, São Luís, 2022.
dc.identifier.uri.fl_str_mv https://tedebc.ufma.br/jspui/handle/tede/tede/3560
identifier_str_mv ALVES, Jordana Maria Freitas. Dinâmica espacial da Covid-19 no Estado do Maranhão. 2022. 86 f. Dissertação (Programa de Pós-Graduação em Enfermagem/CCBS) - Universidade Federal do Maranhão, São Luís, 2022.
url https://tedebc.ufma.br/jspui/handle/tede/tede/3560
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Maranhão
dc.publisher.program.fl_str_mv PROGRAMA DE PÓS-GRADUAÇÃO EM ENFERMAGEM/CCBS
dc.publisher.initials.fl_str_mv UFMA
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv DEPARTAMENTO DE ENFERMAGEM/CCBS
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