ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: COSTA, Silmery da Silva Brito lattes
Orientador(a): BRANCO, Maria dos Remédios Freitas Carvalho lattes
Banca de defesa: BRANCO, Maria dos Remédios Freitas Carvalho lattes, SANTOS, Alcione Miranda dos lattes, MEDEIROS, Maria Nilza Lima lattes, GONÇALVES, Eloisa da Graça do Rosário lattes, CALDAS, Arlene de Jesus Mendes lattes
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal do Maranhão
Programa de Pós-Graduação: PROGRAMA DE PÓS-GRADUAÇÃO EM SAÚDE COLETIVA/CCBS
Departamento: DEPARTAMENTO DE PATOLOGIA/CCBS
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://tedebc.ufma.br/jspui/handle/tede/tede/2946
Resumo: Dengue, chikungunya and zika are extremely relevant arboviruses for world public health, given the damage they cause to the population and economic and social impacts in the affected countries. This ecological study used spatial analysis of probable cases of dengue, chikungunya and zika reported in the Notified Disease Information System (SINAN) in the State of Maranhão, Brazil, from 2015 to 2016. In the first article, the distribution of probable cases of dengue, chikungunya and zika in Maranhão was spatially analyzed, relating it to sociodemographic and economic factors, Unified Health System Performance Index (IDSUS) and vector infestation. The unit of analysis was the municipalities. Geodaversion 1.10 software was used to calculate Moran Global and Local indexes. In the univariate analysis, the Moran Global Index identified a significant autocorrelation of dengue (I = 0.10; p = 0.009) and Zika (I = 0.07; p = 0.03) incidence rates. In the bivariate analysis, there was a positive spatial correlation between dengue and population density (I = 0.31; p <0.001) and a negative correlation with IDSUS for primary care coverage (I = -0.08; p = 0.01). Regarding chikungunya, there were positive spatial correlations with population density (I = 0.06; p = 0.03) and the Municipal Human Development Index (MHDI) (I = 0.10; p = 0.002) and negative correlation with Gini index (I = -0.01; p <0.001) and IDSUS for primary care coverage (I = - 0.18; p <0.001). Finally, positive spatial correlations were identified between zika and population density (I = 0.13; p = 0.005) and MHDI (I = 0.12; p <0.001), as well as negative correlation with Gini index. (I = -0.11; p <0.001) and IDSUS by primary care coverage (I = - 0.05; p = 0.03). In the second article, we analyzed the spatial distribution of the cases of the three georeferenced diseases in the municipality of São Luís, Maranhão, from 2015 to 2016, relating it to socioenvironmental factors, economic and strategic points. The unit of analysis was the census sector. Arcgis version 10.4.1 software was used for georeferencing of disease cases, QGIS version 3.6.0 to aggregate cases by census sector, GeoDa 1.10 for the Global and Local Moran Index and spatial models, and for the classical model, the Stata software. ® 14.0. From the Moran Global Index, significant spatial autocorrelation of the incidence of the three arboviruses was identified (I = 0.55; p = 0.001). The model with the best performance was the SpatialLag, with the highest likelihood log value, the explanatory power (R2 = 0.508) and the Akaike information criterion (2059.28) and the Bayesian Schwarz criterion (2099; 46). In this model only the percentage variable of accumulated garbage in the surroundings remained with a statistically significant positive correlation (p = 0.03). The findings suggest that sociodemographic factors influenced the occurrence of dengue, chikungunya and zika in the state of Maranhão. In São Luís the improper disposal of solid waste had an impact on the occurrence of the three arboviruses.
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spelling BRANCO, Maria dos Remédios Freitas Carvalho255.487.513-87http://lattes.cnpq.br/5449951869928014SANTOS, Alcione Miranda dos641.261.104-53http://lattes.cnpq.br/2709550775435326BRANCO, Maria dos Remédios Freitas Carvalho255.487.513-87http://lattes.cnpq.br/5449951869928014SANTOS, Alcione Miranda dos641.261.104-53http://lattes.cnpq.br/2709550775435326MEDEIROS, Maria Nilza Limahttp://lattes.cnpq.br/2755510184384522GONÇALVES, Eloisa da Graça do Rosáriohttp://lattes.cnpq.br/2449592677614097CALDAS, Arlene de Jesus Mendeshttp://lattes.cnpq.br/7214761052240294006.802.803-65http://lattes.cnpq.br/0542819211562518COSTA, Silmery da Silva Brito2019-12-18T18:25:45Z2019-11-01COSTA, Silmery da Silva Brito. Análise espacial de casos prováveis de Dengue, Chikungunya e Zika no Maranhão, Brasil.. 2019. 119 f. Tese(Programa de Pós-Graduação em Saúde Coletiva/CCBS) - Universidade Federal do Maranhão, São Luis,2019.https://tedebc.ufma.br/jspui/handle/tede/tede/2946Dengue, chikungunya and zika are extremely relevant arboviruses for world public health, given the damage they cause to the population and economic and social impacts in the affected countries. This ecological study used spatial analysis of probable cases of dengue, chikungunya and zika reported in the Notified Disease Information System (SINAN) in the State of Maranhão, Brazil, from 2015 to 2016. In the first article, the distribution of probable cases of dengue, chikungunya and zika in Maranhão was spatially analyzed, relating it to sociodemographic and economic factors, Unified Health System Performance Index (IDSUS) and vector infestation. The unit of analysis was the municipalities. Geodaversion 1.10 software was used to calculate Moran Global and Local indexes. In the univariate analysis, the Moran Global Index identified a significant autocorrelation of dengue (I = 0.10; p = 0.009) and Zika (I = 0.07; p = 0.03) incidence rates. In the bivariate analysis, there was a positive spatial correlation between dengue and population density (I = 0.31; p <0.001) and a negative correlation with IDSUS for primary care coverage (I = -0.08; p = 0.01). Regarding chikungunya, there were positive spatial correlations with population density (I = 0.06; p = 0.03) and the Municipal Human Development Index (MHDI) (I = 0.10; p = 0.002) and negative correlation with Gini index (I = -0.01; p <0.001) and IDSUS for primary care coverage (I = - 0.18; p <0.001). Finally, positive spatial correlations were identified between zika and population density (I = 0.13; p = 0.005) and MHDI (I = 0.12; p <0.001), as well as negative correlation with Gini index. (I = -0.11; p <0.001) and IDSUS by primary care coverage (I = - 0.05; p = 0.03). In the second article, we analyzed the spatial distribution of the cases of the three georeferenced diseases in the municipality of São Luís, Maranhão, from 2015 to 2016, relating it to socioenvironmental factors, economic and strategic points. The unit of analysis was the census sector. Arcgis version 10.4.1 software was used for georeferencing of disease cases, QGIS version 3.6.0 to aggregate cases by census sector, GeoDa 1.10 for the Global and Local Moran Index and spatial models, and for the classical model, the Stata software. ® 14.0. From the Moran Global Index, significant spatial autocorrelation of the incidence of the three arboviruses was identified (I = 0.55; p = 0.001). The model with the best performance was the SpatialLag, with the highest likelihood log value, the explanatory power (R2 = 0.508) and the Akaike information criterion (2059.28) and the Bayesian Schwarz criterion (2099; 46). In this model only the percentage variable of accumulated garbage in the surroundings remained with a statistically significant positive correlation (p = 0.03). The findings suggest that sociodemographic factors influenced the occurrence of dengue, chikungunya and zika in the state of Maranhão. In São Luís the improper disposal of solid waste had an impact on the occurrence of the three arboviruses.Dengue, chikungunya e zika são arboviroses de extrema relevância para a saúde pública mundial, tendo em vista os danos que causam para a população e impactos econômicos e sociais nos países atingidos. Este estudo ecológico utilizou análise espacial de casos prováveis de dengue, chikungunya e zika notificados no Sistema de Informação de Agravos de Notificação (SINAN) no Estado do Maranhão, Brasil, no período de 2015 a 2016. No primeiro artigo, analisou-se espacialmente a distribuição dos casos prováveis de dengue, chikungunya e zika no Maranhão, relacionando-a com fatores sociodemográficos, econômicos, Índice de Desempenho do Sistema Único de Saúde (IDSUS) e infestação vetorial. Considerou-se como unidade de análise os municípios. Utilizou-se o software Geoda versão 1.10 para cálculo dos índices de Moran Global e Local. Na análise univariada o índice de Moran Global identificou uma autocorrelação significativa das taxas de incidência de dengue (I=0,10; p=0,009) e zika (I=0,07; p=0,03). Na análise bivariada houve correlação espacial positiva entre dengue e densidade populacional (I=0,31; p<0,001) e correlação negativa com o IDSUS pela cobertura de atenção básica (I=-0,08; p=0,01). Em relação a chikungunya, houve correlações espaciais positivas com densidade populacional (I=0,06; p=0,03) e o Índice de Desenvolvimento Humano Municipal (IDHM) (I=0,10; p=0,002) e correlação negativa com o índice de Gini (I=-0,01; p<0,001) e o IDSUS pela cobertura de atenção básica (I=-0,18; p<0,001). Por fim, identificou-se correlações espaciais positivas entre zika e a densidade populacional (I=0,13; p=0,005) e o IDHM (I=0,12; p<0,001), assim como correlação negativa com o índice de Gini (I=-0,11; p<0,001) e o IDSUS por cobertura de atenção básica (I=-0,05; p=0,03). No segundo artigo, analisou-se a distribuição espacial dos casos das três doenças georreferenciados no município de São Luís, Maranhão, no período de 2015 a 2016, relacionando-a com fatores socioambientais, econômicos e com pontos estratégicos. A unidade de análise foi o setor censitário. Utilizou-se os softwares Arcgis versão 10.4.1 para georreferenciamento dos casos das doenças, QGIS versão 3.6.0 para agregar os casos por setor censitário, GeoDa 1.10 para o índice de Moran Global e Local e os modelos espaciais e para o modelo clássico o software Stata® 14.0. A partir do índice de Moran Global, identificou-se autocorrelação espacial significativa da incidência das três arboviroses (I=0,55; p=0,001). O modelo que apresentou melhor desempenho foi o Spatial Lag, com maior valor do Log da Verossimilhança, ampliação do poder explicativo (R2=0,508) e redução dos valores do critério de informação de Akaike (2059,28) e do critério bayesiano Schwarz (2099,46). Nesse modelo apenas a variável percentual de lixo acumulado no entorno permaneceu com correlação positiva estatisticamente significativa (p=0,03). Os achados sugerem que fatores sociodemográficos influenciaram na ocorrência de dengue, chikungunya e zika no estado do Maranhão. Em São Luís o descarte inadequado dos resíduos sólidos teve impacto na ocorrência das três arboviroses.Submitted by Maria Aparecida (cidazen@gmail.com) on 2019-12-18T18:25:45Z No. of bitstreams: 1 Silmery da Silva B.C..pdf: 9076342 bytes, checksum: aea358f49eb73c7cd40bc9e72e4d6c7b (MD5)Made available in DSpace on 2019-12-18T18:25:45Z (GMT). No. of bitstreams: 1 Silmery da Silva B.C..pdf: 9076342 bytes, checksum: aea358f49eb73c7cd40bc9e72e4d6c7b (MD5) Previous issue date: 2019-11-01CNPqFAPEMACAPESapplication/pdfporUniversidade Federal do MaranhãoPROGRAMA DE PÓS-GRADUAÇÃO EM SAÚDE COLETIVA/CCBSUFMABrasilDEPARTAMENTO DE PATOLOGIA/CCBSDengue;Chikungunya;Zika;Análise Espacial;Fatores socioeconômicos;Fatores sociodemográficosDengue;Chikungunya;Zika;Spatial analysis;Socioeconomic factors;Sociodemographic FactorsDoenças Infecciosas e ParasitáriasANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.SPACE ANALYSIS OF PROBABLE CASES OF DENGUE, CHIKUNGUNYA AND ZIKA IN MARANHÃO, BRAZIL.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFMAinstname:Universidade Federal do Maranhão (UFMA)instacron:UFMAORIGINALSilmery da Silva B.C..pdfSilmery da Silva B.C..pdfapplication/pdf9076342http://tedebc.ufma.br:8080/bitstream/tede/2946/2/Silmery+da+Silva+B.C..pdfaea358f49eb73c7cd40bc9e72e4d6c7bMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82255http://tedebc.ufma.br:8080/bitstream/tede/2946/1/license.txt97eeade1fce43278e63fe063657f8083MD51tede/29462019-12-18 15:25:45.614oai: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:21312019-12-18T18:25:45Biblioteca Digital de Teses e Dissertações da UFMA - Universidade Federal do Maranhão (UFMA)false
dc.title.por.fl_str_mv ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
dc.title.alternative.eng.fl_str_mv SPACE ANALYSIS OF PROBABLE CASES OF DENGUE, CHIKUNGUNYA AND ZIKA IN MARANHÃO, BRAZIL.
title ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
spellingShingle ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
COSTA, Silmery da Silva Brito
Dengue;
Chikungunya;
Zika;
Análise Espacial;
Fatores socioeconômicos;
Fatores sociodemográficos
Dengue;
Chikungunya;
Zika;
Spatial analysis;
Socioeconomic factors;
Sociodemographic Factors
Doenças Infecciosas e Parasitárias
title_short ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
title_full ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
title_fullStr ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
title_full_unstemmed ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
title_sort ANÁLISE ESPACIAL DE CASOS PROVÁVEIS DE DENGUE, CHIKUNGUNYA E ZIKA NO MARANHÃO, BRASIL.
author COSTA, Silmery da Silva Brito
author_facet COSTA, Silmery da Silva Brito
author_role author
dc.contributor.advisor1.fl_str_mv BRANCO, Maria dos Remédios Freitas Carvalho
dc.contributor.advisor1ID.fl_str_mv 255.487.513-87
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/5449951869928014
dc.contributor.advisor-co1.fl_str_mv SANTOS, Alcione Miranda dos
dc.contributor.advisor-co1ID.fl_str_mv 641.261.104-53
dc.contributor.advisor-co1Lattes.fl_str_mv http://lattes.cnpq.br/2709550775435326
dc.contributor.referee1.fl_str_mv BRANCO, Maria dos Remédios Freitas Carvalho
dc.contributor.referee1ID.fl_str_mv 255.487.513-87
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/5449951869928014
dc.contributor.referee2.fl_str_mv SANTOS, Alcione Miranda dos
dc.contributor.referee2ID.fl_str_mv 641.261.104-53
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/2709550775435326
dc.contributor.referee3.fl_str_mv MEDEIROS, Maria Nilza Lima
dc.contributor.referee3Lattes.fl_str_mv http://lattes.cnpq.br/2755510184384522
dc.contributor.referee4.fl_str_mv GONÇALVES, Eloisa da Graça do Rosário
dc.contributor.referee4Lattes.fl_str_mv http://lattes.cnpq.br/2449592677614097
dc.contributor.referee5.fl_str_mv CALDAS, Arlene de Jesus Mendes
dc.contributor.referee5Lattes.fl_str_mv http://lattes.cnpq.br/7214761052240294
dc.contributor.authorID.fl_str_mv 006.802.803-65
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/0542819211562518
dc.contributor.author.fl_str_mv COSTA, Silmery da Silva Brito
contributor_str_mv BRANCO, Maria dos Remédios Freitas Carvalho
SANTOS, Alcione Miranda dos
BRANCO, Maria dos Remédios Freitas Carvalho
SANTOS, Alcione Miranda dos
MEDEIROS, Maria Nilza Lima
GONÇALVES, Eloisa da Graça do Rosário
CALDAS, Arlene de Jesus Mendes
dc.subject.por.fl_str_mv Dengue;
Chikungunya;
Zika;
Análise Espacial;
Fatores socioeconômicos;
Fatores sociodemográficos
topic Dengue;
Chikungunya;
Zika;
Análise Espacial;
Fatores socioeconômicos;
Fatores sociodemográficos
Dengue;
Chikungunya;
Zika;
Spatial analysis;
Socioeconomic factors;
Sociodemographic Factors
Doenças Infecciosas e Parasitárias
dc.subject.eng.fl_str_mv Dengue;
Chikungunya;
Zika;
Spatial analysis;
Socioeconomic factors;
Sociodemographic Factors
dc.subject.cnpq.fl_str_mv Doenças Infecciosas e Parasitárias
description Dengue, chikungunya and zika are extremely relevant arboviruses for world public health, given the damage they cause to the population and economic and social impacts in the affected countries. This ecological study used spatial analysis of probable cases of dengue, chikungunya and zika reported in the Notified Disease Information System (SINAN) in the State of Maranhão, Brazil, from 2015 to 2016. In the first article, the distribution of probable cases of dengue, chikungunya and zika in Maranhão was spatially analyzed, relating it to sociodemographic and economic factors, Unified Health System Performance Index (IDSUS) and vector infestation. The unit of analysis was the municipalities. Geodaversion 1.10 software was used to calculate Moran Global and Local indexes. In the univariate analysis, the Moran Global Index identified a significant autocorrelation of dengue (I = 0.10; p = 0.009) and Zika (I = 0.07; p = 0.03) incidence rates. In the bivariate analysis, there was a positive spatial correlation between dengue and population density (I = 0.31; p <0.001) and a negative correlation with IDSUS for primary care coverage (I = -0.08; p = 0.01). Regarding chikungunya, there were positive spatial correlations with population density (I = 0.06; p = 0.03) and the Municipal Human Development Index (MHDI) (I = 0.10; p = 0.002) and negative correlation with Gini index (I = -0.01; p <0.001) and IDSUS for primary care coverage (I = - 0.18; p <0.001). Finally, positive spatial correlations were identified between zika and population density (I = 0.13; p = 0.005) and MHDI (I = 0.12; p <0.001), as well as negative correlation with Gini index. (I = -0.11; p <0.001) and IDSUS by primary care coverage (I = - 0.05; p = 0.03). In the second article, we analyzed the spatial distribution of the cases of the three georeferenced diseases in the municipality of São Luís, Maranhão, from 2015 to 2016, relating it to socioenvironmental factors, economic and strategic points. The unit of analysis was the census sector. Arcgis version 10.4.1 software was used for georeferencing of disease cases, QGIS version 3.6.0 to aggregate cases by census sector, GeoDa 1.10 for the Global and Local Moran Index and spatial models, and for the classical model, the Stata software. ® 14.0. From the Moran Global Index, significant spatial autocorrelation of the incidence of the three arboviruses was identified (I = 0.55; p = 0.001). The model with the best performance was the SpatialLag, with the highest likelihood log value, the explanatory power (R2 = 0.508) and the Akaike information criterion (2059.28) and the Bayesian Schwarz criterion (2099; 46). In this model only the percentage variable of accumulated garbage in the surroundings remained with a statistically significant positive correlation (p = 0.03). The findings suggest that sociodemographic factors influenced the occurrence of dengue, chikungunya and zika in the state of Maranhão. In São Luís the improper disposal of solid waste had an impact on the occurrence of the three arboviruses.
publishDate 2019
dc.date.accessioned.fl_str_mv 2019-12-18T18:25:45Z
dc.date.issued.fl_str_mv 2019-11-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv COSTA, Silmery da Silva Brito. Análise espacial de casos prováveis de Dengue, Chikungunya e Zika no Maranhão, Brasil.. 2019. 119 f. Tese(Programa de Pós-Graduação em Saúde Coletiva/CCBS) - Universidade Federal do Maranhão, São Luis,2019.
dc.identifier.uri.fl_str_mv https://tedebc.ufma.br/jspui/handle/tede/tede/2946
identifier_str_mv COSTA, Silmery da Silva Brito. Análise espacial de casos prováveis de Dengue, Chikungunya e Zika no Maranhão, Brasil.. 2019. 119 f. Tese(Programa de Pós-Graduação em Saúde Coletiva/CCBS) - Universidade Federal do Maranhão, São Luis,2019.
url https://tedebc.ufma.br/jspui/handle/tede/tede/2946
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 SAÚDE COLETIVA/CCBS
dc.publisher.initials.fl_str_mv UFMA
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv DEPARTAMENTO DE PATOLOGIA/CCBS
publisher.none.fl_str_mv Universidade Federal do Maranhão
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da UFMA
instname:Universidade Federal do Maranhão (UFMA)
instacron:UFMA
instname_str Universidade Federal do Maranhão (UFMA)
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reponame_str Biblioteca Digital de Teses e Dissertações da UFMA
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bitstream.url.fl_str_mv http://tedebc.ufma.br:8080/bitstream/tede/2946/2/Silmery+da+Silva+B.C..pdf
http://tedebc.ufma.br:8080/bitstream/tede/2946/1/license.txt
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