Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model

Detalhes bibliográficos
Autor(a) principal: Honorato,Taizi
Data de Publicação: 2014
Outros Autores: Lapa,Priscila Pagung de Aquino, Sales,Carolina Maia Martins, Reis-Santos,Barbara, Tristão-Sá,Ricardo, Bertolde,Adelmo Inácio, Maciel,Ethel Leonor Noia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista brasileira de epidemiologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2014000600150
Resumo: OBJECTIVE: To study the relationship between the risk of dengue and sociodemographic variables through the use of spatial regression models fully Bayesian in the municipalities of Espírito Santo in 2010. METHOD: This is an ecological study and exploration that used spatial analysis tools in preparing thematic maps with data obtained from SinanNet. An analysis by area, taking as unit the municipalities of the state, was performed. Thematic maps were constructed by the computer program R 2.15.00 and Deviance Information Criterion (DIC), calculated in WinBugs, Absolut and Normalized Mean Error (NMAE) were the criteria used to compare the models. RESULTS: We were able to geocode 21,933 dengue cases (rate of 623.99 cases per 100 thousand habitants) with a higher incidence in the municipalities of Vitória, Serra and Colatina; model with spatial effect with the covariates trash and income showed the best performance at DIC and Nmae criteria. CONCLUSION: It was possible to identify the relationship of dengue with factors outside the health sector and to identify areas with higher risk of disease.
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spelling Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian modelEpidemiology and BiostatisticsDengueLinear modelsSocial determinants of healthSpatial analysisBayesian Inference OBJECTIVE: To study the relationship between the risk of dengue and sociodemographic variables through the use of spatial regression models fully Bayesian in the municipalities of Espírito Santo in 2010. METHOD: This is an ecological study and exploration that used spatial analysis tools in preparing thematic maps with data obtained from SinanNet. An analysis by area, taking as unit the municipalities of the state, was performed. Thematic maps were constructed by the computer program R 2.15.00 and Deviance Information Criterion (DIC), calculated in WinBugs, Absolut and Normalized Mean Error (NMAE) were the criteria used to compare the models. RESULTS: We were able to geocode 21,933 dengue cases (rate of 623.99 cases per 100 thousand habitants) with a higher incidence in the municipalities of Vitória, Serra and Colatina; model with spatial effect with the covariates trash and income showed the best performance at DIC and Nmae criteria. CONCLUSION: It was possible to identify the relationship of dengue with factors outside the health sector and to identify areas with higher risk of disease. Associação Brasileira de Saúde Coletiva2014-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2014000600150Revista Brasileira de Epidemiologia v.17 suppl.2 2014reponame:Revista brasileira de epidemiologia (Online)instname:Associação Brasileira de Saúde Coletiva (ABRASCO)instacron:ABRASCO10.1590/1809-4503201400060013info:eu-repo/semantics/openAccessHonorato,TaiziLapa,Priscila Pagung de AquinoSales,Carolina Maia MartinsReis-Santos,BarbaraTristão-Sá,RicardoBertolde,Adelmo InácioMaciel,Ethel Leonor Noiaeng2014-11-10T00:00:00Zoai:scielo:S1415-790X2014000600150Revistahttp://www.scielo.br/rbepidhttps://old.scielo.br/oai/scielo-oai.php||revbrepi@usp.br1980-54971415-790Xopendoar:2014-11-10T00:00Revista brasileira de epidemiologia (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO)false
dc.title.none.fl_str_mv Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
title Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
spellingShingle Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
Honorato,Taizi
Epidemiology and Biostatistics
Dengue
Linear models
Social determinants of health
Spatial analysis
Bayesian Inference
title_short Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
title_full Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
title_fullStr Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
title_full_unstemmed Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
title_sort Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
author Honorato,Taizi
author_facet Honorato,Taizi
Lapa,Priscila Pagung de Aquino
Sales,Carolina Maia Martins
Reis-Santos,Barbara
Tristão-Sá,Ricardo
Bertolde,Adelmo Inácio
Maciel,Ethel Leonor Noia
author_role author
author2 Lapa,Priscila Pagung de Aquino
Sales,Carolina Maia Martins
Reis-Santos,Barbara
Tristão-Sá,Ricardo
Bertolde,Adelmo Inácio
Maciel,Ethel Leonor Noia
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Honorato,Taizi
Lapa,Priscila Pagung de Aquino
Sales,Carolina Maia Martins
Reis-Santos,Barbara
Tristão-Sá,Ricardo
Bertolde,Adelmo Inácio
Maciel,Ethel Leonor Noia
dc.subject.por.fl_str_mv Epidemiology and Biostatistics
Dengue
Linear models
Social determinants of health
Spatial analysis
Bayesian Inference
topic Epidemiology and Biostatistics
Dengue
Linear models
Social determinants of health
Spatial analysis
Bayesian Inference
description OBJECTIVE: To study the relationship between the risk of dengue and sociodemographic variables through the use of spatial regression models fully Bayesian in the municipalities of Espírito Santo in 2010. METHOD: This is an ecological study and exploration that used spatial analysis tools in preparing thematic maps with data obtained from SinanNet. An analysis by area, taking as unit the municipalities of the state, was performed. Thematic maps were constructed by the computer program R 2.15.00 and Deviance Information Criterion (DIC), calculated in WinBugs, Absolut and Normalized Mean Error (NMAE) were the criteria used to compare the models. RESULTS: We were able to geocode 21,933 dengue cases (rate of 623.99 cases per 100 thousand habitants) with a higher incidence in the municipalities of Vitória, Serra and Colatina; model with spatial effect with the covariates trash and income showed the best performance at DIC and Nmae criteria. CONCLUSION: It was possible to identify the relationship of dengue with factors outside the health sector and to identify areas with higher risk of disease.
publishDate 2014
dc.date.none.fl_str_mv 2014-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2014000600150
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-790X2014000600150
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1809-4503201400060013
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Saúde Coletiva
publisher.none.fl_str_mv Associação Brasileira de Saúde Coletiva
dc.source.none.fl_str_mv Revista Brasileira de Epidemiologia v.17 suppl.2 2014
reponame:Revista brasileira de epidemiologia (Online)
instname:Associação Brasileira de Saúde Coletiva (ABRASCO)
instacron:ABRASCO
instname_str Associação Brasileira de Saúde Coletiva (ABRASCO)
instacron_str ABRASCO
institution ABRASCO
reponame_str Revista brasileira de epidemiologia (Online)
collection Revista brasileira de epidemiologia (Online)
repository.name.fl_str_mv Revista brasileira de epidemiologia (Online) - Associação Brasileira de Saúde Coletiva (ABRASCO)
repository.mail.fl_str_mv ||revbrepi@usp.br
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