Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , , |
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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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 |
_version_ |
1754212953945538560 |