Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil

Detalhes bibliográficos
Autor(a) principal: Werneck,Guilherme L.
Data de Publicação: 2002
Outros Autores: Maguire,James H.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cadernos de Saúde Pública
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2002000300007
Resumo: Most ecologic studies use geographical areas as units of observation. Because data from areas close to one another tend to be more alike than those from distant areas, estimation of effect size and confidence intervals should consider spatial autocorrelation of measurements. In this report we demonstrate a method for modeling spatial autocorrelation within a mixed model framework, using data on environmental and socioeconomic determinants of the incidence of visceral leishmaniasis (VL) in the city of Teresina, Piauí, Brazil. A model with a spherical covariance structure indicated significant spatial autocorrelation in the data and yielded a better fit than one assuming independent observations. While both models showed a positive association between VL incidence and residence in a favela (slum) or in areas with green vegetation, values for the fixed effects and standard errors differed substantially between the models. Exploration of the data's spatial correlation structure through the semivariogram should precede the use of these models. Our findings support the hypothesis of spatial dependence of VL rates and indicate that it might be useful to model spatial correlation in order to obtain more accurate point and standard error estimates.
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spelling Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, BrazilVisceral LeishmaniasisSpatial AnalysisEcologic StudiesEpidemiologyMost ecologic studies use geographical areas as units of observation. Because data from areas close to one another tend to be more alike than those from distant areas, estimation of effect size and confidence intervals should consider spatial autocorrelation of measurements. In this report we demonstrate a method for modeling spatial autocorrelation within a mixed model framework, using data on environmental and socioeconomic determinants of the incidence of visceral leishmaniasis (VL) in the city of Teresina, Piauí, Brazil. A model with a spherical covariance structure indicated significant spatial autocorrelation in the data and yielded a better fit than one assuming independent observations. While both models showed a positive association between VL incidence and residence in a favela (slum) or in areas with green vegetation, values for the fixed effects and standard errors differed substantially between the models. Exploration of the data's spatial correlation structure through the semivariogram should precede the use of these models. Our findings support the hypothesis of spatial dependence of VL rates and indicate that it might be useful to model spatial correlation in order to obtain more accurate point and standard error estimates.Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz2002-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2002000300007Cadernos de Saúde Pública v.18 n.3 2002reponame:Cadernos de Saúde Públicainstname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZ10.1590/S0102-311X2002000300007info:eu-repo/semantics/openAccessWerneck,Guilherme L.Maguire,James H.eng2015-11-24T00:00:00Zoai:scielo:S0102-311X2002000300007Revistahttp://cadernos.ensp.fiocruz.br/csp/https://old.scielo.br/oai/scielo-oai.phpcadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br1678-44640102-311Xopendoar:2015-11-24T00:00Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ)false
dc.title.none.fl_str_mv Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
title Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
spellingShingle Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
Werneck,Guilherme L.
Visceral Leishmaniasis
Spatial Analysis
Ecologic Studies
Epidemiology
title_short Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
title_full Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
title_fullStr Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
title_full_unstemmed Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
title_sort Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil
author Werneck,Guilherme L.
author_facet Werneck,Guilherme L.
Maguire,James H.
author_role author
author2 Maguire,James H.
author2_role author
dc.contributor.author.fl_str_mv Werneck,Guilherme L.
Maguire,James H.
dc.subject.por.fl_str_mv Visceral Leishmaniasis
Spatial Analysis
Ecologic Studies
Epidemiology
topic Visceral Leishmaniasis
Spatial Analysis
Ecologic Studies
Epidemiology
description Most ecologic studies use geographical areas as units of observation. Because data from areas close to one another tend to be more alike than those from distant areas, estimation of effect size and confidence intervals should consider spatial autocorrelation of measurements. In this report we demonstrate a method for modeling spatial autocorrelation within a mixed model framework, using data on environmental and socioeconomic determinants of the incidence of visceral leishmaniasis (VL) in the city of Teresina, Piauí, Brazil. A model with a spherical covariance structure indicated significant spatial autocorrelation in the data and yielded a better fit than one assuming independent observations. While both models showed a positive association between VL incidence and residence in a favela (slum) or in areas with green vegetation, values for the fixed effects and standard errors differed substantially between the models. Exploration of the data's spatial correlation structure through the semivariogram should precede the use of these models. Our findings support the hypothesis of spatial dependence of VL rates and indicate that it might be useful to model spatial correlation in order to obtain more accurate point and standard error estimates.
publishDate 2002
dc.date.none.fl_str_mv 2002-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2002000300007
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0102-311X2002000300007
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz
publisher.none.fl_str_mv Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz
dc.source.none.fl_str_mv Cadernos de Saúde Pública v.18 n.3 2002
reponame:Cadernos de Saúde Pública
instname:Fundação Oswaldo Cruz (FIOCRUZ)
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instname_str Fundação Oswaldo Cruz (FIOCRUZ)
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reponame_str Cadernos de Saúde Pública
collection Cadernos de Saúde Pública
repository.name.fl_str_mv Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ)
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