Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/0102-311X00036915 http://hdl.handle.net/11449/159093 |
Resumo: | Dengue incidence occurs predominantly within city limits. Identifying spatial distribution of the disease at the local level helps formulate strategies to control and prevent the disease. Spatial analysis of counting data for small areas commonly violates the assumptions of traditional Poisson models due to the excessive amount of zeros. This study compared the performance of four counting models used in mapping diseases: Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial. The methods were compared in a simulation study. The models analyzed in the simulation were applied to a spatial ecological study of dengue data aggregated by census tracts in the city of Campinas, Sao Paulo State, Brazil, 2007. Spatial analysis was conducted with Bayesian hierarchical models. The zero-inflated Poisson model showed the best performance for estimating relative risk of dengue incidence in the census tracts. |
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Repositório Institucional da UNESP |
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Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, BrazilSpatial AnalysisDengueCommunicable Disease ControlDengue incidence occurs predominantly within city limits. Identifying spatial distribution of the disease at the local level helps formulate strategies to control and prevent the disease. Spatial analysis of counting data for small areas commonly violates the assumptions of traditional Poisson models due to the excessive amount of zeros. This study compared the performance of four counting models used in mapping diseases: Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial. The methods were compared in a simulation study. The models analyzed in the simulation were applied to a spatial ecological study of dengue data aggregated by census tracts in the city of Campinas, Sao Paulo State, Brazil, 2007. Spatial analysis was conducted with Bayesian hierarchical models. The zero-inflated Poisson model showed the best performance for estimating relative risk of dengue incidence in the census tracts.Univ Fed Rio Grande do Norte, Programa Posgrad Demog, Av Salgado Filho 3000,Campus Univ, BR-59078970 Natal, RN, BrazilUniv Estadual Paulista, Inst Biociencias, Botucatu, SP, BrazilUniv Estadual Campinas, Fac Ciencias Med, Campinas, SP, BrazilUniv Estadual Paulista, Inst Biociencias, Botucatu, SP, BrazilCadernos Saude PublicaUniv Fed Rio Grande do NorteUniversidade Estadual Paulista (Unesp)Universidade Estadual de Campinas (UNICAMP)Costa, Jose ViltonArruda Silveira, Liciana Vaz de [UNESP]Donalisio, Maria Rita2018-11-26T15:31:17Z2018-11-26T15:31:17Z2016-08-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article14application/pdfhttp://dx.doi.org/10.1590/0102-311X00036915Cadernos De Saude Publica. Rio De Janiero: Cadernos Saude Publica, v. 32, n. 8, 14 p., 2016.0102-311Xhttp://hdl.handle.net/11449/15909310.1590/0102-311X00036915S0102-311X2016000804003WOS:000383895700008S0102-311X2016000804003.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporCadernos De Saude Publicainfo:eu-repo/semantics/openAccess2023-11-02T06:05:46Zoai:repositorio.unesp.br:11449/159093Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:40:09.303838Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil |
title |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil |
spellingShingle |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil Costa, Jose Vilton Spatial Analysis Dengue Communicable Disease Control |
title_short |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil |
title_full |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil |
title_fullStr |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil |
title_full_unstemmed |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil |
title_sort |
Spatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazil |
author |
Costa, Jose Vilton |
author_facet |
Costa, Jose Vilton Arruda Silveira, Liciana Vaz de [UNESP] Donalisio, Maria Rita |
author_role |
author |
author2 |
Arruda Silveira, Liciana Vaz de [UNESP] Donalisio, Maria Rita |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Univ Fed Rio Grande do Norte Universidade Estadual Paulista (Unesp) Universidade Estadual de Campinas (UNICAMP) |
dc.contributor.author.fl_str_mv |
Costa, Jose Vilton Arruda Silveira, Liciana Vaz de [UNESP] Donalisio, Maria Rita |
dc.subject.por.fl_str_mv |
Spatial Analysis Dengue Communicable Disease Control |
topic |
Spatial Analysis Dengue Communicable Disease Control |
description |
Dengue incidence occurs predominantly within city limits. Identifying spatial distribution of the disease at the local level helps formulate strategies to control and prevent the disease. Spatial analysis of counting data for small areas commonly violates the assumptions of traditional Poisson models due to the excessive amount of zeros. This study compared the performance of four counting models used in mapping diseases: Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial. The methods were compared in a simulation study. The models analyzed in the simulation were applied to a spatial ecological study of dengue data aggregated by census tracts in the city of Campinas, Sao Paulo State, Brazil, 2007. Spatial analysis was conducted with Bayesian hierarchical models. The zero-inflated Poisson model showed the best performance for estimating relative risk of dengue incidence in the census tracts. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-08-01 2018-11-26T15:31:17Z 2018-11-26T15:31:17Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1590/0102-311X00036915 Cadernos De Saude Publica. Rio De Janiero: Cadernos Saude Publica, v. 32, n. 8, 14 p., 2016. 0102-311X http://hdl.handle.net/11449/159093 10.1590/0102-311X00036915 S0102-311X2016000804003 WOS:000383895700008 S0102-311X2016000804003.pdf |
url |
http://dx.doi.org/10.1590/0102-311X00036915 http://hdl.handle.net/11449/159093 |
identifier_str_mv |
Cadernos De Saude Publica. Rio De Janiero: Cadernos Saude Publica, v. 32, n. 8, 14 p., 2016. 0102-311X 10.1590/0102-311X00036915 S0102-311X2016000804003 WOS:000383895700008 S0102-311X2016000804003.pdf |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
Cadernos De Saude Publica |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
14 application/pdf |
dc.publisher.none.fl_str_mv |
Cadernos Saude Publica |
publisher.none.fl_str_mv |
Cadernos Saude Publica |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128685457276928 |