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dc.contributor.authorCosta, Jose Vilton
dc.contributor.authorArruda Silveira, Liciana Vaz de [UNESP]
dc.contributor.authorDonalisio, Maria Rita
dc.date.accessioned2018-11-26T15:31:17Z
dc.date.available2018-11-26T15:31:17Z
dc.date.issued2016-08-01
dc.identifierhttp://dx.doi.org/10.1590/0102-311X00036915
dc.identifier.citationCadernos De Saude Publica. Rio De Janiero: Cadernos Saude Publica, v. 32, n. 8, 14 p., 2016.
dc.identifier.issn0102-311X
dc.identifier.urihttp://hdl.handle.net/11449/159093
dc.description.abstractDengue 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.en
dc.format.extent14
dc.language.isopor
dc.publisherCadernos Saude Publica
dc.relation.ispartofCadernos De Saude Publica
dc.sourceWeb of Science
dc.subjectSpatial Analysis
dc.subjectDengue
dc.subjectCommunicable Disease Control
dc.titleSpatial analysis of counting data with excess zeros applied to the study of dengue incidence in Campinas, Sao Paulo State, Brazilen
dc.typeArtigo
dcterms.rightsHolderCadernos Saude Publica
dc.contributor.institutionUniv Fed Rio Grande do Norte
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.description.affiliationUniv Fed Rio Grande do Norte, Programa Posgrad Demog, Av Salgado Filho 3000,Campus Univ, BR-59078970 Natal, RN, Brazil
dc.description.affiliationUniv Estadual Paulista, Inst Biociencias, Botucatu, SP, Brazil
dc.description.affiliationUniv Estadual Campinas, Fac Ciencias Med, Campinas, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Inst Biociencias, Botucatu, SP, Brazil
dc.identifier.doi10.1590/0102-311X00036915
dc.identifier.scieloS0102-311X2016000804003
dc.identifier.wosWOS:000383895700008
dc.rights.accessRightsAcesso aberto
dc.identifier.fileS0102-311X2016000804003.pdf
unesp.author.orcid0000-0003-4457-9897[3]
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