Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression

Detalhes bibliográficos
Autor(a) principal: Fonseca, Fernanda Rodrigues
Data de Publicação: 2014
Outros Autores: Freitas, Corina da Costa, Dutra, Luciano Vieira, Guimarães, Ricardo José de Paula Souza e, Carvalho, Omar dos Santos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da FIOCRUZ (ARCA)
DOI: 10.1016/j.actatropica.2014.01.015
Texto Completo: https://www.arca.fiocruz.br/handle/icict/11008
Resumo: CNPq, CAPES, FAPESP and FAPEMIG
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spelling Fonseca, Fernanda RodriguesFreitas, Corina da CostaDutra, Luciano VieiraGuimarães, Ricardo José de Paula Souza eCarvalho, Omar dos Santos2015-06-30T12:56:15Z2015-06-30T12:56:15Z2014FONSECA, Fernanda Rodrigues et al. Spatial modeling of the schistosomiasis mansoni in Minas GeraisState, Brazil using spatial regression. Acta Tropica, v. 133, p. 56-63, May 2014.0001-706Xhttps://www.arca.fiocruz.br/handle/icict/1100810.1016/j.actatropica.2014.01.015CNPq, CAPES, FAPESP and FAPEMIGInstituto Nacional de Pesquisas Espaciais. São José dos Campos, SP, Brazil / Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Manaus, AM, Brazil.Instituto Nacional de Pesquisas Espaciais. São José dos Campos, SP, Brazil.Instituto Nacional de Pesquisas Espaciais. São José dos Campos, SP, Brazil.Instituto Nacional de Pesquisas Espaciais. São José dos Campos, SP, Brazil / Instituto Evandro Chagas. Ananindeua, PA, Brazil.Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Laboratório de Esquistossomose. Belo Horizonte, MG, Brazil.Schistosomiasis is a transmissible parasitic disease caused by the etiologic agent Schistosoma mansoni, whose intermediate hosts are snails of the genus Biomphalaria. The main goal of this paper is to estimate the prevalence of schistosomiasis in Minas Gerais State in Brazil using spatial disease information derived from the state transportation network of roads and rivers. The spatial information was incorporated in two ways: by introducing new variables that carry spatial neighborhood information and by using spatial regression models. Climate, socioeconomic and environmental variables were also used as co-variables to build models and use them to estimate a risk map for the whole state of Minas Gerais. The results show that the models constructed from the spatial regression produced a better fit, providing smaller root mean square error (RMSE) values. When no spatial information was used, the RMSE for the whole state of Minas Gerais reached 9.5%; with spatial regression, the RMSE reaches 8.8% (when the new variables are added to the model) and 8.5% (with the use of spatial regression). Variables representing vegetation, temperature, precipitation, topography, sanitation and human development indexes were important in explaining the spread of disease and identified certain conditions that are favorable for disease development. The use of spatial regression for the network of roads and rivers produced meaningful results for health management procedures and directing activities, enabling better detection of disease risk areas.engElsevierSpatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regressioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleSpatial relationsGeneralized proximity matricesSpatial analysisRegression analysisSchistosomiasis mansoniainfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-82354https://www.arca.fiocruz.br/bitstream/icict/11008/1/license.txt8b4c200b4e10021c5683c6ccaba07169MD51ORIGINAL2014_020.pdf2014_020.pdfapplication/pdf1844988https://www.arca.fiocruz.br/bitstream/icict/11008/2/2014_020.pdfb6ab84482a0caec87ab398eb245ccc2cMD52TEXT2014_020.pdf.txt2014_020.pdf.txtExtracted texttext/plain44504https://www.arca.fiocruz.br/bitstream/icict/11008/3/2014_020.pdf.txte0cbd16f70d0a267ae2290e6202da1d5MD53icict/110082023-08-15 21:23:55.384oai:www.arca.fiocruz.br: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Repositório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352023-08-16T00:23:55Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)false
dc.title.pt_BR.fl_str_mv Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
title Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
spellingShingle Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
Fonseca, Fernanda Rodrigues
Spatial relations
Generalized proximity matrices
Spatial analysis
Regression analysis
Schistosomiasis mansonia
title_short Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
title_full Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
title_fullStr Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
title_full_unstemmed Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
title_sort Spatial modeling of the schistosomiasis mansoni in Minas Gerais State, Brazil using spatial regression
author Fonseca, Fernanda Rodrigues
author_facet Fonseca, Fernanda Rodrigues
Freitas, Corina da Costa
Dutra, Luciano Vieira
Guimarães, Ricardo José de Paula Souza e
Carvalho, Omar dos Santos
author_role author
author2 Freitas, Corina da Costa
Dutra, Luciano Vieira
Guimarães, Ricardo José de Paula Souza e
Carvalho, Omar dos Santos
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Fonseca, Fernanda Rodrigues
Freitas, Corina da Costa
Dutra, Luciano Vieira
Guimarães, Ricardo José de Paula Souza e
Carvalho, Omar dos Santos
dc.subject.en.pt_BR.fl_str_mv Spatial relations
Generalized proximity matrices
Spatial analysis
Regression analysis
Schistosomiasis mansonia
topic Spatial relations
Generalized proximity matrices
Spatial analysis
Regression analysis
Schistosomiasis mansonia
description CNPq, CAPES, FAPESP and FAPEMIG
publishDate 2014
dc.date.issued.fl_str_mv 2014
dc.date.accessioned.fl_str_mv 2015-06-30T12:56:15Z
dc.date.available.fl_str_mv 2015-06-30T12:56:15Z
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.citation.fl_str_mv FONSECA, Fernanda Rodrigues et al. Spatial modeling of the schistosomiasis mansoni in Minas GeraisState, Brazil using spatial regression. Acta Tropica, v. 133, p. 56-63, May 2014.
dc.identifier.uri.fl_str_mv https://www.arca.fiocruz.br/handle/icict/11008
dc.identifier.issn.none.fl_str_mv 0001-706X
dc.identifier.doi.none.fl_str_mv 10.1016/j.actatropica.2014.01.015
identifier_str_mv FONSECA, Fernanda Rodrigues et al. Spatial modeling of the schistosomiasis mansoni in Minas GeraisState, Brazil using spatial regression. Acta Tropica, v. 133, p. 56-63, May 2014.
0001-706X
10.1016/j.actatropica.2014.01.015
url https://www.arca.fiocruz.br/handle/icict/11008
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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collection Repositório Institucional da FIOCRUZ (ARCA)
bitstream.url.fl_str_mv https://www.arca.fiocruz.br/bitstream/icict/11008/1/license.txt
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