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		<doi>10.1109/IGARSS.2008.4778845</doi>
		<issn>0196-2892</issn>
		<label>lattes: 3532895753681553 1 MartinsBedêFDSFDGAC:2009:RiMaSc</label>
		<citationkey>Martins-BedêFDSFDGAC:2008:RiMaSc</citationkey>
		<title>Risk Mapping of the Schistosomiasis in Minas Gerais, Brasil, using MODIS and socioeconomic spatial data</title>
		<year>2008</year>
		<month>July</month>
		<typeofwork>journal article</typeofwork>
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		<author>Martins-Bedê, Flávia de Toledo,</author>
		<author>Freitas, Corina da Costa,</author>
		<author>Dutra, Luciano Vieira,</author>
		<author>Sandri, Sandra Aparecida,</author>
		<author>Fonseca, Fernanda Rodrigues,</author>
		<author>Drummond, Isabela Neves,</author>
		<author>Guimarães, Ricardo José de Paula Souza e,</author>
		<author>Amaral, Ronaldo Santos do,</author>
		<author>Carvalho, Omar dos Santos,</author>
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		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation></affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Centro de Pesquisas René Rachou/FIOCRUZ,MG, Brazil</affiliation>
		<affiliation>Programa de Pós-Graduação da Santa Casa de Misericórdia de Belo Horizonte, MG, Brazil</affiliation>
		<affiliation>Centro de Pesquisas René Rachou/FIOCRUZ,MG, Brazil</affiliation>
		<affiliation>Secretaria de Vigilância em Saúde/MS</affiliation>
		<affiliation>Universidade Federal de Minas Gerais/UFMG,MG,Brazil</affiliation>
		<electronicmailaddress>flavinha@dpi.inpe.br</electronicmailaddress>
		<e-mailaddress>flavinha@dpi.inpe.br</e-mailaddress>
		<journal>IEEE Transactions on Geoscience and Remote Sensing</journal>
		<volume>1</volume>
		<pages>1-10</pages>
		<secondarymark>A_CIÊNCIA_DA_COMPUTAÇÃO A_CIÊNCIAS_AGRÁRIAS A_GEOCIÊNCIAS A_GEOGRAFIA B_ASTRONOMIA_/_FÍSICA</secondarymark>
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		<contenttype>External Contribution</contenttype>
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		<keywords>Disease development, Disease risks, Disease spreading, Environmental variables, Favorable conditions, Health management, Human development, Minas Gerais , Brazil, Schistosoma mansoni, schistosomiasis mansoni, Spatial analysis, Spatial dependence, Spatial regression, Spatial regression model, Regression analysis, Remote sensing, Geology.</keywords>
		<abstract>Schistosomiasis mansoni is a disease with social and behavioral characteristics, and distributed mainly in poor regions of Brazil. From 1995 to 2005 more than a million positive cases of the disease were reported, 27% of them reported in Minas Gerais state. The objective of this work is to estimate the prevalence risk of schistosomiasis in the Minas Gerais state through the characterization of the habitat of the snail. Two approaches were used for modeling the risk, by making use of the following types of variables: remote sensing, climate, socioeconomic, and variables that characterizes the neighborhood. In the first approach a unique regression model was generated and used to estimate the disease risk for the entire state. In the second approach, the state was divided in four regions, and four models were generated and used to estimate the disease risk across state, one for each region. The coefficients of determination for these two approaches were 0.424 and 0.717, respectively.</abstract>
		<area>SRE</area>
		<language>en</language>
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		<notes>Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International</notes>
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