A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil

Detalhes bibliográficos
Autor(a) principal: Guimarães,Ricardo José de Paula Souza
Data de Publicação: 2010
Outros Autores: Freitas,Corina Costa, Dutra,Luciano Vieira, Scholte,Ronaldo Guilherme Carvalho, Martins-Bedé,Flávia Toledo, Fonseca,Fernanda Rodrigues, Amaral,Ronaldo Santos, Drummond,Sandra Costa, Felgueiras,Carlos Alberto, Oliveira,Guilherme Corrêa, Carvalho,Omar Santos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Memórias do Instituto Oswaldo Cruz
Texto Completo: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762010000400030
Resumo: Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.
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spelling A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazilschistosomiasisgeographical information systemgeostatistical proceduresBiomphalariamultiple linear regressionepidemiologyGeographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.Instituto Oswaldo Cruz, Ministério da Saúde2010-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762010000400030Memórias do Instituto Oswaldo Cruz v.105 n.4 2010reponame:Memórias do Instituto Oswaldo Cruzinstname:Fundação Oswaldo Cruzinstacron:FIOCRUZ10.1590/S0074-02762010000400030info:eu-repo/semantics/openAccessGuimarães,Ricardo José de Paula SouzaFreitas,Corina CostaDutra,Luciano VieiraScholte,Ronaldo Guilherme CarvalhoMartins-Bedé,Flávia ToledoFonseca,Fernanda RodriguesAmaral,Ronaldo SantosDrummond,Sandra CostaFelgueiras,Carlos AlbertoOliveira,Guilherme CorrêaCarvalho,Omar Santoseng2020-04-25T17:50:48Zhttp://www.scielo.br/oai/scielo-oai.php0074-02761678-8060opendoar:null2020-04-26 02:17:02.937Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruztrue
dc.title.none.fl_str_mv A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
title A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
spellingShingle A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
Guimarães,Ricardo José de Paula Souza
schistosomiasis
geographical information system
geostatistical procedures
Biomphalaria
multiple linear regression
epidemiology
title_short A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
title_full A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
title_fullStr A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
title_full_unstemmed A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
title_sort A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
author Guimarães,Ricardo José de Paula Souza
author_facet Guimarães,Ricardo José de Paula Souza
Freitas,Corina Costa
Dutra,Luciano Vieira
Scholte,Ronaldo Guilherme Carvalho
Martins-Bedé,Flávia Toledo
Fonseca,Fernanda Rodrigues
Amaral,Ronaldo Santos
Drummond,Sandra Costa
Felgueiras,Carlos Alberto
Oliveira,Guilherme Corrêa
Carvalho,Omar Santos
author_role author
author2 Freitas,Corina Costa
Dutra,Luciano Vieira
Scholte,Ronaldo Guilherme Carvalho
Martins-Bedé,Flávia Toledo
Fonseca,Fernanda Rodrigues
Amaral,Ronaldo Santos
Drummond,Sandra Costa
Felgueiras,Carlos Alberto
Oliveira,Guilherme Corrêa
Carvalho,Omar Santos
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Guimarães,Ricardo José de Paula Souza
Freitas,Corina Costa
Dutra,Luciano Vieira
Scholte,Ronaldo Guilherme Carvalho
Martins-Bedé,Flávia Toledo
Fonseca,Fernanda Rodrigues
Amaral,Ronaldo Santos
Drummond,Sandra Costa
Felgueiras,Carlos Alberto
Oliveira,Guilherme Corrêa
Carvalho,Omar Santos
dc.subject.por.fl_str_mv schistosomiasis
geographical information system
geostatistical procedures
Biomphalaria
multiple linear regression
epidemiology
topic schistosomiasis
geographical information system
geostatistical procedures
Biomphalaria
multiple linear regression
epidemiology
dc.description.none.fl_txt_mv Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.
description Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.
publishDate 2010
dc.date.none.fl_str_mv 2010-07-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762010000400030
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762010000400030
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0074-02762010000400030
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Instituto Oswaldo Cruz, Ministério da Saúde
publisher.none.fl_str_mv Instituto Oswaldo Cruz, Ministério da Saúde
dc.source.none.fl_str_mv Memórias do Instituto Oswaldo Cruz v.105 n.4 2010
reponame:Memórias do Instituto Oswaldo Cruz
instname:Fundação Oswaldo Cruz
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reponame_str Memórias do Instituto Oswaldo Cruz
collection Memórias do Instituto Oswaldo Cruz
instname_str Fundação Oswaldo Cruz
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repository.name.fl_str_mv Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruz
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