A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , , , , , , , , |
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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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 instacron:FIOCRUZ |
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Memórias do Instituto Oswaldo Cruz |
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Memórias do Instituto Oswaldo Cruz |
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Fundação Oswaldo Cruz |
instacron_str |
FIOCRUZ |
institution |
FIOCRUZ |
repository.name.fl_str_mv |
Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruz |
repository.mail.fl_str_mv |
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