Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators

Detalhes bibliográficos
Autor(a) principal: Martins-Bedê,Flávia T
Data de Publicação: 2010
Outros Autores: Dutra,Luciano V, Freitas,Corina C, Guimarães,Ricardo JPS, Amaral,Ronaldo S, Drummond,Sandra C, Carvalho,Omar S
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=S0074-02762010000400033
Resumo: Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.
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spelling Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicatorsschistosomiasisrisk mappingpublic healthdecision treeSchistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.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=S0074-02762010000400033Memórias do Instituto Oswaldo Cruz v.105 n.4 2010reponame:Memórias do Instituto Oswaldo Cruzinstname:Fundação Oswaldo Cruzinstacron:FIOCRUZ10.1590/S0074-02762010000400033info:eu-repo/semantics/openAccessMartins-Bedê,Flávia TDutra,Luciano VFreitas,Corina CGuimarães,Ricardo JPSAmaral,Ronaldo SDrummond,Sandra CCarvalho,Omar Seng2020-04-25T17:50:48Zhttp://www.scielo.br/oai/scielo-oai.php0074-02761678-8060opendoar:null2020-04-26 02:17:03.524Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruztrue
dc.title.none.fl_str_mv Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
title Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
spellingShingle Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
Martins-Bedê,Flávia T
schistosomiasis
risk mapping
public health
decision tree
title_short Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
title_full Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
title_fullStr Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
title_full_unstemmed Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
title_sort Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
author Martins-Bedê,Flávia T
author_facet Martins-Bedê,Flávia T
Dutra,Luciano V
Freitas,Corina C
Guimarães,Ricardo JPS
Amaral,Ronaldo S
Drummond,Sandra C
Carvalho,Omar S
author_role author
author2 Dutra,Luciano V
Freitas,Corina C
Guimarães,Ricardo JPS
Amaral,Ronaldo S
Drummond,Sandra C
Carvalho,Omar S
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Martins-Bedê,Flávia T
Dutra,Luciano V
Freitas,Corina C
Guimarães,Ricardo JPS
Amaral,Ronaldo S
Drummond,Sandra C
Carvalho,Omar S
dc.subject.por.fl_str_mv schistosomiasis
risk mapping
public health
decision tree
topic schistosomiasis
risk mapping
public health
decision tree
dc.description.none.fl_txt_mv Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.
description Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.
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=S0074-02762010000400033
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762010000400033
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0074-02762010000400033
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
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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