Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators
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=S0074-02762010000400033 |
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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Memórias do Instituto Oswaldo Cruz |
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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 |
instacron_str |
FIOCRUZ |
institution |
FIOCRUZ |
repository.name.fl_str_mv |
Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruz |
repository.mail.fl_str_mv |
|
_version_ |
1669937707938217984 |