Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species
Autor(a) principal: | |
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Data de Publicação: | 2004 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista da Sociedade Brasileira de Medicina Tropical |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822004000100003 |
Resumo: | An important aspect of tropical medicine is analysis of geographic aspects of risk of disease transmission, which for lack of detailed public health data must often be reduced to an understanding of the distributions of critical species such as vectors and reservoirs. We examine the applicability of a new technique, ecological niche modeling, to the challenge of understanding distributions of such species based on municipalities in the state of São Paulo in which a group of 5 Lutzomyia sandfly species have been recorded. The technique, when tested based on independent occurrence data, yielded highly significant predictions of species' distributions; minimum sample sizes for effective predictions were around 40 municipalities. |
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Revista da Sociedade Brasileira de Medicina Tropical |
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Using epidemiological survey data to infer geographic distributions of leishmaniasis vector speciesEcological niche modelingGenetic algorithm for rule-set predictionLutzomyiaLeishmaniasisAn important aspect of tropical medicine is analysis of geographic aspects of risk of disease transmission, which for lack of detailed public health data must often be reduced to an understanding of the distributions of critical species such as vectors and reservoirs. We examine the applicability of a new technique, ecological niche modeling, to the challenge of understanding distributions of such species based on municipalities in the state of São Paulo in which a group of 5 Lutzomyia sandfly species have been recorded. The technique, when tested based on independent occurrence data, yielded highly significant predictions of species' distributions; minimum sample sizes for effective predictions were around 40 municipalities.Sociedade Brasileira de Medicina Tropical - SBMT2004-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822004000100003Revista da Sociedade Brasileira de Medicina Tropical v.37 n.1 2004reponame:Revista da Sociedade Brasileira de Medicina Tropicalinstname:Sociedade Brasileira de Medicina Tropical (SBMT)instacron:SBMT10.1590/S0037-86822004000100003info:eu-repo/semantics/openAccessPeterson,A. TownsendPereira,Ricardo ScachettiNeves,Vera Fonseca de Camargoeng2004-03-19T00:00:00Zoai:scielo:S0037-86822004000100003Revistahttps://www.sbmt.org.br/portal/revista/ONGhttps://old.scielo.br/oai/scielo-oai.php||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br1678-98490037-8682opendoar:2004-03-19T00:00Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT)false |
dc.title.none.fl_str_mv |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species |
title |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species |
spellingShingle |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species Peterson,A. Townsend Ecological niche modeling Genetic algorithm for rule-set prediction Lutzomyia Leishmaniasis |
title_short |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species |
title_full |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species |
title_fullStr |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species |
title_full_unstemmed |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species |
title_sort |
Using epidemiological survey data to infer geographic distributions of leishmaniasis vector species |
author |
Peterson,A. Townsend |
author_facet |
Peterson,A. Townsend Pereira,Ricardo Scachetti Neves,Vera Fonseca de Camargo |
author_role |
author |
author2 |
Pereira,Ricardo Scachetti Neves,Vera Fonseca de Camargo |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Peterson,A. Townsend Pereira,Ricardo Scachetti Neves,Vera Fonseca de Camargo |
dc.subject.por.fl_str_mv |
Ecological niche modeling Genetic algorithm for rule-set prediction Lutzomyia Leishmaniasis |
topic |
Ecological niche modeling Genetic algorithm for rule-set prediction Lutzomyia Leishmaniasis |
description |
An important aspect of tropical medicine is analysis of geographic aspects of risk of disease transmission, which for lack of detailed public health data must often be reduced to an understanding of the distributions of critical species such as vectors and reservoirs. We examine the applicability of a new technique, ecological niche modeling, to the challenge of understanding distributions of such species based on municipalities in the state of São Paulo in which a group of 5 Lutzomyia sandfly species have been recorded. The technique, when tested based on independent occurrence data, yielded highly significant predictions of species' distributions; minimum sample sizes for effective predictions were around 40 municipalities. |
publishDate |
2004 |
dc.date.none.fl_str_mv |
2004-02-01 |
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://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822004000100003 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822004000100003 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0037-86822004000100003 |
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 |
Sociedade Brasileira de Medicina Tropical - SBMT |
publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina Tropical - SBMT |
dc.source.none.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical v.37 n.1 2004 reponame:Revista da Sociedade Brasileira de Medicina Tropical instname:Sociedade Brasileira de Medicina Tropical (SBMT) instacron:SBMT |
instname_str |
Sociedade Brasileira de Medicina Tropical (SBMT) |
instacron_str |
SBMT |
institution |
SBMT |
reponame_str |
Revista da Sociedade Brasileira de Medicina Tropical |
collection |
Revista da Sociedade Brasileira de Medicina Tropical |
repository.name.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT) |
repository.mail.fl_str_mv |
||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br |
_version_ |
1752122152463630336 |