Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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=S0074-02762016000700433 |
Resumo: | The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America. |
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Memórias do Instituto Oswaldo Cruz |
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Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombiacutaneous leishmaniasisenvironmental risk factorsColombian Andean regionspatial analysisThe objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America.Instituto Oswaldo Cruz, Ministério da Saúde2016-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762016000700433Memórias do Instituto Oswaldo Cruz v.111 n.7 2016reponame:Memórias do Instituto Oswaldo Cruzinstname:Fundação Oswaldo Cruzinstacron:FIOCRUZ10.1590/0074-02760160074info:eu-repo/semantics/openAccessPérez-Flórez,MauricioOcampo,Clara BeatrizValderrama-Ardila,CarlosAlexander,Nealeng2020-04-25T17:52:25Zhttp://www.scielo.br/oai/scielo-oai.php0074-02761678-8060opendoar:null2020-04-26 02:21:18.535Memórias do Instituto Oswaldo Cruz - Fundação Oswaldo Cruztrue |
dc.title.none.fl_str_mv |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia |
title |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia |
spellingShingle |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia Pérez-Flórez,Mauricio cutaneous leishmaniasis environmental risk factors Colombian Andean region spatial analysis |
title_short |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia |
title_full |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia |
title_fullStr |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia |
title_full_unstemmed |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia |
title_sort |
Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia |
author |
Pérez-Flórez,Mauricio |
author_facet |
Pérez-Flórez,Mauricio Ocampo,Clara Beatriz Valderrama-Ardila,Carlos Alexander,Neal |
author_role |
author |
author2 |
Ocampo,Clara Beatriz Valderrama-Ardila,Carlos Alexander,Neal |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Pérez-Flórez,Mauricio Ocampo,Clara Beatriz Valderrama-Ardila,Carlos Alexander,Neal |
dc.subject.por.fl_str_mv |
cutaneous leishmaniasis environmental risk factors Colombian Andean region spatial analysis |
topic |
cutaneous leishmaniasis environmental risk factors Colombian Andean region spatial analysis |
dc.description.none.fl_txt_mv |
The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America. |
description |
The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-07-01 |
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=S0074-02762016000700433 |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762016000700433 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0074-02760160074 |
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.111 n.7 2016 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 |
|
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1669937721286590464 |