Downscaling incidence risk mapping for a Colombian malaria endemic region

ABSTRACT: Objective. To map at a fine spatial scale, the risk of malaria incidence for the important endemic region is Uraba-Bajo Cauca and Alto Sinu, NW Colombia, using a new modelling framework based on GIS and remotely sensed environmental data. Methods. The association between environmental and...

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Autores:
Altamiranda Saavedra, Mariano
Porcasi, Ximena
Scavuzzo, Carlos Marcelo
Correa Ochoa, Margarita Maria
Tipo de recurso:
Article of investigation
Fecha de publicación:
2018
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/20008
Acceso en línea:
http://hdl.handle.net/10495/20008
Palabra clave:
Ecoepidemiology
Ecoepidemiología
Anopheles
Malaria - Colombia
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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repository_id_str
dc.title.spa.fl_str_mv Downscaling incidence risk mapping for a Colombian malaria endemic region
title Downscaling incidence risk mapping for a Colombian malaria endemic region
spellingShingle Downscaling incidence risk mapping for a Colombian malaria endemic region
Ecoepidemiology
Ecoepidemiología
Anopheles
Malaria - Colombia
title_short Downscaling incidence risk mapping for a Colombian malaria endemic region
title_full Downscaling incidence risk mapping for a Colombian malaria endemic region
title_fullStr Downscaling incidence risk mapping for a Colombian malaria endemic region
title_full_unstemmed Downscaling incidence risk mapping for a Colombian malaria endemic region
title_sort Downscaling incidence risk mapping for a Colombian malaria endemic region
dc.creator.fl_str_mv Altamiranda Saavedra, Mariano
Porcasi, Ximena
Scavuzzo, Carlos Marcelo
Correa Ochoa, Margarita Maria
dc.contributor.author.none.fl_str_mv Altamiranda Saavedra, Mariano
Porcasi, Ximena
Scavuzzo, Carlos Marcelo
Correa Ochoa, Margarita Maria
dc.subject.decs.none.fl_str_mv Ecoepidemiology
Ecoepidemiología
Anopheles
topic Ecoepidemiology
Ecoepidemiología
Anopheles
Malaria - Colombia
dc.subject.lemb.none.fl_str_mv Malaria - Colombia
description ABSTRACT: Objective. To map at a fine spatial scale, the risk of malaria incidence for the important endemic region is Uraba-Bajo Cauca and Alto Sinu, NW Colombia, using a new modelling framework based on GIS and remotely sensed environmental data. Methods. The association between environmental and topographic variables obtained from remote sensors and the annual parasite incidence (API) for the years 2013–2015 was calculated using multiple regression analysis; subsequently, a model was constructed to estimate the API and to project it to the entire endemic region in order to design the risk map. The model was validated by relating the obtained API values with the presence of the three main Colombian malaria vectors, Anopheles darlingi, Anopheles albimanus and Anopheles nuneztovari. Results. Temperature and Normalized Difference Water Index (NDWI) showed a significant correlation with the observed API. The risk map of malaria incidence showed that the zones at higher risk in the Uraba-Bajo Cauca and Alto Sinu region were located south-east of the region, while the northern area presented the lowest malaria risk. A method was generated to estimate the API for small urban centres, instead of the used reports at the municipality level. Conclusions. These results provide evidence of the utility of risk maps to identify environmentally vulnerable areas at a fine spatial resolution in the Uraba-Bajo Cauca and Alto Sinu region. This information contributes to the implementation of vector control interventions at the icrogeographic scale at areas of high malaria risk.
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2021-06-08T18:58:42Z
dc.date.available.none.fl_str_mv 2021-06-08T18:58:42Z
dc.type.spa.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.issn.none.fl_str_mv 1360-2276
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10495/20008
dc.identifier.doi.none.fl_str_mv 10.1111/tmi.13128
dc.identifier.eissn.none.fl_str_mv 1365-3156
identifier_str_mv 1360-2276
10.1111/tmi.13128
1365-3156
url http://hdl.handle.net/10495/20008
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.ispartofjournalabbrev.spa.fl_str_mv Trop Med Int Health
dc.rights.spa.fl_str_mv info:eu-repo/semantics/openAccess
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dc.format.extent.spa.fl_str_mv 9
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dc.publisher.spa.fl_str_mv Blackwell Scientific Publications
dc.publisher.group.spa.fl_str_mv Microbiología Molecular
dc.publisher.place.spa.fl_str_mv Oxford, Reino Unido
institution Universidad de Antioquia
bitstream.url.fl_str_mv http://bibliotecadigital.udea.edu.co/bitstream/10495/20008/1/AltamirandaMariano_2018_DownscalingIncidenceRisk.pdf
http://bibliotecadigital.udea.edu.co/bitstream/10495/20008/2/license_rdf
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repository.name.fl_str_mv Repositorio Institucional Universidad de Antioquia
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spelling Altamiranda Saavedra, MarianoPorcasi, XimenaScavuzzo, Carlos MarceloCorrea Ochoa, Margarita Maria2021-06-08T18:58:42Z2021-06-08T18:58:42Z20181360-2276http://hdl.handle.net/10495/2000810.1111/tmi.131281365-3156ABSTRACT: Objective. To map at a fine spatial scale, the risk of malaria incidence for the important endemic region is Uraba-Bajo Cauca and Alto Sinu, NW Colombia, using a new modelling framework based on GIS and remotely sensed environmental data. Methods. The association between environmental and topographic variables obtained from remote sensors and the annual parasite incidence (API) for the years 2013–2015 was calculated using multiple regression analysis; subsequently, a model was constructed to estimate the API and to project it to the entire endemic region in order to design the risk map. The model was validated by relating the obtained API values with the presence of the three main Colombian malaria vectors, Anopheles darlingi, Anopheles albimanus and Anopheles nuneztovari. Results. Temperature and Normalized Difference Water Index (NDWI) showed a significant correlation with the observed API. The risk map of malaria incidence showed that the zones at higher risk in the Uraba-Bajo Cauca and Alto Sinu region were located south-east of the region, while the northern area presented the lowest malaria risk. A method was generated to estimate the API for small urban centres, instead of the used reports at the municipality level. Conclusions. These results provide evidence of the utility of risk maps to identify environmentally vulnerable areas at a fine spatial resolution in the Uraba-Bajo Cauca and Alto Sinu region. This information contributes to the implementation of vector control interventions at the icrogeographic scale at areas of high malaria risk.COL00137469application/pdfengBlackwell Scientific PublicationsMicrobiología MolecularOxford, Reino Unidoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARTArtículo de investigaciónhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/2.5/co/http://purl.org/coar/access_right/c_abf2https://creativecommons.org/licenses/by-nc-nd/4.0/Downscaling incidence risk mapping for a Colombian malaria endemic regionEcoepidemiologyEcoepidemiologíaAnophelesMalaria - ColombiaTrop Med Int HealthTropical Medicine and International Health110111092310Universidad de Antioquia. Escuela de Microbiología. Laboratorio de Microbiologia MolecularDepartamento Administrativo de Ciencia, Tecnología e Innovación - ColcienciasUniversidad de Antioquia. Estrategia para la Sostenibilidad de Grupos de Investigacióngrid.412881.6596-2013, 528, 2012ORIGINALAltamirandaMariano_2018_DownscalingIncidenceRisk.pdfAltamirandaMariano_2018_DownscalingIncidenceRisk.pdfArtículo de investigaciónapplication/pdf844800http://bibliotecadigital.udea.edu.co/bitstream/10495/20008/1/AltamirandaMariano_2018_DownscalingIncidenceRisk.pdf9a879bb91de24505c6e7ef691279e308MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8823http://bibliotecadigital.udea.edu.co/bitstream/10495/20008/2/license_rdfb88b088d9957e670ce3b3fbe2eedbc13MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://bibliotecadigital.udea.edu.co/bitstream/10495/20008/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5310495/20008oai:bibliotecadigital.udea.edu.co:10495/200082022-04-22 10:15:37.154Repositorio Institucional Universidad de Antioquiaandres.perez@udea.edu.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