Spatial fine-resolution model of malaria risk for the Colombian Pacific region

ABSTRACT : Objective To categorise and map, at high resolution, the risk of malaria incidence in the Pacific region, the main malaria-endemic region of Colombia. Methods The relationship between the environmental variables Normalized Difference Vegetation Index Normalized Difference Water Index, Top...

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Autores:
Piedrahita Hernández, Stefani Andrea
Altamiranda Saavedra, Mariano
Correa Ochoa, Margarita María
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/31090
Acceso en línea:
https://hdl.handle.net/10495/31090
Palabra clave:
Anopheles
Malaria
Incidencia
Incidence
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 Spatial fine-resolution model of malaria risk for the Colombian Pacific region
title Spatial fine-resolution model of malaria risk for the Colombian Pacific region
spellingShingle Spatial fine-resolution model of malaria risk for the Colombian Pacific region
Anopheles
Malaria
Incidencia
Incidence
title_short Spatial fine-resolution model of malaria risk for the Colombian Pacific region
title_full Spatial fine-resolution model of malaria risk for the Colombian Pacific region
title_fullStr Spatial fine-resolution model of malaria risk for the Colombian Pacific region
title_full_unstemmed Spatial fine-resolution model of malaria risk for the Colombian Pacific region
title_sort Spatial fine-resolution model of malaria risk for the Colombian Pacific region
dc.creator.fl_str_mv Piedrahita Hernández, Stefani Andrea
Altamiranda Saavedra, Mariano
Correa Ochoa, Margarita María
dc.contributor.author.none.fl_str_mv Piedrahita Hernández, Stefani Andrea
Altamiranda Saavedra, Mariano
Correa Ochoa, Margarita María
dc.subject.decs.none.fl_str_mv Anopheles
Malaria
Incidencia
Incidence
topic Anopheles
Malaria
Incidencia
Incidence
description ABSTRACT : Objective To categorise and map, at high resolution, the risk of malaria incidence in the Pacific region, the main malaria-endemic region of Colombia. Methods The relationship between the environmental variables Normalized Difference Vegetation Index Normalized Difference Water Index, Topographic Wetness Index, precipitation and temperature with the observed Annual Parasitic Index was evaluated using a generalised linear model. An incidence risk map at a resolution of 1 km2 was constructed and projected to the entire endemic region. Associations of malaria risk categories with both presence records and co-occurrence of the three main malaria vectors were determined. Results A significant correlation was found for the incidence of malaria with precipitation and Normalized Difference Vegetation Index (R2 = 0.98, P < 0.05), whereas there was no significant correlation with the remaining environmental and topographic variables. Moderate- to high-risk areas were located mainly in central Choco Department along the San Juan and Atrato rivers and in areas west of the Cauca River and Pacific lowlands of the Andes Mountains. There was a statistically significant relationship for the presence of the two main vectors Anopheles darlingi and Anopheles nuneztovari with the high malaria risk category. Furthermore, malaria risk was directly proportional to the number of co-occurring vector species. Conclusions The map obtained provides useful information on the risk of malaria in particular places of the Colombian Pacific region. The data can be used by public entities to optimise the allocation of economic resources for vector control interventions and surveillance.
publishDate 2020
dc.date.issued.none.fl_str_mv 2020
dc.date.accessioned.none.fl_str_mv 2022-10-06T14:39:18Z
dc.date.available.none.fl_str_mv 2022-10-06T14:39:18Z
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 https://hdl.handle.net/10495/31090
dc.identifier.doi.none.fl_str_mv 10.1111/tmi.13443
dc.identifier.eissn.none.fl_str_mv 1365-3156
identifier_str_mv 1360-2276
10.1111/tmi.13443
1365-3156
url https://hdl.handle.net/10495/31090
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
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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dc.publisher.spa.fl_str_mv Blackwell Science Publications
dc.publisher.group.spa.fl_str_mv Microbiología Molecular
dc.publisher.place.spa.fl_str_mv Oxford, Inglaterra
institution Universidad de Antioquia
bitstream.url.fl_str_mv https://bibliotecadigital.udea.edu.co/bitstream/10495/31090/2/license_rdf
https://bibliotecadigital.udea.edu.co/bitstream/10495/31090/3/license.txt
https://bibliotecadigital.udea.edu.co/bitstream/10495/31090/1/PiedrahitaStefani_2020%20_Spatial%20fine%e2%80%90resolution.pdf
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spelling Piedrahita Hernández, Stefani AndreaAltamiranda Saavedra, MarianoCorrea Ochoa, Margarita María2022-10-06T14:39:18Z2022-10-06T14:39:18Z20201360-2276https://hdl.handle.net/10495/3109010.1111/tmi.134431365-3156ABSTRACT : Objective To categorise and map, at high resolution, the risk of malaria incidence in the Pacific region, the main malaria-endemic region of Colombia. Methods The relationship between the environmental variables Normalized Difference Vegetation Index Normalized Difference Water Index, Topographic Wetness Index, precipitation and temperature with the observed Annual Parasitic Index was evaluated using a generalised linear model. An incidence risk map at a resolution of 1 km2 was constructed and projected to the entire endemic region. Associations of malaria risk categories with both presence records and co-occurrence of the three main malaria vectors were determined. Results A significant correlation was found for the incidence of malaria with precipitation and Normalized Difference Vegetation Index (R2 = 0.98, P < 0.05), whereas there was no significant correlation with the remaining environmental and topographic variables. Moderate- to high-risk areas were located mainly in central Choco Department along the San Juan and Atrato rivers and in areas west of the Cauca River and Pacific lowlands of the Andes Mountains. There was a statistically significant relationship for the presence of the two main vectors Anopheles darlingi and Anopheles nuneztovari with the high malaria risk category. Furthermore, malaria risk was directly proportional to the number of co-occurring vector species. Conclusions The map obtained provides useful information on the risk of malaria in particular places of the Colombian Pacific region. The data can be used by public entities to optimise the allocation of economic resources for vector control interventions and surveillance.COL00137468application/pdfengBlackwell Science PublicationsMicrobiología MolecularOxford, Inglaterrainfo: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/Spatial fine-resolution model of malaria risk for the Colombian Pacific regionAnophelesMalariaIncidenciaIncidenceTrop. Med. Int. Health.Tropical Medicine and International Health10241031258CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8823https://bibliotecadigital.udea.edu.co/bitstream/10495/31090/2/license_rdfb88b088d9957e670ce3b3fbe2eedbc13MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bibliotecadigital.udea.edu.co/bitstream/10495/31090/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD53ORIGINALPiedrahitaStefani_2020 _Spatial fine‐resolution.pdfPiedrahitaStefani_2020 _Spatial fine‐resolution.pdfArtículo de investigaciónapplication/pdf1137312https://bibliotecadigital.udea.edu.co/bitstream/10495/31090/1/PiedrahitaStefani_2020%20_Spatial%20fine%e2%80%90resolution.pdfaa3ae1dc1db6dcc5380a2c36ed8c45a6MD5110495/31090oai:bibliotecadigital.udea.edu.co:10495/310902022-10-06 09:39:19.317Repositorio Institucional Universidad de Antioquiaandres.perez@udea.edu.coTk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=