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Authordc.contributor.authorHernández, Jaime 
Authordc.contributor.authorNúñez, Ignacia 
Authordc.contributor.authorBacigalupo, Antonella 
Authordc.contributor.authorCattan Ayala, Pedro 
Admission datedc.date.accessioned2018-12-20T14:13:57Z
Available datedc.date.available2018-12-20T14:13:57Z
Publication datedc.date.issued2013
Cita de ítemdc.identifier.citationInternational Journal of Health Geographics, Volumen 12,
Identifierdc.identifier.issn1476072X
Identifierdc.identifier.other10.1186/1476-072X-12-29
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/155031
Abstractdc.description.abstractBackground: Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area.Methods: Vector's locations were obtained with a rural householders' survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids.Results: The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range.Conclusions: The methodology presented here was useful to model the distributio
Lenguagedc.language.isoen
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
Sourcedc.sourceInternational Journal of Health Geographics
Keywordsdc.subjectMepraia spinolai
Keywordsdc.subjectRandom forests
Keywordsdc.subjectRemote sensing
Keywordsdc.subjectTriatoma infestans
Keywordsdc.subjectTriatominae
Títulodc.titleModeling the spatial distribution of Chagas disease vectors using environmental variables and peoplés knowledge
Document typedc.typeArtículo de revista
dcterms.accessRightsdcterms.accessRightsAcceso Abierto
Catalogueruchile.catalogadorSCOPUS
Indexationuchile.indexArtículo de publicación SCOPUS
uchile.cosechauchile.cosechaSI


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Attribution-NonCommercial-NoDerivs 3.0 Chile
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile