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Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge
BACKGROUND: 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 ho...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680173/ https://www.ncbi.nlm.nih.gov/pubmed/23724993 http://dx.doi.org/10.1186/1476-072X-12-29 |
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author | Hernández, Jaime Núñez, Ignacia Bacigalupo, Antonella Cattan, Pedro E |
author_facet | Hernández, Jaime Núñez, Ignacia Bacigalupo, Antonella Cattan, Pedro E |
author_sort | Hernández, Jaime |
collection | PubMed |
description | BACKGROUND: 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 distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study’s methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases. |
format | Online Article Text |
id | pubmed-3680173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36801732013-06-25 Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge Hernández, Jaime Núñez, Ignacia Bacigalupo, Antonella Cattan, Pedro E Int J Health Geogr Research BACKGROUND: 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 distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study’s methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases. BioMed Central 2013-05-31 /pmc/articles/PMC3680173/ /pubmed/23724993 http://dx.doi.org/10.1186/1476-072X-12-29 Text en Copyright © 2013 Hernández et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Hernández, Jaime Núñez, Ignacia Bacigalupo, Antonella Cattan, Pedro E Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge |
title | Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge |
title_full | Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge |
title_fullStr | Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge |
title_full_unstemmed | Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge |
title_short | Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge |
title_sort | modeling the spatial distribution of chagas disease vectors using environmental variables and people´s knowledge |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3680173/ https://www.ncbi.nlm.nih.gov/pubmed/23724993 http://dx.doi.org/10.1186/1476-072X-12-29 |
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