Environmental Determinants of the Distribution of Chagas Disease Vector Triatoma dimidiata in Colombia |
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Authors: | Gabriel Parra-Henao Oscar Quirós-Gómez Nicolas Jaramillo-O ángela Segura Cardona |
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Affiliation: | Red Chagas Colombia, Bogotá, Colombia; Grupo de Epidemiología y Bioestadística, Universidad CES, Medellín, Colombia; Instituto de Biología, Universidad de Antioquia, Medellín, Colombia |
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Abstract: | Triatomadimidiata (Hemiptera: Reduviidae) is a secondary vector of Trypanosoma cruzi in Colombia and represents an important epidemiological risk mainly in the central and oriental regions of the country where it occupies sylvatic, peridomestic, and intradomestic ecotopes, and because of this complex distribution, its distribution and abundance could be conditioned by environmental factors. In this work, we explored the relationship between T. dimidiata distribution and environmental factors in the northwest, northeast, and central zones of Colombia and developed predictive models of infestation in the country. The associations between the presence of T. dimidiata and environmental variables were studied using logistic regression models and ecological niche modeling for a sample of villages in Colombia. The analysis was based on the information collected in field about the presence of T. dimidiata and the environmental data for each village extracted from remote sensing images. The presence of Triatoma dimidiata (Latreille, 1811) was found to be significantly associated with the maximum vegetation index, minimum land surface temperature (LST), and the digital elevation for the statistical model. Temperature seasonality, annual precipitation, and vegetation index were the variables that most influenced the ecological niche model of T. dimidiata distribution. The logistic regression model showed a good fit and predicted suitable habitats in the Andean and Caribbean regions, which agrees with the known distribution of the species, but predicted suitable habitats in the Pacific and Orinoco regions proposing new areas of research. Improved models to predict suitable habitats for T. dimidiata hold promise for spatial targeting of integrated vector management. |
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