Environmental determinants of the distribution of Chagas disease vectors in south-eastern Guatemala

Abstract

Abstract.The associations between the presence of triatomines and environmental variables were studied using correlation analysis and logistic regression models for a sample of villages in the south-eastern provinces of Guatemala. Information on the presence of Triatoma dimidiata, T. nitida and Rhodnius prolixus came from entomological surveys carried out by the Ministry of Health of Guatemala as part of its vector control programme. Environmental information for each village was extracted from digital thematic maps developed by the Ministry of Agriculture. The presence of T. nitida was found to be significantly associated with the average minimum temperature. The odds of presence of T. nitida in a village decreased as the average minimum temperature increased. T. nitida exists at altitudes above 1000 m above sea level in temperate regions. The presence of R. prolixus showed a significant positive association with maximum absolute temperature and relative humidity. The logistic regression model for R. prolixus showed a good fit and predicted suitable habitats in the provinces of Chiquimula, Zacapa and Jalapa, which agrees with the known distribution of the species. Habitat partitioning between R. prolixus and T. dimidiata is suggested by their significant and opposite associations with maximum absolute temperature. Improved models to predict suitable habitats for T. dimidiata hold promise for spatial targeting of integrated vector management.

The potential for emergence of Chagas disease in the United States

“…In particular, Peterson et al (2002) applied the genetic algorithm for rule-set prediction (GARP) model to the T. gerstaeckeri species' range in Mexico to evaluate the environmental characteristics under which the disease agent and vector thrive. Similarly, a regional analysis in Guatemala utilized environmental factors and data from field collections to determine the Chagas disease vector's primary habitat range (Bustamante et al, 2007). The broadscale study presented here fills a gap in research on the potential for Chagas disease emergence in the United States by using a GIS to analyze the current and potential triatomine range within the country.…”

“…Wood (1938) described the northward range expansion of T. protracta in California, but since that time, research on the triatomine's range has been limited in the United States with the exception of modeling the species' range in parts of Texas Beard et al, 2003). Modeling efforts have mapped the triatomine range in much of Latin America (Abad-Franch et al, 2001;Costa et al, 2002;Peterson et al, 2002;Guzman-Tapia et al, 2005;López-Cárdenas et al, 2005;Bustamante et al, 2007). In particular, Peterson et al (2002) applied the genetic algorithm for rule-set prediction (GARP) model to the T. gerstaeckeri species' range in Mexico to evaluate the environmental characteristics under which the disease agent and vector thrive.…”

Climatic factors influencing triatomine occurrence in Central-West Brazil

“…Specific climatic conditions can influence the occurrence of triatomines (Bustamante et al 2007). Ecological niche modelling (ENM) is an approach that permits the exploration of geographic and ecologic phenomena based on known occurrences of species (Peterson 2011).…”

Environmental Determinants of the Distribution of Chagas Disease Vector Triatoma dimidiata in Colombia

“…14,15 During the past few years, a growing number of studies have attempted to establish integrated relationships between environmental variables and triatominae distribution. 13,14,21,22,[24][25][26][27][28][29]42 In this study, environmental variables that showed association with the presence of T. dimidiata were MaxNDVI, MinLST, and the DEM in the statistical model that we developed using variables extracted from remote sensors and NDVI and temperature seasonality and annual precipitation (both from WorldClim database) in ENM. Both models were in agreement with the importance of the vegetation index associated with T. dimidiata infestation.…”

“…The local environmental determinants for the presence of triatomines include altitude, climate, vegetation type, and land use. 13 Analytical tools such as geographic information systems (GIS), remote sensing, and niche modeling have greatly enhanced our ability to evaluate the relationships between environmental factors and vector ecology or disease transmission. 14 Remote sensing data are increasingly being used to measure environmental and topographic variables on the ground, and GIS are being used to model these data both spatially and temporally.…”