Domestic (re)infestation risk with the main vector Triatoma infestans increases with surrounding green vegetation and social vulnerability in the Argentine Chaco

• Published in: Parasites & vectors Vol. 17; no. 1; p. 240
• Main Authors: Elias, Dario E, Cardinal, Marta V, Macchiaverna, Natalia P, Enriquez, Gustavo F, Gürtler, Ricardo E, Gaspe, M Sol
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 27.05.2024; BioMed Central; BMC
• Subjects: Animals; Argentina - epidemiology; Bayes Theorem; Chagas; Chagas Disease - epidemiology; Chagas Disease - transmission; Chagas' disease; Environmental aspects; Health aspects; Housing; Humans; Insect Vectors - physiology; Management; NDVI; Plant communities; Risk Factors; Rural Population; Social disparities; Socioeconomic Factors; Spatial analysis; Triatoma - parasitology; Triatoma - physiology; Trypanosoma cruzi; Vector-borne diseases; Argentina; Vector-borne diseases; Spatial analysis; NDVI; Chagas; Social disparities
• ISSN: 1756-3305; 1756-3305
• DOI: 10.1186/s13071-024-06324-3

Chagas disease, caused by Trypanosoma cruzi, is still a public health problem in Latin America and in the Southern Cone countries, where Triatoma infestans is the main vector. We evaluated the relationships among the density of green vegetation around rural houses, sociodemographic characteristics, and domestic (re)infestation with T. infestans while accounting for their spatial dependence in the municipality of Pampa del Indio between 2007 and 2016. The study comprised sociodemographic and ecological variables from 734 rural houses with no missing data. Green vegetation density surrounding houses was estimated by the normalized difference vegetation index (NDVI). We used a hierarchical Bayesian logistic regression composed of fixed effects and spatial random effects to estimate domestic infestation risk and quantile regressions to evaluate the association between surrounding NDVI and selected sociodemographic variables. Qom ethnicity and the number of poultry were negatively associated with surrounding NDVI, whereas overcrowding was positively associated with surrounding NDVI. Hierarchical Bayesian models identified that domestic infestation was positively associated with surrounding NDVI, suitable walls for triatomines, and overcrowding over both intervention periods. Preintervention domestic infestation also was positively associated with Qom ethnicity. Models with spatial random effects performed better than models without spatial effects. The former identified geographic areas with a domestic infestation risk not accounted for by fixed-effect variables. Domestic infestation with T. infestans was associated with the density of green vegetation surrounding rural houses and social vulnerability over a decade of sustained vector control interventions. High density of green vegetation surrounding rural houses was associated with households with more vulnerable social conditions. Evaluation of domestic infestation risk should simultaneously consider social, landscape and spatial effects to control for their mutual dependency. Hierarchical Bayesian models provided a proficient methodology to identify areas for targeted triatomine and disease surveillance and control.