Leishmaniasis is a zoonotic disease transmitted to humans by a protozoan parasite through sandfly vectors and multiple vertebrate hosts. The Pan American Health Organization reported a declining trend in cases, with Brazil, Colombia, Peru, Nicaragua, and Bolivia having the most cases in 2020. There are still knowledge gaps in transmission and the parasite-host relationship. Ecological niche modeling has been used to study host-vector relationships, disease dynamics, and the impact of climate change. Understanding these aspects can aid in early surveillance and vector control strategies. The potential distribution of five host species associated with the transmission of cutaneous leishmaniasis (CL) was modeled. Occurrence data were collected for each host species, and environmental variables were used to build the models. Climatic data from El Niño, La Niña, and Neutral episodes were used to compare the predicted distributions. Additionally, the potential distributions of four vector species were compared to identify overlaps with host species. Niche analysis was conducted to evaluate changes in vector niches across episodes and to identify host-vector pairs based on niche overlap in geographic and environmental spaces. After spatial thinning, 467 records were obtained, and 1,190 candidate models were evaluated for each species. Results showed the distribution of occurrences in the environmental space, highlighting a high risk of extrapolation beyond the calibration areas. Movement-Oriented Parity analysis revealed distinct distribution patterns under different climate conditions, with areas of environmental similarity identified. Bradypus variegatus exhibited a broad potential distribution, while Dasypus novemcinctus and Didelphis marsupialis had more restricted ranges. Sylvilagus braziliensis covered most of the Neotropics. Our study provides valuable insights into ecological niches and geographic ranges of these species, contributing to the understanding of cutaneous leishmaniasis transmission dynamics.

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http://dx.doi.org/10.1016/j.actatropica.2023.107060DOI Listing

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