Ecological Niche Modeling is widely used for animals, but rarely for understanding the parasite ecology. Trypanosoma cruzi is a heterogeneous and widely dispersed multi-host parasite. Didelphis aurita is a generalist species, both in terms of diet and environments. We modeled the D. aurita niche and T. cruzi infection in the Brazilian Atlantic Rainforest, using the models of two common vector species (Triatoma vitticeps and Panstrongylus megistus) as biotic variables, predicting their occurrence. Records of T. cruzi infected and non-infected D. aurita were analyzed through climate and landscape approaches by the Ecoland method. Models for each triatomine species and infected and noninfected D. aurita were produced considering climate and landscape: resolution of ~1km2 selected by Pearson's correlation [-0.7≤α≤0.7]. For modeling, seven algorithms available in ModleR package were used. True Skill Statistic was used to evaluate the models' performance (≥ 0.7). T. vitticeps indicates that there is a spatial dependence with warm areas in the southeastern region while P. megistus presented a distribution with high environmental suitability concentrated in the Southeast. High values of climatic suitability, landscape and potential presence of T. vitticeps and P. megistus were considered necessary, but not sufficient for the presence of D. aurita infected by T. cruzi. Climate models showed an ecological niche with suitability variations homogeneous, and landscape models showed a distribution of habitat conditions along the biome, with a fragmented profile and heterogeneous between locations. Ecoland demonstrated that D. aurita has different degrees of impact on its role in the enzootic cycle in different locations of the Atlantic Rainforest. Associating the models with the Ecoland method allowed the recognition of areas where D. aurita are important T. cruzi reservoirs. Areas of high suitability for the presence of marsupials are a necessary, but not sufficient for D. aurita to act as a reservoir for T. cruzi.
Copyright: © 2023 Testai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.