ArticlePloS one2023
Space-environment relationship in the identification of potential areas of expansion of Trypanosoma cruzi infection in Didelphis aurita in the Atlantic Rainforest.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 4 citations in OpenAlex.
- Landscape modeling as a surveillance strategy for Trypanosoma cruzi vectors in Brazil.Parasites & vectors · 2026Article
- Spatial overlap of palm trees and triatomine distribution areas in Brazil.Scientific reports · 2026Article
- Unveiling the ecology and spatial dynamics of Trypanosoma cruzi, its DTUs and Triatoma vitticeps in the Atlantic Forest of south-eastern Espírito Santo State, Brazil.PLoS neglected tropical diseases · 2026Article
- On the juice? Trypanosoma cruzi vectorial-oral outbreak investigation in a semi-arid rural area of Brazil.Parasites & vectors · 2025Article
- Climate change-induced degradation of expert range maps drawn for kissing bugs (Hemiptera: Reduviidae) and long-standing current and future sampling gaps across the Americas.Memorias do Instituto Oswaldo Cruz · 2024Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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