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

The transmission dynamics of Trypanosoma cruzi in natural environments exhibit considerable variation at the micro-locality scale. However, the specific biotic and abiotic factors driving this heterogeneity remain largely unidentified. The Atlantic Forest of the state of Espírito Santo (ES) presents a unique transmission network of T. cruzi, in which Triatoma vitticeps represents the absolute majority among existing triatomines, with high infection rates and diversity of genotypes, frequently invading homes. No infection was found in peridomestic mammals. This study aimed to elucidate the spatial and environmental distribution patterns of T. vitticeps and its infection by T. cruzi DTUs throughout Espírito Santo, quantifying the influence of abiotic variables on both vector occurrence and infection dynamics. Species Distribution Modeling (SDM) of T. cruzi genotypes in T. vitticeps collected in the Atlantic Forest of Espírito Santo was performed using the ModleR package, in the R programming language, with climate and landscape variables (~1km²) selected by Spearman's correlation [-0.7 ≤ ρ ≤ 0.7]. True Skill Statistic (≥ 0.7) was used to evaluate model performance. Decision tree to classify T. vitticeps infection by T. cruzi was created using machine learning algorithms in WEKA 3.8.6 software. The SDMs of T. vitticeps and its infection demonstrated: i. Central and South mesoregions presented better environmental conditions for their occurrence; ii. association with mountainous regions with high altitudes, humid and superhumid, with vegetation density and vigor and high values of topographic diversity; iii. Schoener similarity suggests Z3 is mixed, dominated by TcIV and TcIII in Central-South, with TcIII influence Northwest and North Coast; iv. Infection was explained by wind speed, mammal richness, and temperature, with the decision tree identifying 84% of positives and 29% of negatives. T. vitticeps may originate in high-altitude regions and disperse via wind to lowlands, promoting domiciliary invasion and supporting previously hypothesized long-distance transmission of T. cruzi.

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Journal
PLoS neglected tropical diseases
Published
2026-03-16
DOI
https://doi.org/10.1371/journal.pntd.0014111
Primary Topic
Trypanosoma species research and implications
Type
article
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article

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

Maria Augusta Dario, Raphael Testai, Flávio Luis de Mello, Ane Luíse Quinze Dias de Faro de Oliveira et al.
PLoS neglected tropical diseases
Trypanosoma species research and implications
article

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

Maria Augusta Dario, Raphael Testai, Flávio Luis de Mello, Ane Luíse Quinze Dias de Faro de Oliveira, Felipe de Oliveira, Ana Maria Jansen, Samanta Cristina das Chagas Xavier
article en

Abstract

The transmission dynamics of Trypanosoma cruzi in natural environments exhibit considerable variation at the micro-locality scale. However, the specific biotic and abiotic factors driving this heterogeneity remain largely unidentified. The Atlantic Forest of the state of Espírito Santo (ES) presents a unique transmission network of T. cruzi, in which Triatoma vitticeps represents the absolute majority among existing triatomines, with high infection rates and diversity of genotypes, frequently invading homes. No infection was found in peridomestic mammals. This study aimed to elucidate the spatial and environmental distribution patterns of T. vitticeps and its infection by T. cruzi DTUs throughout Espírito Santo, quantifying the influence of abiotic variables on both vector occurrence and infection dynamics. Species Distribution Modeling (SDM) of T. cruzi genotypes in T. vitticeps collected in the Atlantic Forest of Espírito Santo was performed using the ModleR package, in the R programming language, with climate and landscape variables (~1km²) selected by Spearman's correlation [-0.7 ≤ ρ ≤ 0.7]. True Skill Statistic (≥ 0.7) was used to evaluate model performance. Decision tree to classify T. vitticeps infection by T. cruzi was created using machine learning algorithms in WEKA 3.8.6 software. The SDMs of T. vitticeps and its infection demonstrated: i. Central and South mesoregions presented better environmental conditions for their occurrence; ii. association with mountainous regions with high altitudes, humid and superhumid, with vegetation density and vigor and high values of topographic diversity; iii. Schoener similarity suggests Z3 is mixed, dominated by TcIV and TcIII in Central-South, with TcIII influence Northwest and North Coast; iv. Infection was explained by wind speed, mammal richness, and temperature, with the decision tree identifying 84% of positives and 29% of negatives. T. vitticeps may originate in high-altitude regions and disperse via wind to lowlands, promoting domiciliary invasion and supporting previously hypothesized long-distance transmission of T. cruzi.

PLoS neglected tropical diseasesVol. 20(3)
Universidade Federal do Rio de Janeiro (BR), Fundação Oswaldo Cruz (BR)
Openalex Percentile: Top 22%
Trypanosoma species research and implications
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