Successional and native forests predict the occurrence and infection status of Chagas disease vectors in Panama

Abstract Changes in land use and land cover (LULC) due to agricultural expansion, commercial land management and other human‐driven modifications significantly influence the ecology of pathogens and vectors. This underscores the urgent need to understand how these respond to rapid and dynamic land use changes in these ecosystems and, critically, to identify strategies for mitigating their impacts. In tropical Central and South America, palm trees serve as primary habitats for Rhodnius kissing bugs, vectors of Trypanosoma cruzi , the etiologic agent of Chagas disease. This study investigates how LULC, weather and traits of the palm Attalea butyracea predict the occurrence and infection of Rhodnius pallescens , integrating field data collection, molecular detection and spatial and hierarchical analyses across a rural landscape in Panama. Rhodnius pallescens were collected from 46 palms in 11 communities with different landscape compositions including native forests, grasslands, successional forests and artificial structures. Robust occupancy modelling using land cover data at 10 m 2 resolution revealed that successional forest cover at 300 m spatial scale predicted greater occurrence of R. pallescens , whereas native forest predicted lower occurrence. Quadratic models outperformed linear models, indicating occupancy peaks at intermediate land covers and palm tree traits. Real‐time PCR assays detected Trypanosoma infections in 70% of R. pallescens across communities. Spatial autocorrelation analyses showed significant spatial clustering for T. cruzi but not for Trypanosoma rangeli . We used generalized additive mixed models to assess the influence of palm‐level and landscape‐scale attributes on parasite infection and identified significant nonlinear positive associations between T . cruzi infection and native forest and grassland, with high predictive accuracy (AUC = 0.90). Synthesis and applications . Findings here show that successional forest predicts greater kissing bug infestation risk in palm trees, whereas native forest predicts lower kissing bug occurrence but greater infection with T. cruzi . These insights can guide land use planning towards vegetation management practices that help minimize T. cruzi transmission risks for rural communities. Importantly, vector surveillance should target forest‐grassland ecotones and consider forest successional stages near settlements, with intensified monitoring after disturbances; this approach is applicable to other vector‐borne pathogen systems shaped by land use change.