Climate Change Impact on Human-Rodent Interfaces: Modeling Junin Virus Reservoir Shifts

Nuri Flores-Pérez; Pranav Kulkarni; Marcela Uhart; Pranav S Pandit

doi:10.1007/s10393-025-01723-z

Climate Change Impact on Human-Rodent Interfaces: Modeling Junin Virus Reservoir Shifts

Ecohealth. 2025 Jun 27. doi: 10.1007/s10393-025-01723-z. Online ahead of print.

Authors

Nuri Flores-Pérez¹, Pranav Kulkarni², Marcela Uhart³, Pranav S Pandit²

Affiliations

¹ Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA. flores.nuri@gmail.com.
² Department of Population Health and Reproduction, School of Veterinary Medicine, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.
³ School of Veterinary Medicine, Karen C. Drayer Wildlife Health Center, University of California, Davis, CA, USA.

PMID: 40576885
DOI: 10.1007/s10393-025-01723-z

Abstract

The drylands vesper mouse (Calomys musculinus) is the primary host for Junin mammarenavirus (JUNV), the etiological agent of Argentine hemorrhagic fever in humans. We assessed the potential distribution of C. musculinus and identified disease transmission hotspots under current climatic conditions and projected future scenarios, including severe (Representative Concentration Pathway 8.5) and intermediate (Representative Concentration Pathway 4.5) climate change scenarios in 2050 and 2070. Utilizing tree-based machine learning algorithms, we modeled C. musculinus distribution by incorporating bioclimatic and landscape predictors. The model showed strong performance, achieving F-scores between 80.22 and 83.09%. Key predictors indicated that C. musculinus prefers warm temperatures, moderate annual precipitation, low precipitation variability, and low pasture coverage. Under the severe climate change scenario, suitable areas for the rodent and hotspots for potential disease decreased. The intermediate scenario showed an expansion in C. musculinus distribution alongside increased potential hotspot zones. Despite the complexity of ecological systems and the limitations of the model, our findings offer a framework for preventive measures and ecological studies in regions prone to the expansion of C. musculinus and in hotspots for disease transmission driven by climate change.

Keywords: Calomys musculinus; arenaviruses; argentine hemorrhagic fever; climate change; drylands vesper mouse; machine learning; species distribution model.

Abstract

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