# Environmental transmission from bamboo rats: Mapping current and future talaromycosis risk in China under climate change

## TL;DR

This study maps the current and future risk of talaromycosis in China, showing how climate change and socio-economic factors influence its spread.

## Contribution

The study provides the first high-resolution predictive risk maps of talaromycosis in China using a One Health framework and climate projections.

## Key findings

- High-suitability regions for talaromycosis are concentrated in Southern/Southwestern China, aligning with known endemic areas.
- Human infection risk is higher in HIV-positive populations in core endemic zones and in HIV-negative populations in broader regions.
- Future risk projections show expansion under high emissions but contraction under low emissions climate scenarios.

## Abstract

Talaromycosis (TSM), a severe fungal infection caused by Talaromyces marneffei (TM), poses a significant threat to immunocompromised individuals in recent years. Despite its high mortality and socioeconomic burden, predictive spatial risk distributions are lacking.

Here, we first employed a One Health framework to model current and future TM/TSM risk distributions across China. Using the Maximum Entropy (Maxent) model, we predicted the habitat suitability for three key bamboo rat reservoir species. Based on this, we developed the risk distribution maps of TM/TSM across China by integrating socio-economic factors.

Accurate modeling results (AUC: 0.958–0.999) identified precipitation- and temperature- related factors as decisive environmental drivers. Specifically, high-suitability regions were concentrated in Southern/Southwestern China (Yunnan, Guangxi, Guizhou, Sichuan, Hunan, and Guangdong Provinces), coincident with known endemic areas. Furthermore, human infection risk maps were generated by integrating suitability distribution with socio-economic factors (HIV incidence, population density, GDP). High-risk hotspots stratified by HIV status confirmed core endemic zones for HIV-positive populations and identified broader risk areas for HIV-negative populations (e.g., parts of Guangdong, Jiangxi and Fujian Provinces). Projections under different climate change scenarios showed host suitability will decrease under low emissions (SSP126) but expand under high emissions (SSP585), indicating dynamic future TM/TSM risk patterns and disease administration dependent on emission conditions.

Collectively, these findings first revealed high-resolution predictive risk maps of TM/TSM in China and provided valuable reference for targeted public health interventions. The proposed methods in this study will also shed light on the prevention and administration of other “fungi - animal host - human” diseases in both current and emerging risk zones under climate change in the future.

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