Spatiotemporal analysis of plague risk in Tibet: Multi-source data-driven ensemble model development and validation.

Area of Science:

• Epidemiology
• Environmental Science
• Spatial Analysis

Background:

• Plague, caused by *Yersinia pestis*, is a significant public health concern.
• Tibet's unique alpine environment presents understudied plague dynamics.
• Understanding plague foci drivers is crucial for public health in the region.

Purpose of the Study:

• To reveal environmental drivers of plague foci in Tibet.
• To analyze the spatiotemporal evolution of plague distribution.
• To provide a scientific basis for plague prevention in Tibet.

Main Methods:

• Integrated Tibet plague surveillance data (2000-2021) with eight environmental variables.
• Employed ten algorithms via BIOMOD2 to model plague risk across four distinct phases.
• Validated models using 2022-2023 data and analyzed risk distribution, area, and centroid changes.

Main Results:

• Ensemble model demonstrated excellent predictive accuracy (AUC > 0.98, TSS > 0.92).
• Key drivers identified: population, precipitation, maximum temperature, and NDVI.
• Plague foci exhibited stage-wise centroid migration, influenced by human activities and climate variations.

Conclusions:

• Multi-model integration elucidated plague foci distribution and centroid evolution in Tibet.
• The study captured significant human-climate impacts on plague dynamics.
• Findings provide a scientific foundation for targeted plague prevention in high-risk zones.