Long-Term Evidence of ENSO-Driven Rodent Population Dynamics in a Natural Plague Focus of Southwestern China.

Climate variability can modulate zoonotic disease risk by altering interactions among wildlife hosts, vectors, and human environments, yet long-term evidence linking large-scale climate oscillations to natural plague systems remains scarce. We investigated the influence of El Niño-Southern Oscillation (ENSO)-related climate variability on rodent host dynamics in a long-established plague focus in Jianchuan County, southwestern China. Using continuous monthly surveillance data from 1978 to 2025, we analyzed population dynamics of two ecologically distinct plague hosts-the wild rodent Apodemus chevrieri and the domestic rodent Rattus tanezumi-together with flea infection rates and local climate variables. Generalized additive models showed that ENSO, quantified by the Southern Oscillation Index (SOI), exerted significant delayed effects on both rodent populations, with El Niño conditions consistently associated with increased host abundance. Wavelet coherence analyses revealed synchronized ENSO-rodent oscillations at dominant 2-3-year periodicities, indicating persistent large-scale climate forcing. In contrast, responses to local environmental factors differed between species: surface temperature strongly constrained the wild rodent A. chevrieri, whereas the domestic R. tanezumi showed weaker thermal sensitivity, consistent with buffering by human-modified indoor habitats. Flea infection rates declined as rodent densities increased, suggesting a dilution effect within the host-vector system. By integrating long-term wildlife surveillance, climate indicators, and vector data, this study provides empirical evidence that ENSO-driven climate variability plays a central role in regulating plague source activity at the human-animal-environment interface. These findings highlight the value of climate-informed, ecology-based surveillance frameworks for anticipating periods of elevated plague risk and strengthening early warning systems in endemic regions.