Parasites & vectors · 2026
Non-linear effects and lag patterns of eco-environmental factors on scrub typhus: a spatiotemporal analysis in Yunnan, China, 2015-2022.
СтатьяНазвание и аннотация: Перевод в очереди
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Jing Xiangnan, Ling Yuewei, Jing Ruonan, Guo Fuying, Yin Feifei, Huang Dongsheng, Zhang Lijie, Yan Xiangyu, Shui Tiejun
Аннотация
BACKGROUND: Yunnan Province is characterized by a high incidence of scrub typhus and complex ecological environments, where epidemic patterns are shaped by the dual influence of the plateau monsoon system and geomorphological evolution. However, macro-scale meteorological indicators often fail to accurately capture climatic features within such rugged terrains, leaving the multi-factor coupled spatiotemporal associations of scrub typhus epidemics elusive.
METHODS: This study integrates Wavelet periodicity analysis and STL decomposition to identify the temporal rhythms and structural mutations of scrub typhus. Furthermore, GLM and Poisson-DLNM were employed to evaluate the independent contributions and non-linear lag risks of environmental factors.
RESULTS: Our findings indicate that scrub typhus in Yunnan Province exhibits steady-state seasonality characterized by a dominant 12-month cycle. The epidemic dynamics underwent a structural mutation around 2018, marking a transition into a high-intensity epidemic stage. In terms of environmental drivers, the Normalized Difference Water Index (NDWI) outperformed traditional precipitation indicators in risk explanatory power (aRR=1.93, 95% CI 1.84-2.04), suggesting that moisture accessibility in local micro-habitats is a critical variable for chigger survival. Furthermore, due to the saturation effect of the plateau biomass system, the Enhanced Vegetation Index (EVI) proved superior to the Normalized Difference Vegetation Index (NDVI) in characterizing habitats, with EVI showing a significant association (aRR = 0.75, 95% CI 0.72-0.78), while NDVI remained non-significant. Regarding human interference, habitat remodeling induced by urbanization has significantly intensified the human-rodent contact interface (aRR = 1.15, 95% CI 1.13-1.16). Finally, soil moisture exhibited the strongest cumulative risk effect (Cumulative RR = 2.23, 95% CI 1.86-2.67) characterized by a persistent long-term lag, and maintained a significant independent driving effect (aRR = 1.05, 95% CI 1.02-1.08).
CONCLUSIONS: This study elucidates that in regions with complex topography, the core drivers of scrub typhus epidemics are constituted by local geohydrological indicators and micro-environmental evolution instead of macro-meteorological factors. The findings underscore the importance of integrating high-resolution geodetic monitoring indicators into infectious disease early-warning systems. These results provide a robust scientific foundation for the identification of cross-border health security risks and the development of precision early-warning strategies.
METHODS: This study integrates Wavelet periodicity analysis and STL decomposition to identify the temporal rhythms and structural mutations of scrub typhus. Furthermore, GLM and Poisson-DLNM were employed to evaluate the independent contributions and non-linear lag risks of environmental factors.
RESULTS: Our findings indicate that scrub typhus in Yunnan Province exhibits steady-state seasonality characterized by a dominant 12-month cycle. The epidemic dynamics underwent a structural mutation around 2018, marking a transition into a high-intensity epidemic stage. In terms of environmental drivers, the Normalized Difference Water Index (NDWI) outperformed traditional precipitation indicators in risk explanatory power (aRR=1.93, 95% CI 1.84-2.04), suggesting that moisture accessibility in local micro-habitats is a critical variable for chigger survival. Furthermore, due to the saturation effect of the plateau biomass system, the Enhanced Vegetation Index (EVI) proved superior to the Normalized Difference Vegetation Index (NDVI) in characterizing habitats, with EVI showing a significant association (aRR = 0.75, 95% CI 0.72-0.78), while NDVI remained non-significant. Regarding human interference, habitat remodeling induced by urbanization has significantly intensified the human-rodent contact interface (aRR = 1.15, 95% CI 1.13-1.16). Finally, soil moisture exhibited the strongest cumulative risk effect (Cumulative RR = 2.23, 95% CI 1.86-2.67) characterized by a persistent long-term lag, and maintained a significant independent driving effect (aRR = 1.05, 95% CI 1.02-1.08).
CONCLUSIONS: This study elucidates that in regions with complex topography, the core drivers of scrub typhus epidemics are constituted by local geohydrological indicators and micro-environmental evolution instead of macro-meteorological factors. The findings underscore the importance of integrating high-resolution geodetic monitoring indicators into infectious disease early-warning systems. These results provide a robust scientific foundation for the identification of cross-border health security risks and the development of precision early-warning strategies.