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Background <p>Scrub typhus is transmitted through vectors and is susceptible to meteorological factors, posing a significant threat to human life and health. Therefore, in this study, the nonlinear relationships between meteorological factors and scrub typhus (ST) and the lag effects of meteorological factors on ST were analyzed, and the explanatory power of these factors on the spatially stratified heterogeneity of ST was evaluated.</p> Methods <p>Monthly data on ST cases and meteorological factors were collected in Jiangxi from 2014 to 2023. A distributed lag nonlinear model (DLNM) was used to analyze the lag effects and nonlinear relationships between meteorological factors and ST. Geodetector was conducted using 2023 spatial data to evaluate the explanatory power of meteorological factors and their interactions on the spatially stratified heterogeneity of ST.</p> Results <p>A total of 9129 cases of newly diagnosed ST were recorded. The DLNM demonstrated nonlinear relationships between meteorological factors and ST and lag effects of meteorological factors on ST. The influence of temperature, relative humidity, and wind speed on the ST initially increased, peaking at 25.50&#xa0;°C, 84.80%, and 2.00&#xa0;m/s, respectively, before decreasing. Precipitation was associated with an increasing risk of ST, whereas pressure tended to decrease risk. Compared with median meteorological values, extreme conditions (such as extremely low temperature, extremely low relative humidity, extremely high pressure, and extremely high wind speed) had a protective effect on the incidence of ST. Conversely, extremely high precipitation and extremely low pressure were associated with an elevated risk of ST. Geodetector analysis revealed the following explanatory power for the spatially stratified heterogeneity of ST: temperature (0.357) &gt; relative humidity (0.351) &gt; pressure (0.275) &gt; precipitation (0.225) &gt; wind speed (0.223). Temperature and relative humidity emerged as the most critical indicators affecting ST. Furthermore, the incidence of ST was driven by the combined effects of multiple meteorological factors.</p> Conclusions <p>The incidence of ST in Jiangxi Province is significantly influenced by meteorological factors, with both lag effects and nonlinear relationships. Temperature and relative humidity are the key indicators affecting ST. The consideration of meteorological factors is essential for the prevention and control of ST.</p>

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Influence of meteorological factors on scrub typhus in Southeast China: a study across 100 districts in Jiangxi Province

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月7日

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  • Yanwu Nie,
  • Yisheng Zhou,
  • Shu Yang,
  • Xiaobo Liu,
  • Yibing Fan,
  • Qinhan Jiang,
  • Yong Liu,
  • Yangqing Liu,
  • Daiwei Zhang,
  • Yuanan Lu,
  • Hui Li,
  • Lei Wu

摘要

Background

Scrub typhus is transmitted through vectors and is susceptible to meteorological factors, posing a significant threat to human life and health. Therefore, in this study, the nonlinear relationships between meteorological factors and scrub typhus (ST) and the lag effects of meteorological factors on ST were analyzed, and the explanatory power of these factors on the spatially stratified heterogeneity of ST was evaluated.

Methods

Monthly data on ST cases and meteorological factors were collected in Jiangxi from 2014 to 2023. A distributed lag nonlinear model (DLNM) was used to analyze the lag effects and nonlinear relationships between meteorological factors and ST. Geodetector was conducted using 2023 spatial data to evaluate the explanatory power of meteorological factors and their interactions on the spatially stratified heterogeneity of ST.

Results

A total of 9129 cases of newly diagnosed ST were recorded. The DLNM demonstrated nonlinear relationships between meteorological factors and ST and lag effects of meteorological factors on ST. The influence of temperature, relative humidity, and wind speed on the ST initially increased, peaking at 25.50 °C, 84.80%, and 2.00 m/s, respectively, before decreasing. Precipitation was associated with an increasing risk of ST, whereas pressure tended to decrease risk. Compared with median meteorological values, extreme conditions (such as extremely low temperature, extremely low relative humidity, extremely high pressure, and extremely high wind speed) had a protective effect on the incidence of ST. Conversely, extremely high precipitation and extremely low pressure were associated with an elevated risk of ST. Geodetector analysis revealed the following explanatory power for the spatially stratified heterogeneity of ST: temperature (0.357) > relative humidity (0.351) > pressure (0.275) > precipitation (0.225) > wind speed (0.223). Temperature and relative humidity emerged as the most critical indicators affecting ST. Furthermore, the incidence of ST was driven by the combined effects of multiple meteorological factors.

Conclusions

The incidence of ST in Jiangxi Province is significantly influenced by meteorological factors, with both lag effects and nonlinear relationships. Temperature and relative humidity are the key indicators affecting ST. The consideration of meteorological factors is essential for the prevention and control of ST.