Evidence map›Paper›PMID 41204392›Full record

ArticleTropical medicine and health2025

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

Yanwu Nie, Yisheng Zhou, Shu Yang, Xiaobo Liu, Yibing Fan, Qinhan Jiang, Yong Liu, Yangqing Liu, Daiwei Zhang, Yuanan Lu and 2 more

Abstract read
In one paragraph

Article in Tropical medicine and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Yanwu Nie *Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330006, China.
Yisheng Zhou *Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330006, China.
Shu Yang *Jiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330006, China.
Xiaobo LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, 102206, China.
Yibing FanJiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330006, China.
Qinhan JiangSchool of Public Health, Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China.
Yong LiuSchool of Public Health, Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China.
Yangqing LiuJiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330006, China.
Daiwei ZhangJiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330006, China.
Yuanan LuSchool of Public Health, Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China.
Hui LiJiangxi Provincial Health Commission Key Laboratory of Pathogenic Diagnosis and Genomics of Emerging Infectious Diseases, Nanchang Center for Disease Control and Prevention, Nanchang, 330006, China. nccdcyjb@163.com.
Lei WuSchool of Public Health, Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Jiangxi Medical College, Nanchang University, Nanchang, 330006, China. leiwu@ncu.edu.cn.

Funding

Jiangxi Provincial Postgraduate Innovation Special 2024 Grant YC2024 - B054Science and Technology Bureau of Nanchang City, China 2020133-18
6 · The paper itself

Abstract

backgroundScrub 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.

methodsMonthly 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.

resultsA 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.

conclusionsThe 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.

Indexed as

DLNMGeodetectorMeteorological factorsScrub typhus

Identifiers

PMID41204392
PMCPMC12595867

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.