Huang Shumei, Tian Yao, Yan Meiying, Lv Chen-Long, Fang Li-Qun, Kan Biao
State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
Front Public Health. 2025 Apr 9;13:1550904. doi: 10.3389/fpubh.2025.1550904. eCollection 2025.
Enteric fever primarily affects the southwestern and central regions of China. Although the overall incidence rate has declined, certain areas have seen an increase in cases, necessitating further investigation into their geographic distribution, clustering areas, and potential influencing factors.
City-level data from 2001 to 2020 were analyzed. Spatial clustering was identified, and wavelet transform analysis explored periodic and seasonal characteristics. Determinants were identified using generalized estimating equation and distributed lag non-linear model.
Incidence declined from 2001 to 2008 but leveled off since 2009, shifting eastward. Two clustering areas were identified: Guangxi-Guizhou-Yunnan and Zhejiang. In the Zhejiang, incidence was negatively correlated with GDP per capita and popularization rate of safe drinking water in rural areas. Temperature and relative humidity had delayed effects on incidence in Zhejiang, showing linear or parabolic patterns. In the Guangxi-Guizhou-Yunnan, incidence was positively correlated with the proportion of water bodies. Temperature and relative humidity had delayed effects on incidence in Guangxi-Guizhou-Yunnan, and these effects exhibited fluctuating patterns.
Over the past 20 years, enteric fever incidence in China has shown a rapid early decline but has stabilized more recently. The factors influencing enteric fever prevalence vary between clustering areas, indicating the need for region-specific measures.
伤寒主要影响中国西南部和中部地区。尽管总体发病率有所下降，但某些地区的病例数有所增加，因此有必要进一步调查其地理分布、聚集区以及潜在影响因素。
分析了2001年至2020年的市级数据。确定了空间聚集情况，并通过小波变换分析探索了周期性和季节性特征。使用广义估计方程和分布滞后非线性模型确定了决定因素。
发病率在2001年至2008年期间下降，但自2009年以来趋于平稳，并向东转移。确定了两个聚集区：广西-贵州-云南和浙江。在浙江，发病率与人均国内生产总值和农村安全饮用水普及率呈负相关。温度和相对湿度对浙江的发病率有延迟影响，呈线性或抛物线模式。在广西-贵州-云南，发病率与水体比例呈正相关。温度和相对湿度对广西-贵州-云南的发病率有延迟影响，且这些影响呈现出波动模式。
在过去20年中，中国伤寒发病率早期迅速下降，但最近趋于稳定。影响伤寒流行的因素在不同聚集区有所不同，这表明需要采取针对特定区域的措施。
