Hong Chuangyue, Ge Jinjin, Gui Jing, Che Xiaoling, Li Yilin, Zhuo Zhipeng, Li Mingzhen, Wang Feng, Tan Weiguo, Zhao Zhiguang
Department of Tuberculosis Prevention and Control, Shenzhen Center for Chronic Disease Control; Shenzhen Institute of Pulmonology, Shenzhen, 518020, People's Republic of China.
National Clinical Research Center for Infectious Diseases, Shenzhen Clinical Research Center for Tuberculosis, Shenzhen Third People's Hospital, Shenzhen, 518112, People's Republic of China.
Infect Drug Resist. 2025 Mar 19;18:1551-1560. doi: 10.2147/IDR.S516162. eCollection 2025.
This study aims to elucidate the transmission dynamics of tuberculosis in a Chinese city with high population mobility and to identify the associated risk factors.
We included the data from ten city-level surveillance sites in Shenzhen between 2018 and 2023. Genomic clusters were defined as having a genomic distance of 12 single nucleotide polymorphisms based on whole-genome sequencing. Cross-district clusters were characterized as clusters containing patients from at least two districts, indicating cross-district transmission. Risk factors for clustering were identified using logistic regression.
Of the 2,519 enrolled patients, 263 (10.4%) were grouped into 119 genomic clusters. Notably, 52.1% (62/119) of these clusters were cross-district clusters. We analyzed the data from Shenzhen's 10 districts separately and compared the results with a citywide combined analysis, finding that the combined analysis revealed significantly higher clustering rates across all districts (P<0.001). Furthermore, the risk of cross-district transmission was 3.41 times higher (95% CI: 1.49-7.80) among internal migrants than among residents. Multivariable logistic regression analysis identified significant risk factors for TB transmission, including age under 25 years (OR=3.07, 95% CI: 1.17-8.03), age 25-44 years (OR=2.86, 95% CI: 1.13-7.23), and drug-resistant TB (OR=1.57, 95% CI: 1.15-2.13).
Cross-district transmission is a key factor in the spread of tuberculosis in cities with high population mobility. TB control institutions at all levels must transcend regional boundaries and enhance collaboration to achieve more effective tuberculosis control.
本研究旨在阐明在中国一个人口流动性高的城市中结核病的传播动态，并确定相关风险因素。
我们纳入了2018年至2023年深圳十个市级监测点的数据。基于全基因组测序，基因组聚类被定义为基因组距离为12个单核苷酸多态性。跨区聚类的特征是包含来自至少两个区的患者，表明存在跨区传播。使用逻辑回归确定聚类的风险因素。
在2519名登记患者中，263名（10.4%）被归入119个基因组聚类。值得注意的是，这些聚类中有52.1%（62/119）是跨区聚类。我们分别分析了深圳10个区的数据，并将结果与全市综合分析进行比较，发现综合分析显示所有区的聚类率显著更高（P<0.001）。此外，流动人口中跨区传播的风险比常住人口高3.41倍（95%置信区间：1.49-7.80）。多变量逻辑回归分析确定了结核病传播的重要风险因素，包括25岁以下（比值比=3.07，95%置信区间：1.17-8.03）、25-44岁（比值比=2.86，95%置信区间：1.13-7.23）以及耐药结核病（比值比=1.57，95%置信区间：1.15-2.13）。
跨区传播是人口流动性高的城市中结核病传播的关键因素。各级结核病防控机构必须打破区域界限，加强合作，以实现更有效的结核病防控。
