Shanghai Institute of Infectious Disease and Biosecurity, Key Laboratory of Medical Molecular Virology (MOE/ NHC/CAMS), School of Basic Medical Science, Fudan University, Shanghai, People's Republic of China.
Institution for Tuberculosis Prevention and Control, Henan Provincial Center for Disease Control and Prevention, Zhengzhou, People's Republic of China.
Emerg Microbes Infect. 2024 Dec;13(1):2399273. doi: 10.1080/22221751.2024.2399273. Epub 2024 Sep 5.
The incidence of tuberculosis (TB) has declined more slowly in rural than urban areas in China, and data on the patterns of transmission and the high-risk populations in rural areas remains scarce. We conducted a population-based study of culture-positive pulmonary TB patients diagnosed in rural Linzhou City, Henan Province from July 2018 to February 2023. Genomic clusters were defined based on whole-genome sequencing and risk factors for clustering were identified by logistic regression. Transmission events were inferred with phybreak and transmission links were sought through epidemiological investigation of clustered patients. Logistic regression was used to explore the relationship between genomic differences of patient isolates and geographical distances of patient residences. Spatial hotspots were defined using kernel density estimation. Of 455 culture-positive patients, 430 were included in the final analysis. Overall, 192 (44.7%,192/430) patients were grouped into 49 clusters. Clusters containing ≥5 patients accounted for 18.4% (9/49) of the clusters and clustering was highest in student patients. No super-spreaders were detected. Confirmed epidemiologic links were identified for only 18.2% of clustered patients. The clustering risk decreased rapidly with increasing distances between patient residences, but 77.6% of clustered patient pairs lived ≥5.0 km apart. Both the Central Subdistrict and Rencun Township were identified as hotspots for TB transmission. Recent transmission appears to be an important driver of the TB burden in Linzhou. The formulation of effective strategies to reduce TB incidence in rural areas will require further studies to identify high-risk populations and venues where local inhabitants congregate and transmit the infection.
中国农村地区的结核病（TB）发病率下降速度较城市缓慢，农村地区的传播模式和高危人群数据仍然稀缺。我们对 2018 年 7 月至 2023 年 2 月在河南省林州市确诊的农村地区培养阳性肺结核患者进行了一项基于人群的研究。基于全基因组测序定义基因组聚类，通过逻辑回归确定聚类的危险因素。使用 phybreak 推断传播事件，并通过对聚类患者的流行病学调查寻找传播联系。使用逻辑回归探讨患者分离株基因组差异与患者居住地地理距离之间的关系。使用核密度估计定义空间热点。在 455 例培养阳性患者中，有 430 例纳入最终分析。总体而言，192 例（44.7%，192/430）患者分为 49 个聚类。包含≥5 例患者的聚类占 18.4%（9/49），聚类中以学生患者居多。未发现超级传播者。仅对 18.2%的聚类患者确定了明确的流行病学联系。聚类风险随患者居住地之间的距离增加而迅速下降，但 77.6%的聚类患者居住距离≥5.0 公里。中区和仁村乡均被确定为结核病传播的热点。近期传播似乎是林州结核病负担的重要驱动因素。制定有效策略降低农村地区结核病发病率，需要进一步研究以确定高危人群和当地居民聚集和传播感染的场所。
