Wang Xin, Guo Jianhua, Shi Xiaojing, Cui Lihua
School of Public Health, North China University of Science and Technology, Tangshan, China.
Department of Tuberculosis Control and Prevention, Shijiazhuang Center for Disease Control and Prevention, Shijiazhuang, China.
Front Public Health. 2025 Jul 3;13:1621695. doi: 10.3389/fpubh.2025.1621695. eCollection 2025.
Spatio-temporal analysis is a key epidemiological tool for monitoring disease transmission and identifying outbreak hotspots. However, the patterns of pulmonary tuberculosis (PTB) spread over time and space in Shijiazhuang remain poorly understood. This study aims to clarify the spatio-temporal dynamics of PTB transmission in this region.
We conducted a retrospective study using PTB surveillance data from 2010 to 2023, extracted from the national Tuberculosis Information Management System. Descriptive epidemiological analysis was conducted to assess the severity and distribution characteristics of PTB in Shijiazhuang. The Joinpoint regression model was employed to analyze the annual temporal trends. Spatial autocorrelation analysis and Space-time scan analysis were utilized to explore the spatio-temporal clustering characteristics.
From 2010 to 2023, a total of 54,855 PTB cases were reported, with an average annual incidence of 38.97 per 100,000 population. Males, older adults, and farmers were disproportionately affected. The overall incidence declined significantly (AAPC = -7.65%, < 0.05), with a steeper drop between 2010 to 2013 and a more gradual decline thereafter. Spatial analysis revealed persistent high-high clusters in rural counties such as Lingshou county and Pingshan county, and low-low clusters in central urban districts. The phased space-time scan analysis results identified 19 clusters.
This study reveals a declining PTB incidence in Shijiazhuang, with a higher burden among males, older adults, and farmers, alongside persistent spatial clusters in rural areas, particularly in the north. These findings emphasize the need for targeted interventions and strengthened rural surveillance to achieve tuberculosis elimination goals.
时空分析是监测疾病传播和识别疫情热点的关键流行病学工具。然而，石家庄市肺结核（PTB）在时间和空间上的传播模式仍知之甚少。本研究旨在阐明该地区PTB传播的时空动态。
我们利用从国家结核病信息管理系统中提取的2010年至2023年的PTB监测数据进行了一项回顾性研究。进行描述性流行病学分析以评估石家庄市PTB的严重程度和分布特征。采用Joinpoint回归模型分析年度时间趋势。利用空间自相关分析和时空扫描分析来探索时空聚集特征。
2010年至2023年，共报告54855例PTB病例，平均年发病率为每10万人38.97例。男性、老年人和农民受影响的比例过高。总体发病率显著下降（AAPC = -7.65%，<0.05），2010年至2013年下降幅度较大，此后下降较为平缓。空间分析显示，灵寿县和平山县等农村县存在持续的高高聚集区，中心城区存在低低聚集区。分阶段时空扫描分析结果确定了19个聚集区。
本研究揭示了石家庄市PTB发病率的下降，男性、老年人和农民的负担较重，同时农村地区，特别是北部地区存在持续的空间聚集。这些发现强调了需要采取有针对性的干预措施并加强农村监测，以实现结核病消除目标。
