Li K K, Dang L H, Zhang H W, He Z Q
Shaanxi Provincial Center for Disease Control and Prevention, Xi'an 710054, China.
Shaanxi Provincial Health Education Center, Xi'an 710016, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2025 Jul 10;46(7):1180-1187. doi: 10.3760/cma.j.cn112338-20250126-00064.
To understand the spatiotemporal distribution of pulmonary tuberculosis (TB) in Shaanxi Province from 2015 to 2023, and provide reference for the prevention and control of pulmonary TB in Shaanxi. The registration data of etiologically positive pulmonary TB cases in Shaanxi from 2015 to 2023 were collected from the tuberculosis subsystem of Chinese Disease Control and Prevention Information System. Descriptive method was used to analyze the basic characteristics of the etiologically positive pulmonary TB cases. Linear trend test was used to analyze trends in registration rate and pathogen positive rate. Software SPSS 25.0 was used for statistical analysis. Software ArcGIS 10.8 was used for global spatial autocorrelation and hotspot analysis to explore spatial clustering of the etiologically positive pulmonary TB cases. Software SaTScan 10.0 was used for spatiotemporal scan statistics, and software ArcGIS 10.8 was used to visualize the spatiotemporal clustering. A total of 64 148 cases of etiologically positive pulmonary TB were registered in Shaanxi from 2015 to 2023, with an average annual registration rate of 18.33/100 000. The registration rate and pathgen positive rate all showed upward trends from 2015 to 2023, and the differences were significant (the trend =4 555.18 and 19 330.43, both <0.001). Global spatial autocorrelation and hotspot analysis showed that the registration rate of etiologically positive pulmonary TB in Shaanxi from 2017 to 2023 showed a spatial clustering. The hotspots were mainly in Zhenba and Xixiang counties of Hanzhong, six counties (districts) of Ankang, and Yanchuan and Yanchang counties of Yan'an. The coldspots were mainly in parts of the Guanzhong area, including Baoji, Xi'an, and Xianyang. A total of 4 spatiotemporal clustering areas were explored by spatiotemporal scanning analysis (all <0.001), in which the first-level clustering areas covered 17 counties (districts), mainly Zhenping, Ziyang, Zhenba, in southern Shaanxi from 2019 to 2022, the second-level clustering areas covered 6 counties (districts), mainly Yanchuan, Yanchang, Qingjian, in northern Shaanxi from 2018 to 2021, the third-level clustering areas covered 14 counties (districts), mainly Yanta, Chang'an, Jingyang, in Guanzhong area from 2018 to 2019, and the fourth-level clustering areas covered 10 counties (districts) from 2019 to 2021. The registration rate of labortory confirmed pulmonary TB cases in Shaanxi showed an upward trend, with obvious differences in spatiotemporal clustering distribution. The clustering areas were mainly in southern Shaanxi, such as Zhenba, Zhenping, Hanbin, Langao, Pingli, Xunyang, Ziyang counties, and northern Shaanxi, such as Yanchuan and Yanchang counties, as well as in capital city, Xi'an and the adjacent Guanzhong area. It is necessary to develope targeted measures according to local conditions for the improvement of pulmonary TB prevention and control strategies in Shaanxi.
了解2015年至2023年陕西省肺结核(TB)的时空分布情况,为陕西省肺结核的防控工作提供参考。收集中国疾病预防控制信息系统结核病子系统中2015年至2023年陕西省病原学阳性肺结核病例的登记数据。采用描述性方法分析病原学阳性肺结核病例的基本特征。运用线性趋势检验分析登记率和病原学阳性率的变化趋势。使用SPSS 25.0软件进行统计分析。运用ArcGIS 10.8软件进行全局空间自相关和热点分析,以探究病原学阳性肺结核病例的空间聚集情况。使用SaTScan 10.0软件进行时空扫描统计,并运用ArcGIS 10.8软件对时空聚集情况进行可视化展示。2015年至2023年陕西省共登记病原学阳性肺结核病例64148例,年均登记率为18.33/10万。2015年至2023年登记率和病原学阳性率均呈上升趋势,差异有统计学意义(趋势=4555.18和19330.43,均<0.001)。全局空间自相关和热点分析显示,2017年至2023年陕西省病原学阳性肺结核病例登记率呈现空间聚集性。热点地区主要位于汉中的镇巴县和西乡县、安康的6个县(区)以及延安的延川县和延长县。冷点地区主要位于关中地区的部分地方,包括宝鸡、西安和咸阳。通过时空扫描分析共探索出4个时空聚集区域(均<0.001),其中一级聚集区域覆盖17个县(区),主要为2019年至2022年陕南的镇坪县、紫阳县、镇巴县;二级聚集区域覆盖6个县(区),主要为2018年至2021年陕北的延川县、延长县、清涧县;三级聚集区域覆盖14个县(区),主要为2018年至2019年关中地区的雁塔区、长安区、泾阳县;四级聚集区域覆盖10个县(区),时间跨度为2019年至2021年。陕西省实验室确诊肺结核病例的登记率呈上升趋势,时空聚集分布差异明显。聚集区域主要在陕南,如镇巴县、镇坪县、汉滨区、岚皋县、平利县、旬阳县、紫阳县,陕北的延川县和延长县,以及省会城市西安和相邻的关中地区。有必要因地制宜制定针对性措施,以完善陕西省肺结核防控策略。