2013—2017年上海市金山区新登记肺结核患者时空聚集性分析

目的分析2013—2017年上海市金山区活动性肺结核疫情的时空分布特征,探寻肺结核疫情防治重点区域。方法通过国家《结核病管理信息系统》收集金山区肺结核患者基本信息,以街镇为单位(共计11个),用SaTScan 9.6软件对上海市金山区2013—2017年新登记肺结核患者登记率进行时空分析,通过ArcGIS 10.4软件对结果进行可视化呈现。结果金山区2013—2017年新登记活动性肺结核患者1021例,年均登记率为25.64/10万(1021/3981892),其中户籍人口和非户籍人口肺结核患者年均登记率分别为28.68/10万(757/2639117)和19.66/10万(264/1342775)。空间分布上总体肺结核患者登记率最高的街镇在张堰镇,户籍人口登记的肺结核患者主要分布在张堰镇、漕泾镇、金山工业区;非户籍人口主要分布在廊下镇和石化街道。单纯时间扫描结果显示,总体与户籍人口登记肺结核患者的聚集时间均为2014—2015年;单纯空间扫描结果显示,总体登记肺结核患者的聚集区为张堰镇,而户籍人口聚集区为金山区东北部四街镇(亭林镇、漕泾镇、张堰镇和工业区);时空扫描显示,金山区总体人口相对风险值(RR)=1.50,对数似然比(LLR)=10.35,P<0.01]和户籍人口(RR=1.72,LLR=13.29,P<0.01)肺结核一级聚集区均在2014—2015年出现,聚集区域均为亭林镇、漕泾镇、张堰镇、工业区。结论金山区肺结核发病具有一定的时空聚集性,聚集性主要受户籍人口影响,东北部四街镇为金山区肺结核高发区域。

Spatial-temporal analysis on newly registered tuberculosis patients in Jinshan District,Shanghai from 2013 to 2017

Objective To analyze the spatial-temporal distribution characteristics of active pulmonary tuberculosis (PTB) in Jinshan District, Shanghai from 2013 to 2017, and to explore the critical regions of TB prevention and control. Methods The basic information of TB patients was collected from the Tuberculosis Management Information System. SaTScan 9.6 software was used to analyze the space-time clusters of the TB patient registration rate at the town level, and the spatial-temporal clusters areas were displayed by ArcGIS 10.4. Results A total of 1021 new active PTB cases were registered during 2013-2017, and the annual PTB registration rates for the whole, for the household registered population and the non-household registered population were 25.64/100000 (1021/3981892), 28.68/100000 (757/2639117) and 19.66/100000 (264/1342775) respectively. In terms of spatial distribution, the town with the highest registration rates were Zhangyan for the whole, and Zhangyan, Caojing and Jinshan Industrial Zone for the household registered population and Langxia and Shihua Street for the non-household registered population. Temporal scan showed that the aggregation time was both 2014-2015 for the whole and the household registered population. Spatial cluster was located in Zhangyan for the whole. Spatial clusters for household registered population were located in the four towns in the northeast of Jinshan District (Tinglin, Caojing, Zhangyan and Jinshan Industrial Zone). The spatial-temporal scan indicated the primary clusters of PTB in Jinshan District (relative risk (RR)=1.5, log-likelihood ratio (LRR)=10.35, P<0.01) and household registered population (RR=1.72, LRR=13.29, P<0.01) were both clustered in Tinglin, Caojing, Zhangyan and Jinshan Industrial Zone during 2014-2015. Conclusion Incidence of PTB displayed certain spatial-temporal clustering in Jinshan District, which is mainly affected by the household registered population, with high risk areas relatively concentrated in the four towns in the northeast of Jinshan District.