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2011 - 2021年江苏省病原学阳性肺结核的时空分布特征

[Spatial-temporal distribution characteristics of etiologically positive pulmonary tuberculosis in Jiangsu Province from 2011 to 2021].

作者信息

Chen K, Yu H, Zhu L M, Liu Q, Wang B

机构信息

School of Public Health, Southeast University, Nanjing 210009, China.

Institute for Chronic Infectious Disease Prevention and Control, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China.

出版信息

Zhonghua Liu Xing Bing Xue Za Zhi. 2024 Apr 10;45(4):513-519. doi: 10.3760/cma.j.cn112338-20230915-00161.

Abstract

To analyze the spatial-temporal distribution of etiologically positive pulmonary tuberculosis (PTB) at the county (city, district) unit in Jiangsu Province from 2011 to 2021 to provide evidence for the implementation and adjustment of prevention and control strategies of PTB in Jiangsu Province. The registration data of etiologically positive PTB patients in Jiangsu Province from 2011 to 2021 were collected from the Tuberculosis Management Information System in the China Information System of Disease Control and Prevention. Data on the permanent population were from the statistical yearbook of each county (city, district) in Jiangsu Province. Geoda 1.18.0 software was used to analyze the global and local spatial autocorrelation and explore the spatial clustering. SaTScan 10.1 software was used to analyze the spatial-temporal clusters, and ArcGIS 10.7 software was used to visualize the spatial-temporal clusters. A total of 128 240 etiological positive PTB cases were registered in Jiangsu Province from 2011 to 2021, with an average annual registration rate of 13.99/100 000. The registration rate showed an overall upward trend (trend =63.49, <0.001) after 2017, and the etiologically positive rate showed an overall upward trend (trend =3 710.86, <0.001). The annual Moran's values ranged from 0.107 to 0.343, which showed a spatial clustering distribution. The results of local spatial autocorrelation analysis showed that there were "high-high" clustering areas in Jiangsu Province each year, showing a dynamic distribution, and most of the areas were distributed in the central and southern regions of Jiangsu Province, with the largest number (7) in 2015 and the smallest number (1) in 2011. A total of 4 spatial-temporal clustering areas were explored by spatial-temporal scanning analysis (all <0.001), among which the first-level clustering area covered 3 counties (cities, districts), namely Changshu, Taicang, and Xiangcheng District of Suzhou, and the clustering time was from 2011 to 2015. The secondary clustering areas covered 24 counties (cities, districts), mainly covering Jiangsu's central and northern regions, such as Huai'an, Suqian, and Yancheng. The third-level clustering areas covered 26 counties (cities, districts); the fourth-level clustering area was the Gaochun District of Nanjing, with the clustering period from 2017 to 2021. From 2011 to 2021, the etiologically positive PTB registration rate at the county (city, district) level in Jiangsu Province had obvious spatial-temporal clustering characteristics. The clustering areas included the northern areas with relatively backward economies and the southern areas with better economic development. Multiple measures should be taken to prevent and control PTB according to the specific situation in different regions.

摘要

分析2011—2021年江苏省县(市、区)级病原学阳性肺结核(PTB)的时空分布特征,为江苏省PTB防控策略的实施与调整提供依据。收集中国疾病预防控制信息系统中江苏省结核病管理信息系统2011—2021年病原学阳性PTB患者的登记数据,常住人口数据来自江苏省各县(市、区)统计年鉴。运用Geoda 1.18.0软件分析全局和局部空间自相关,探索空间聚集性;运用SaTScan 10.1软件分析时空聚集性,ArcGIS 10.7软件对时空聚集进行可视化。2011—2021年江苏省共登记病原学阳性PTB患者128 240例,年均登记率为13.99/10万。2017年后登记率呈总体上升趋势(趋势=63.49,P<0.001),病原学阳性率呈总体上升趋势(趋势=3 710.86,P<0.001)。年度Moran's I值范围为0.107~0.343,呈空间聚集分布。局部空间自相关分析结果显示,江苏省每年均存在“高高”聚集区,呈动态分布,主要分布在江苏省中南部地区,2015年最多(7个),2011年最少(1个)。时空扫描分析共探索出4个时空聚集区(均P<0.001),其中一级聚集区覆盖3个县(市、区),即苏州市常熟、太仓及相城区,聚集时间为2011—2015年;二级聚集区覆盖24个县(市、区),主要覆盖江苏省中北部地区,如淮安、宿迁、盐城等;三级聚集区覆盖26个县(市、区);四级聚集区为南京市高淳区,聚集期为2017—2021年。2011—2021年江苏省县(市、区)级病原学阳性PTB登记率具有明显的时空聚集特征,聚集区包括经济相对落后的北部地区和经济较发达的南部地区。应根据不同地区具体情况采取多种措施防控PTB。

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