Wang Y S, Wang J M, Wang W B
Department of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2020 Apr 10;41(4):526-531. doi: 10.3760/cma.j.cn112338-20190614-00441.
To analyze the spatial distribution pattern and the cluster spots of tuberculosis (TB) patients in China from 2004 to 2016, so as to provide evidence for prevention and control of the disease. Using ArcGIS 10.0 software as a platform for data management and presentation, a TB spatial analysis database from 2004 to 2016 was established, and spatial autocorrelation analysis was performed based on the TB epidemics. SaTScan 9.6 software was used for spatiotemporal scanning analysis. From 2004 to 2016, a total of 13 157 794 cases of pulmonary tuberculosis were registered in China, with the mean annual registered incidence rate as 75.90/100 000 (range: 27.95/100 000-180.82/100 000). Through Global spatial autocorrelation studies, the results showed that the distribution of TB incidence was somehow clustered. The result of local Moran's autocorrelation analysis showed that Xinjiang, Tibet, Guizhou, Guangxi, Hainan provinces were high-high cluster areas, and Beijing, Hebei, Tianjin, Shandong, Jiangsu, and Shanghai provinces were low-low cluster areas. Result from the Getis-Ord General spatial autocorrelation analysis showed the existence of fifteen "hot spot" regions, of which three "positive hot spots" were Xinjiang, Tibet, and Hainan provinces, and twelve "negative hot spots" were Beijing, Tianjin, Liaoning, Inner Mongolia, Hebei, Shandong, Jiangsu, Anhui, Shanghai, Shanxi, Henan, Jilin provinces. Using the SaTScan 9.6 software, results from the Phased spatial-temporal analysis identified twelve cluster areas, with statistical significances (<0.05) among them. From 2004 to 2016, tuberculosis epidemics showed an annual downward trend in China. The average annual rates of notification among provinces were not randomly distributed, showing the existence of obvious spatial aggregation. Numbers of areas with clustering nature that noticed through the temporal and spatial scanning technics had gradually decreased. At the same time, progress had been made in TB control programs, despite the existence of high-risk areas. Development of more strict and targeted prevention and control measures are called for.
分析2004年至2016年中国结核病患者的空间分布格局和聚集点,为该病的防控提供依据。以ArcGIS 10.0软件作为数据管理和展示平台,建立2004年至2016年结核病空间分析数据库,并基于结核病流行情况进行空间自相关分析。使用SaTScan 9.6软件进行时空扫描分析。2004年至2016年,中国共登记肺结核病例13157794例,年均登记发病率为75.90/10万(范围:27.95/10万 - 180.82/10万)。通过全局空间自相关研究,结果表明结核病发病率分布呈一定程度的聚集性。局部Moran自相关分析结果显示,新疆、西藏、贵州、广西、海南省为高高聚集区,北京、河北、天津、山东、江苏、上海市为低低聚集区。Getis-Ord全局空间自相关分析结果显示存在15个“热点”区域,其中新疆、西藏和海南省为3个“正热点”,北京、天津、辽宁、内蒙古、河北、山东、江苏、安徽、上海、山西、河南、吉林省为12个“负热点”。使用SaTScan 9.6软件,阶段性时空分析结果确定了12个聚集区,其中具有统计学意义(<0.05)。2004年至2016年,中国结核病疫情呈逐年下降趋势。各省年均报告率并非随机分布,存在明显的空间聚集性。通过时空扫描技术发现的具有聚集性质的区域数量逐渐减少。同时,尽管存在高危地区,但结核病防控工作取得了进展。需要制定更严格、更有针对性的防控措施。