[Temporal-spatial distribution of tuberculosis in China, 2004-2016].
[Temporal-spatial distribution of tuberculosis in China, 2004-2016].
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DOI：
10.3760/cma.j.cn112338-20190614-00441
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发表时间：
2020-04-10
影响因子：
--
通讯作者：
Wang, W B
中科院分区：
文献类型：
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作者：
Wang, Y S;Wang, J M;Wang, W B
目的：分析2004年至2016年中国地区结核病患者的空间分布格局和聚集点，为结核病的防治提供依据。方法：以ArcGIS10.0软件为数据管理和展示平台，建立2004~2016年结核病空间分析数据库，根据结核病流行情况进行空间自相关分析。采用SATScan 9.6软件进行时空扫描分析。结果：2004年至2016年，中国共登记肺结核13157794例，年均登记发病率为75.90/10万(范围：27.95/10万~180.82/10万)。通过全球空间自相关研究，结果表明结核病发病率的分布具有某种程度的聚集性。当地Moran‘s I自相关分析结果表明，新疆、西藏、贵州、广西、海南为高-高聚集区，北京、河北、天津、山东、江苏、上海为低-低聚集区。Getis-Ord一般G空间自相关分析结果表明，存在15个“热点”区域，其中3个“正热点”是新疆、西藏和海南，12个“负热点”是北京、天津、辽宁、内蒙古、河北、山东、江苏、安徽、上海、山西、河南和吉林。利用SATScan 9.6软件进行分阶段的时空分析，共划分出12个聚集区，具有统计学意义(P
Objective: 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. Methods: 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. Results: 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 I 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 G 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 (P