Rao H X, Cai Z F, Xu L L, Shi Y
Institute for Communicable Disease Control and Prevention, Qinghai Provincial Center for Disease Control and Prevention, Xining 810007, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2018 Mar 10;39(3):347-351. doi: 10.3760/cma.j.issn.0254-6450.2018.03.019.
To analyze the spatial distribution of tuberculosis (TB) and identify the clustering areas in Qinghai province from 2014 to 2016, and provide evidence for the prevention and control of TB. The data of pulmonary TB cases confirmed by clinical and laboratory diagnosis in Qinghai during this period were collected from National Disease Reporting Information System. The visualization of annual reported incidence, three-dimensional trend analysis and local Getis-Ord () spatial autocorrelation analysis of TB were performed by using software ArcGIS 10.2.2, and global Moran's spatial autocorrelation analysis were analyzed by using software OpenGeoDa 1.2.0 to describe and analyze the spatial distribution characteristics and high incidence areas of TB in Qinghai from 2014 to 2016. A total of 20 609 pulmonary TB cases were reported in Qinghai during this period. The reported incidences were 101.16/100 000, 123.26/100 000 and 128.70/100 000 respectively, an increasing trend with year was observed (trend (2)=187.21, <0.001). The three-dimensional trend analysis showed that the TB incidence increased from northern area to southern area, and up-arch trend from the east to the west. Global Moran's spatial autocorrelation analysis showed that annual reported TB incidence in different areas had moderate spatial clustering (Moran's values were 0.631 3, 0.605 4, and 0.587 3, <0.001). And local () analysis showed that there were some areas with high TB incidences, such as 10 counties of Yushu and Guoluo prefectures (Gande, Banma and Dari counties, . located in the southwest of Qinghai), and some areas with low TB incidences, such as Huangzhong county, Chengdong district and Chengbei district of Xining city and Dachaidan county of Haixi prefecture, and the reported TB incidences in the remaining areas were moderate. The annual reported TB incidence increased year by year in Qinghai from 2014 to 2016. The distribution of TB cases showed obvious spatial clustering, and Yushu and Guoluo prefectures were the key areas in TB prevention and control. In addition, the spatial clustering analysis could provide the important evidence for the development of TB prevention and control measures in Qinghai.
分析2014年至2016年青海省结核病(TB)的空间分布,识别聚集区域,为结核病防控提供依据。收集此期间青海省临床和实验室确诊的肺结核病例数据,来源于国家疾病报告信息系统。利用ArcGIS 10.2.2软件对结核病年度报告发病率进行可视化、三维趋势分析和局部Getis-Ord()空间自相关分析,利用OpenGeoDa 1.2.0软件进行全局Moran's空间自相关分析,以描述和分析2014年至2016年青海省结核病的空间分布特征和高发病区。此期间青海省共报告20609例肺结核病例。报告发病率分别为101.16/10万、123.26/10万和128.70/10万,呈逐年上升趋势(趋势(2)=187.21,P<0.001)。三维趋势分析显示,结核病发病率从北部地区向南部地区升高,从东部到西部呈拱形上升趋势。全局Moran's空间自相关分析显示,不同地区年度报告的结核病发病率存在中度空间聚集(Moran's I值分别为0.631 3、0.605 4和0.587 3,P<0.001)。局部()分析显示,有一些结核病高发病区,如玉树州和果洛州的10个县(甘德县、班玛县和达日县等,位于青海西南部),还有一些低发病区,如西宁市湟中县、城东区和城北区以及海西州大柴旦县,其余地区报告的结核病发病率为中度。2014年至2016年青海省年度报告的结核病发病率逐年上升。结核病病例分布呈现明显的空间聚集性,玉树州和果洛州是结核病防控的重点地区。此外,空间聚集性分析可为青海省结核病防控措施的制定提供重要依据。