摘要
目的在街道／乡镇水平上分析2005-2015年北京市肺结核发病的时空流行特征。方法从结核病管理信息系统收集2005-2015年北京市肺结核发病数据，以地理信息系统和空间分析为基础，在街道／乡镇水平上采用全局空间自相关和局部空间自相关统计量（Moran’s I）分析肺结核发病的空间聚集性，采用时空扫描统计分析时空聚集性。结果在街道／乡镇水平上，北京市各年肺结核发病整体上呈现空间自相关性（Moran’s I值均〉0，均P〈0．05），高一高发病聚集区为门头沟区的军庄镇、王平办事处、永定镇、潭柘寺镇，房山区的阎村镇，丰台区的王佐镇，西城区的天桥街道和顺义区的天竺镇8个街道／乡镇。时空扫描统计结果显示，一级聚集区主要分布在朝阳区和顺义区，覆盖17个街道／乡镇，分别为朝阳区的崔各庄、麦子店、东风、太阳宫、左家庄、和平街、小关、香河园、东坝、将台、望京、金盏、酒仙桥、来广营、孙河和顺义区的后沙峪、天竺等街道／乡镇；聚集时间为2005年1—12月。结论2005-2015年北京市肺结核发病在街道／乡镇水平上呈现空间聚集性，且发病热点地区主要集中在中南部地区。
Objective To analyze the spatial distribution and identify the high risk areas of pulmonary tuberculosis at the township level in Beijing during 2005-2015. Methods Data on pulmonary tuberculosis cases was collected from the tuberculosis information management system. Global autocorrelation analysis, local indicators of spatial association and Kulldorff＇ s Scan Statistics were applied to map the spatial distribution and detect the space-time clusters of the pulmonary tuberculosis cases during 2005-2015. Results Spatial analysis on the incidence of pulmonary tuberculosis at the township level demonstrated that the spatial autocorrelation was positive during the study period. The values of Moran＇ s I ranged from 0.224 3 to 0.291 8 with all the P values less than 0.05. Hotspots were primarily distributed in 8 towns/streets as follows： Junzhuang, Wangping, Yongding and Tanzhesi in Mentougou district, Yancun in Fangshan district, Wangzuo town in Fengtai district, Tianqiao street in Xicheng district and Tianzhu town in Shunyi district. Spatiotemporal clusters across the entire study period were identified by using Kulldorff＇s spatiotemporal scan statistic. The primary cluster was located in Chaoyang and Shunyi districts, including 17 towns/streets,as follows： Cuigezhuang, Maizidian, Dongfeng, Taiyanggong, Zuojiazhuang, Hepingjie, Xiaoguan, Xiangheyuan, Dongba, Jiangtai, Wangjing, Jinzhan, Jiuxianqiao, Laiguangying, Sunhe towns/streets in Chaoyang district, Houshayu and Tianzhu town in Shunyi district, during January to December 2005. Conclusion Incidence rates of pulmonary tuberculosis displayed spatial and temporal clusterings at the township level in Beijing during 2005-2015, with high risk areas relatively concentrated in the central and southern parts of Beijing.
作者
孙闪华
高志东
赵飞
张文义
赵鑫
李艳圆
李亚敏
洪峰
贺晓新
詹思延
Sun Shanhua;Gao Zhidong;Zhao Fei;Zhang Wenyi;Zhao Xin;Li Yanyuan;Li Yamin;Hong Feng;He Xiaoxin;Zhan Siyan(The Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China;Beijing Research Institute for Tuberculosis Control, Beijing 100035, China;National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China;Institute of Disease Control and Prevention of the People＇s Liberation Army, Beijing 100071, China)
出处
《中华流行病学杂志》
CAS
CSCD
北大核心
2018年第6期816-820,共5页
Chinese Journal of Epidemiology
基金
首都卫生发展科研专项（首发2018-2-3021）
北京市科技计划（D121100003012004）
关键词
结核
肺
空间自相关性
时空聚集分析
Tuberculosis
Pulmonary
Spatial autocorrelation
Spatial-temporal clustering
