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预防医学  2022, Vol. 34 Issue (4): 375-379    DOI: 10.19485/j.cnki.issn2096-5087.2022.04.011
  疾病控制 本期目录 | 过刊浏览 | 高级检索 |
2015—2020年宁波市肺结核疫情时空聚集性分析
陈云鹏1, 倪敏东2, 贺天锋3, 张新运2, 车洋3, 桑国鑫3
1.宁波大学医学院,浙江 宁波 315211;
2.宁波市规划设计研究院,浙江 宁波 315042;
3.宁波市疾病预防控制中心,浙江 宁波 315010
Spatio-temporal clustering analysis of pulmonary tuberculosis in Ningbo City from 2015 to 2020
CHEN Yunpeng1, NI Mindong2, HE Tianfeng3, ZHANG Xinyun2, CHE Yang3, SANG Guoxin3
1. School of Medicine, Ningbo University, Ningbo, Zhejiang 315211, China;
2. Ningbo Urban Planning Design Institute, Ningbo, Zhejiang 315042, China;
3. Ningbo Center for Disease Control and Prevention, Ningbo, Zhejiang 315010, China
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摘要 目的 了解2015—2020年宁波市肺结核疫情的时空分布特征,为防治肺结核提供依据。方法 从中国疾病预防控制信息系统结核病管理系统导出2015—2020年宁波市肺结核病例资料,并与宁波市规划设计研究院地理信息数据库关联;采用SaTScan 10.0软件对2015—2020年宁波市153个乡镇(街道)的肺结核报告病例数、人口数和地理经纬度进行逐月时空扫描和聚集性分析。结果 2015—2020年宁波市肺结核病例存在1个一类聚集区和2个二类聚集区;其中一类聚集区以松岙镇为中心,覆盖37个乡镇(街道),聚集时间为2015年1月1日至2017年12月31日;二类聚集区包括以余姚市三七市镇为中心的38个乡镇(街道)和杭州湾新区1个乡镇。2015—2016年一类聚集时间为1—6月,2017—2019年为3—8月,2020年为5—10月。2015—2020年宁波市各乡镇(街道)报告发病率总体呈下降趋势,但2020年鄞州区福明街道和象山县爵溪街道的发病率均高于80/10万。结论 2015—2020年宁波市肺结核发病在街道(乡镇)水平上存在明显的时空聚集特征,且聚集范围主要集中在中东部地区,鄞州区福明街道和象山县爵溪街道报告发病率较高,应实施针对性强的区域结核病防治策略。
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陈云鹏
倪敏东
贺天锋
张新运
车洋
桑国鑫
关键词 肺结核时空聚集时空聚类分析宁波市    
AbstractObjective To investigate the spatio-temporal distribution characteristics of pulmonary tuberculosis in Ningbo City from 2015 to 2020, so as to provide insights into tuberculosis control. Methods The data of pulmonary tuberculosis cases in Ningbo City from 2015 to 2020 were collected from Tuberculosis Management Information System of China Disease Control and Prevention Information System, and were linked with the geographic information database of Ningbo Planning Design and Research Institute. The software SaTScan version 10.3 was employed for monthly spatio-temporal scanning and cluster analysis of reported pulmonary tuberculosis cases, populations, longitude and latitude in 153 townships of Ningbo City from 2015 to 2020. Results There were one class Ⅰ cluster and two class Ⅱ clusters of pulmonary tuberculosis cases in Ningbo City from 2015 to 2020, and the class Ⅰ cluster was centered in Song'ao Township and covered 37 townships, with aggregation time from January 1, 2015 to December 31, 2017, while class Ⅱ clusters were covered 38 tounships which were centered in Sanqishi Township of Yuyao County, and one township in Hangzhou Bay New Town. The aggregation time was from January to June in 2015 and 2016, from March to August between 2017 and 2019 and between May and October, 2020. The overall reported incidence of pulmonary tuberculosis appeared a tendency towards a decline in each township of Ningbo City from 2015 to 2020; however, the incidence of pulmonary tuberculosis was more than 80 per 100 thousand in Fuming Township of Yinzhou District and Juexi Township of Xiangshan County in 2020. Conclusions There were significant spatio-temporal clustering characteristics of pulmonary tuberculosis incidence at a township level in Ningbo City from 2015 to 2020, and the clusters were mainly concentrated in the central and eastern Ningbo City. The reported incidence of pulmonary tuberculosis is high in Fuming Township of Yinzhou District and Juexi Township of Xiangshan County, where targeted regional tuberculosis control strategies should be implemented.
Key wordspulmonary tuberculosis    spatio-temporal aggregation    spatio-temporal clustering analysis    Ningbo City
收稿日期: 2021-11-09      修回日期: 2022-01-08      出版日期: 2022-04-10
中图分类号:  R521  
基金资助:浙江省医药卫生科技项目(2021KY334); 浙江省医药卫生科技项目(2022KY1189); 浙江省公益基金项目(LGF19H260010); 浙江省医学重点学科项目(07-013); 宁波市卫生品牌学科基金(PPXK2018-10)
通信作者: 贺天锋,E-mail:hetfnbcdc@163.com;倪敏东,E-mail:nmd1983@sina.com   
作者简介: 陈云鹏,硕士在读
引用本文:   
陈云鹏, 倪敏东, 贺天锋, 张新运, 车洋, 桑国鑫. 2015—2020年宁波市肺结核疫情时空聚集性分析[J]. 预防医学, 2022, 34(4): 375-379.
CHEN Yunpeng, NI Mindong, HE Tianfeng, ZHANG Xinyun, CHE Yang, SANG Guoxin. Spatio-temporal clustering analysis of pulmonary tuberculosis in Ningbo City from 2015 to 2020. Preventive Medicine, 2022, 34(4): 375-379.
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http://www.zjyfyxzz.com/CN/10.19485/j.cnki.issn2096-5087.2022.04.011      或      http://www.zjyfyxzz.com/CN/Y2022/V34/I4/375
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