2008—2019年宝鸡市流行性腮腺炎时空聚集性分析  

Spatial-temporal clustering analysis of mumps in Baoji City from 2008 to 2019

作　　者：贾敏[1] 何微[1] 李红兵[1] 赖专华[1] 梁文革[1] 田辉[1] 李小东[1] JIA Min;HE Wei;LI Hong-bing;LAI Zhuan-hua;LIANG Wen-ge;TIAN Hui;LI Xiao-dong(Baoji Center for Disease Control and Prevention,Shaanxi 721000,China)

机构地区：[1]宝鸡市疾病预防控制中心,陕西721000

出　　处：《医学动物防制》2022年第3期235-238,共4页Journal of Medical Pest Control

基　　金：宝鸡市卫健委科研立项(2019-51)。

摘　　要：目的了解2008—2019年宝鸡市流行性腮腺炎时空聚集情况,为流行性腮腺炎预防和控制提供科学依据。方法应用ArcGIS 10.1软件和SaTScan 9.0软件对中国传染病报告信息管理系统中2008—2019年宝鸡市的流行性腮腺炎病例进行时空分析。结果2008—2019年宝鸡市共报告流行性腮腺炎病例12154例,年平均发病率为26.92/10万。每年4—7月出现第一个发病高峰,11月—次年1月有一个小的发病高峰,呈现明显的季节性、周期性变化。2008—2012年发病趋势不明显,上下波动,2012年达最高峰,随后总体发病趋势逐年下降,2014—2019年维持在较低水平。时空扫描发现宝鸡市流行性腮腺炎发病有时空聚集性,凤县、太白县、金台区、渭滨区为高发聚集区。结论2008—2019年宝鸡市流行性腮腺炎发病有明显的时空聚集性,应根据流行性腮腺炎发病时空分布特点制定相应的防制措施。Objective To understand the temporal and spatial clustering of mumps in Baoji from 2008 to 2019,and to provide a scientific basis for the prevention and control of mumps.Methods Application of ArcGIS 10.1 and SaTScan 9.0 software were used to analyze of mumps cases in Baoji from 2008 to 2019 in the Chinese Infectious Disease Reporting Information Management System.Results A total of 12154 cases of mumps were reported in Baoji from 2008 to 2019,with an average annual incidence of 26.92/100000.The first peak occurs from April to July each year,and a small peak from November to January,showing a clear seasonal and cyclical variation.The incidence trend was insignificant and fluctuated up and down from 2008 to 2012,peaking in 2012.The overall incidence trend declined year by year from 2014 to 2019,remaining at a low level.Fengxian County,Taibai County,Jintai District and Weibin District were the high-occurrence aggregation areas.Conclusion There is a clear spatial and temporal clustering of mumps incidence in Baoji from 2008 to 2019.The corresponding prevention and control measures should be formulated according to the temporal and spatial distribution characteristics of mumps incidence.

关 键 词：流行性腮腺炎 地理信息系统 空间自相关 时空聚集性 分析 

分 类 号：R512.1[医药卫生—内科学]