国家传染病自动预警系统在基层应用效果初步分析

余斐; 张洪龙; 赖圣杰; 叶楚楚; 赵丹; 李中杰; 杨维中

Abstract

余斐,张洪龙,赖圣杰,叶楚楚,赵丹,李中杰,杨维中.国家传染病自动预警系统在基层应用效果初步分析[J].Chinese journal of Epidemiology,2011,32(5):446-449

国家传染病自动预警系统在基层应用效果初步分析

The effectiveness of China Infectious Disease Automated-alert and Response System(CIDARS)in the local regions

Received:January 29, 2011

DOI：

KeyWord: 传染病预警系统

English Key Word: Infectious disease Early-warning system

FundProject:"十一五"国家科技支撑计划(2006BAK01A13,2008BAI56B02);中国-世界卫生组织合作项目(WPCHN0801617,WPCHN1002405);国家科技重大专项(2009ZX10004-201)

Author Name	Affiliation	E-mail
YU Fei	Wenzhou Medical College, Wenzhou 325035, China Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention3.Chinese Center for Disease Control and Prevention
ZHANG Hong-long	Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention3.Chinese Center for Disease Control and Prevention
LAI Sheng-jie	Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention3.Chinese Center for Disease Control and Prevention
YE Chu-chu	Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention3.Chinese Center for Disease Control and Prevention
ZHAO Dan	Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention3.Chinese Center for Disease Control and Prevention
LI Zhong-jie	Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention3.Chinese Center for Disease Control and Prevention	lizj@chinacdc.cn
YANG Wei-zhong	Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention3.Chinese Center for Disease Control and Prevention	yangwz@chinacdc.cn

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Abstract:

目的初步了解国家传染病自动预警系统(CIDARS)在基层传染病暴发早期探测中发挥的作用.方法在云南和湖南两省共选取4个市(县、区),对2008年7月1日至2010年6月30日预警相关病种的报告病例数、预警信号数、预警信号初步核实结果反馈时间间隔和初步核实方式、预警信号初步核实和现场调查结果进行分析.结果两省4个市(县、区)共报告了纳入预警系统的28种传染病病例12 346例,预警系统共发出2096条预警信号,共涉及19种疾病,平均每个市(县、区)每周预警信号数为4.94条.预警信号初步核实结果反馈时间间隔中位数为0.70 h(P₂₅～P₇₅为0.06-1.29h),预警信号初步核实的主要方式是监测数据分析(占63.07%).预警信号经过初步核实后,共有4种传染病的34条预警信号被判断为疑似事件信号,占总预警信号的1.62%;4个市(县、区)的疑似事件信号占预警信号的比例有较大差异,其中湖南省双峰县比例最高(4.71%)、昆明市西山区比例最低(0.58%),长沙市岳麓区为1.88%、云南省个旧市为0.95%.疑似事件经过进一步现场调查后确认了12起暴发,其中风疹事件5起,流行性腮腺炎4起,流行性感冒2起,伤寒1起.结论 CIDARS能够辅助基层疾病预防控制机构早期发现可能的传染病暴发,但不同地区、不同病种的预警效果存在差别.

English Abstract:

Objective To understand the effectiveness of China Infectious Disease Automated-alert and Response System(CIDARS)for outbreak detection at the regional level.Methods Two counties in Hunan province(Yuelu and Shuangfeng county)and two counties in Yunnan province(Xishan and Gejiu county)were chosen as the study areas. Data from CIDARS were analyzed on the following items: reported cases, warning signals, the time interval of signal response feedback, way of signal verification, outcome of signal verification and field investigation, from July 1,2008 to June 30,2010. Results In total, 12 346 cases from 28 kinds of diseases were reported,and 2096 signals of 19 diseases were generated by the system, with an average of 4.94 signals per county per week. The median of time interval on signal verification feedback was 0.70 hours(P₂₅-P₇₅:0.06-1.29 h)and the main way of signal preliminary verification was through the review of surveillance data(account for 63.07%). Among all the signals, 34 of them(1.62%)were considered to be related to suspected events via the preliminary verification at the local level. Big differences were found to have existed on the proportion of signals related to the suspected events of the total signals among the four counties, with Shuangfeng county as 4.71%, Yuelu county as 1.88%, Gejiu county as 0.95% and Xishan county as 0.58%. After an indepth study on the fields of suspected events, 12outbreaks were finally confirmed, including 5 on rubella, 4 on mumps, 2 on influenza and 1 on typhoid fever. Conclusion CIDARS could be used to assist the local public health institutions on early detection of possible outbreaks at the early stage. However, the effectiveness was different depending on the regions and diseases.

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