余向华, 潘琼娇, 魏晶娇, 林丹, 倪庆翔, 陈祎, 张孝和, 陈晟. 浙江省温州市传染病自动预警系统运行情况分析[J]. 疾病监测, 2013, 28(6): 496-498. DOI: 10.3784/j.issn.1003-9961.2013.6.021
引用本文: 余向华, 潘琼娇, 魏晶娇, 林丹, 倪庆翔, 陈祎, 张孝和, 陈晟. 浙江省温州市传染病自动预警系统运行情况分析[J]. 疾病监测, 2013, 28(6): 496-498. DOI: 10.3784/j.issn.1003-9961.2013.6.021
YU Xiang-hua, PAN Qiong-jiao, WEI Jing-jiao, LIN Dan, NI Qing-xiang, CHEN Yi, ZHANG Xiao-he, CHEN Sheng. Performance of national communicable disease automatic early warning system in Wenzhou, Zhejiang[J]. Disease Surveillance, 2013, 28(6): 496-498. DOI: 10.3784/j.issn.1003-9961.2013.6.021
Citation: YU Xiang-hua, PAN Qiong-jiao, WEI Jing-jiao, LIN Dan, NI Qing-xiang, CHEN Yi, ZHANG Xiao-he, CHEN Sheng. Performance of national communicable disease automatic early warning system in Wenzhou, Zhejiang[J]. Disease Surveillance, 2013, 28(6): 496-498. DOI: 10.3784/j.issn.1003-9961.2013.6.021

浙江省温州市传染病自动预警系统运行情况分析

Performance of national communicable disease automatic early warning system in Wenzhou, Zhejiang

  • 摘要: 目的 了解国家传染病自动预警系统(预警系统)在温州市传染病暴发早期探测的应用情况及效果。 方法 以温州市2008年4月21日至2011年12月31日预警系统产生的预警信号量、信号响应率、响应时间、信号核实率、信号核实方式、响应结果、灵敏度和阳性预测值等进行描述性分析。 结果 预警系统共发出预警信号8491条,信号响应率为100%,24 h信号核实率为71.75%。涉及24种传染病。81条预警信号被判断为疑似事件,经过现场调查共确认暴发7起,预警系统的灵敏度为43.75%,阳性预测值为0.08%。 结论 预警系统可初步实现传染病暴发早期自动预警,但预警系统灵敏度和阳性预测值较低,需要不断改进。建议不同的传染病可依据本地流行情况设定不同的预警值,以提高传染病自动预警质量。

     

    Abstract: Objective To evaluate the performance of national communicable disease automatic early warning system in Wenzhou, Zhejiang province, and provide evidence for the improvement of the system. Methods Descriptive epidemiological analysis was conducted on the data of disease early warning in Wenzhou from 21 April 2008 to 31 December 2011 obtained from the system. Results A total of 8491 warning signals of 24 diseases were generated by the system. The response rate of the signals was 100% and the verifying rate of the signals within 24 hours was 71.75%. Eighty one signals were considered as suspected events after preliminary analysis and 7 outbreaks were finally confirmed by field investigation. The sensitivity of the system was 43.75%. Conclusion The system works on the automatic early warning of communicable diseases, but the sensitivity and positive predictive value were relatively low. More effort should be made to improve the system, such as setting the thresholds according to the local disease situation.

     

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