“十三五”期间天津市传染病自动预警系统运行情况分析

Analysis on the application of infectious diseases automated-alert and response system in Tianjin during the 13th Five-Year Plan period

摘要:

目的 分析“十三五”期间天津市接收的传染病自动预警信号流行病学特征，为“十四五”期间传染病自动预警系统的功能优化提供参考依据。方法 通过“传染病自动预警信息系统”下载天津市2016-2020年传染病自动预警信号资料，通过描述性方法对预警信号特征及响应情况等进行分析。结果 “十三五”期间天津市收到预警信号23660条，涉及病种39种，响应率100%，预警信号阳性率1.10%。预警信号响应时间中位数为0.53h（P25-P75：0.19-1.17h）。2小时内响应及时率为95.74%；24小时内响应及时率为98.47%。预警信号数居前五位的是新型冠状病毒肺炎、其它感染性腹泻病、痢疾、麻疹及猩红热。结论 “十三五”期间天津市传染病自动预警系统运行情况良好，但存在预警信号阳性率低等问题，希望“十四五”期间应根据防控需求及疾病流行特征完善预警阈值，提高工作人员工作效率。

Abstract:

Objective To analyze the epidemiological characteristics of automatic warning signals of infectious diseases received in Tianjin during the 13th Five-Year Plan period, and to provide reference for the function optimization of automatic warning system of infectious diseases during the 14th Five-year Plan period． Methods The data of infectious disease automatic early warning signals in Tianjin from 2016 to 2020 were downloaded from the China infectious diseases automated-alert and response system (CIDARS). The characteristics and response of early warning signals were analyzed by descriptive method. Results During the 13th Five-Year Plan period, 23,660 early warning signals were received in Tianjin, involving 39 kinds of infectious diseases, with 100% response rate and 1.10% positive rate of early warning signals. The median response time of warning signal was 0.53 hours (P25-P75: 0.19-1.17h). 95.74% of signals were responded within 2 hours and 98.47% of signals were responded within 24 hours. COVID-19, other infectious diarrhea diseases, dysentery, measles, and scarlet fever were the top five diseases with early warning signals. Conclusion During the 13th Five-Year, the automatic early warning system of infectious diseases in Tianjin runs well and has a high response rate, but the positive rate of early warning signal is low. During the 14th Five-Year，further research is needed to improve the early warning threshold according to the prevention and control needs and epidemic characteristics of different diseases, and to improve early warning positive rate.