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目的通过对《传染病自动预警信息系统》中江西省常见传染病的时间序列参数进行调整,减少错误预警信息,提高监测效率;同时为以后其他病种的预警参数调整提供科学依据。方法收集整理2010—2014年江西省传染病自动预警信息以及2015—2016年参数调整后自动预警信息。使用卡方检验、fisher确切概率法等方法,分析参数调整对传染病自动预警信息灵敏度、特异度以及阳性预测值的影响。结果 2015—2016年江西省常见传染病共发出预警信息3 980个,年平均1 990个;预警灵敏度为46.67%、特异度为57.90%、PPV为0.53%。与2010—2014年相比,年平均预警信息数下降72.85%;通过Fisher确切概率法比较预警灵敏度,P=0.43;通过卡方检验比较预警特异度和阳性预测值,P<0.001。结论通过调整预警基准值,2015—2016年江西省预警信息数有明显下降,预警特异性以及阳性预测值差异均有统计学意义,有效减少了错误预警信息,提高了监测效率。
Objective To adjust the time series parameters of common infectious diseases in Jiangxi Province for the Automatic Early Warning System of Infectious Diseases, to reduce the error warning information and improve the monitoring efficiency, and to provide a scientific basis for the adjustment of the early warning parameters of other diseases in the future. Methods To collect and sort out the automatic warning information of infectious diseases in Jiangxi province during 2010-2014 and the automatic warning information of 2015-2016 parameters adjustment. Using the chi-square test and fisher exact probability method, the influence of parameter adjustment on the sensitivity, specificity and positive predictive value of automatic warning information of infectious diseases was analyzed. Results In 2015-2016, a total of 3 980 early warning messages were issued for common infectious diseases in Jiangxi Province, with an average annual number of 1 990. The warning sensitivity was 46.67%, the specificity was 57.90% and the PPV was 0.53%. Compared with 2010-2014, the annual average number of early warning information decreased by 72.85%; Fisher’s exact probabilistic method was used to compare the early warning sensitivity, P = 0.43; chi square test was used to compare the early warning specificity and positive predictive value, P <0.001. Conclusion By adjusting the precautionary baseline value, the number of early warning information in Jiangxi Province decreased significantly in 2015-2016. The differences between early warning specificity and positive predictive value were statistically significant, which effectively reduced the error warning information and improved the monitoring efficiency.