摘要
目的采用移动流行区间法计算流感流行阈值和强度阈值,预测流感到达高峰的时间,为监测流感活动水平和早期预警提供理论依据。方法以江苏省扬州市2011-2018年冬春季(第40周至次年第20周)流感样病例监测中流感病毒核酸检测阳性率数据为历史基线,利用移动流行区间法分析扬州市2018-2019年流感冬春季流行阈值和3个强度阈值,并根据历史数据计算阳性率从开始超过流行阈值至高峰的平均周数以预测2018-2019年流感冬春季高峰期。结果对2011-2018年流感冬春季数据建模,最优参数δ值为2.10,平均灵敏度、特异度、阳性预测值、阴性预测值和约登指数分别为0.81、0.91、0.87、0.87和0.72。2018-2019年流感冬春季在2019年第3周进入流行期,预测的高峰期与实际观察到的一致(第8周),处于高强度水平。结论应用于流感病原学数据的移动流行区间法是评估扬州市流感流行强度和预测流感高峰期的有效工具。
Objective To calculate the influenza epidemic threshold, intensity thresholds and predict peak, and provides a theoretical basis for the surveillance for influenza activity levels and early warning. Methods The positive rates of influenza virus in influenza seasons from 2011 to 2018 in Yangzhou(from week 40 to week 20 of the next year) was used as the historical baseline data. Moving epidemic method(MEM) was used to analyze the epidemic threshold and three intensity thresholds, and the average number of weeks from the day reaching epidemic threshold to the day reaching peak was calculated to predict peak of 2018 -2019 influenza season in Yangzhou. Results The data of influenza seasons from 2011 to 2018 were used to establish the model, the optimal parameter δ value was 2.10. The average sensitivity, specificity, positive predictive value, negative predictive value and Yoden index were 0.81, 0.91, 0.87, 0.87 and 0.72, respectively. In 2018 -2019 influenza season, the epidemic period began in the third week of 2019. The predicted peak was consistent with the observed peak(week8). The intensity level was high. Conclusion The MEM using influenza virology data is an effective tool for assessment of the intensity of influenza epidemic and prediction of the peak of influenza season in Yangzhou.
作者
郭倩
周罗晶
Guo Qian;Zhou Luojing(Department of Preventive Medicine,Medicine College of Yangzhou University,Yangzhou 225001,Jiangsu,China;Department of Science and Technology,Clinical Medical School of Yangzhou University,Yangzhou 225001,Jiangsu,China)
出处
《疾病监测》
CAS
2020年第4期316-320,共5页
Disease Surveillance
关键词
流感
移动流行区间法
阈值
预测预警
Influenza
Moving epidemic method
Threshold
Prediction and early warning
