Application of the moving epidemic method in the development of epidemic thresholds and tiered warning alert approachs for influenza prevention in Beijing

Abstract

Objective: To calculate both the epidemic and intensity thresholds for different levels in Beijing and to establish a tiered alert system in the 2018-2019 influenza season as well as to evaluate the performance of calculated thresholds. Method: Weekly count of influenza-like illness and percentage of influenza-like illness (ILI%) of the last five influenza seasons were modeled by 'moving epidemic method' (MEM) to calculate the influenza epidemic and intensity thresholds at different levels. A cross-validation procedure was used to evaluate the performance. Indicators of Matthew correlation coefficient, Youden's index, sensitivity and specificity were calculated. Results: For weekly count of influenza-like illness, data showed that the epidemic threshold for 2018-2019 influenza season was 12 984 and the medium, high and very high intensity thresholds were 22 503, 37 589, 47 157, respectively. Matthew correlation coefficient of the epidemic threshold was 62% and youden's index as 60% , sensitivity as 69%, specificity as 91%. Data on weekly ILI%, the epidemic threshold for 2018-2019 influenza season was 1.66%, with medium, high and very high intensity thresholds as 2.46%, 3.84% and 4.66%, respectively. The overall Matthew correlation coefficient of the epidemic threshold was 59%, with 54% for the Youden's index, sensitivity as 60% and specificity as 94%. Conclusions: MEM produced a good specific signal for detecting the influenza epidemics and the accuracy of the method was acceptable. The early warning performance regarding the application of weekly count on influenza-like illness was slightly better than ILI%. This method could be applied in the practical influenza epidemic alert "work in Beijing" .