A statistical assessment of influenza intensity thresholds from the moving epidemic and WHO methods

Abstract Monitoring influenza activity is a key task of public health agencies worldwide. Intensity thresholds serve to retrospectively classify season peak intensity and to compare current influenza activity to past peak values. The resulting classifications into low, medium, high, or very high intensity inform national-level risk assessment and planning. Moreover, they feed into international summary reports. Two common thresholding approaches, recommended in dedicated WHO guidelines, are the moving epidemic method (MEM) and the WHO method. In both approaches, thresholds correspond to quantiles of a normal distribution fitted to a set of historical observations. While an extensive literature on applications of these methods exists, their statistical properties have not been assessed systematically. In this article, we study them analytically and in a simulation study based on re-sampling of French influenza surveillance data. Moreover, extensions to account for small sample sizes and secular trends are described. Under the default settings, both the MEM and WHO method on average classify more seasons than intended as high or very high intensity. Combining characteristics of both and adding a small-sample correction, better-calibrated thresholds can be achieved. Even these, however, have modest sensitivity and positive predictive values. This concerns especially thresholds for very high intensity.