Modeling Properties of Influenza-Like Illness Peak Events with Crossing Theory

The concept of ―peak event‖ has been used extensively to characterize influenza epidemics. Current definitions, however, could not maximize the amount of pertinent information about the probabilities of peak events that could be extracted from the generally limited available records. This study proposes a new method of defining peak events and statistically characterizing their properties, including: annual event density, their timing, the magnitude over prescribed thresholds and duration. These properties of peak events are analyzed in five counties of Florida using records from the Influenza-Like Illness Surveillance Network (ILINet). Further, the identified properties of peak events are compared between counties to reveal the geographic variability of influenza peak activity. The results of this study illustrate the proposed methodology’s capacity to aid public health professionals in supporting influenza surveillance and implementing timely effective intervention strategies.