At present, a number of methods [12, 13, 15] exist to establish the onset of peak activities in the epidemics of seasonal influenza. These methods are mostly based on regression [16, 17] or time-series [12, 13, 15] analysis of seasonal ILI data. One such method is the Moving-Average Cumulative sums (Mov-Avg Cusum) method [18] [19] [20] . Originally developed for the industrial quality control [21] , it is now frequently used for detecting the outbreaks of seasonal and pandemic influenza [12, 22] . Recently there has been a flurry of new detection methods based on sophisticated statistical approaches [1, 2] , including those aimed at real-time monitoring and projecting of influenza cases [23, 24] . However, challenges remain in terms of how to use the ILI surveillance data in a simple and efficient manner for timely detection of influenza pandemics.