Real-Time Forecast of Influenza Outbreak Using Dynamic Network Marker Based on Minimum Spanning Tree

Figure 3

The predictions of annual influenza outbreak in Tokyo city between 2009 and 2019. For each year, our MST-DNM method timely issues the early-warning signal of influenza outbreak only based on the clinic-visiting information. For each figure, the -axis represents the time evolution from the 20th week to the 72nd week (roughly a seasonal-outbreak period), and the -axis represents the MST-DNM score and average number of clinic visits, respectively. The red hollow triangle represents the early-warning signal detected by the MST-DNM method, and the explosion symbol is the actual outbreak point of influenza, i.e., the peak of the clinic-visiting number.