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

Figure 4

The dynamic evolution of the minimum spanning tree of the city network in Tokyo during years 2013-2014. The nodes are colored by the average number of clinic visits of the corresponding district, and the thickness of the edges represents the correlations between corresponding nodes (the detailed calculation is in Materials and Methods). It is clear that the edges become thicker before the nodes turn red in week 54, which indicates that the early-warning signals from our method appear before the flu outbreak.