BioMed Research International / 2020 / Article / Fig 1

Research Article

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

Figure 1

Schematic illustration of detecting the early-warning signal of influenza outbreak based on MST-DNM. (a) The historical records of clinic visits caused by influenza between 1 January 2009 and 1 May 2019 were collected from three regions of Japan, including Tokyo, Osaka, and Hokkaido. (b) Through building a city network, weighting, and the changes of the minimum spanning tree of this network, the MST-DNM method can monitor in real time the progress of the influenza and issue early-warning signals in a timely manner. (c) Based on the MST-DNM method, the outbreak process of influenza could be divided into three states, i.e., the normal state, the preoutbreak state, and the flu outbreak state. The abrupt increase of MST-DNM score means the arrival of the preoutbreak state.

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