Research Article
Real-Time Forecast of Influenza Outbreak Using Dynamic Network Marker Based on Minimum Spanning Tree
Input: one-year hospitalization data caused by influenza; | Output: the tipping point of the flu outbreak of this year. | 1: Model a city network for a specific city | 2: Map the hospitalization data into the corresponding nodes in the network | 3: for week in a certain year do | 4: for each edge do | 5: Weight the edge with | 6: end for/obtained a weighted undirected graph / | 7: obtained the minimum spanning tree using Algorithm 2/ | 8: Calculate the minimum spanning tree’s weight sum as the MST-DNB score | 9: ifthen /the parameter was trained by other year’s dataset/ | 10: the week is deemed to the tipping point | 11: Break | 12: end if | 13: end for |
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