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
12: end if
13: end for
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