Author: James Yeongjun Park
Title: Spatial Visualization of Cluster-Specific COVID-19 Transmission Network in South Korea During the Early Epidemic Phase Document date: 2020_3_20
ID: 901m6zw0_18
Snippet: where is the number of shortest paths with edges and as their end edges while ( ) is the number of those shortest paths that include node . 11 We propose a degree-weighted betweenness centrality ( ), which prioritizes nodes with high degrees while penalizing them by ( ) = ∑ ( ) ≠≠* to capture the super-spreader in the capital area network. By looking at betweenness centrality only, the 6th case who transmitted the virus to five distinct c.....
Document: where is the number of shortest paths with edges and as their end edges while ( ) is the number of those shortest paths that include node . 11 We propose a degree-weighted betweenness centrality ( ), which prioritizes nodes with high degrees while penalizing them by ( ) = ∑ ( ) ≠≠* to capture the super-spreader in the capital area network. By looking at betweenness centrality only, the 6th case who transmitted the virus to five distinct cases has the highest betweenness centrality. However, a degree-weighted measure indicates that the 29th case with a much larger degree is the most central node in the network. This metric may be useful for small networks with limited information to identify super-spreaders in the early transmission networks.
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