Numerical investigation of metrics for epidemic processes on graphs
2015 49th Asilomar Conference on Signals, Systems and Computers, 2015•ieeexplore.ieee.org
This study develops the epidemic hitting time (EHT) metric on graphs measuring the
expected time an epidemic starting at node a in a fully susceptible network takes to
propagate and reach node b. An associated EHT centrality measure is then compared to
degree, betweenness, spectral, and effective resistance centrality measures through
exhaustive numerical simulations on several real-world network data-sets. We find two
surprising observations: first, EHT centrality is highly correlated with effective resistance …
expected time an epidemic starting at node a in a fully susceptible network takes to
propagate and reach node b. An associated EHT centrality measure is then compared to
degree, betweenness, spectral, and effective resistance centrality measures through
exhaustive numerical simulations on several real-world network data-sets. We find two
surprising observations: first, EHT centrality is highly correlated with effective resistance …
This study develops the epidemic hitting time (EHT) metric on graphs measuring the expected time an epidemic starting at node a in a fully susceptible network takes to propagate and reach node b. An associated EHT centrality measure is then compared to degree, betweenness, spectral, and effective resistance centrality measures through exhaustive numerical simulations on several real-world network data-sets. We find two surprising observations: first, EHT centrality is highly correlated with effective resistance centrality; second, the EHT centrality measure is much more delocalized compared to degree and spectral centrality, highlighting the role of peripheral nodes in epidemic spreading on graphs.
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