Spreaders in the Network SIR Model: An Empirical Study

We use the susceptible-infected-recovered (SIR) model for disease spread over a network, and empirically study how well various centrality measures perform at identifying which nodes in a network will be the best spreaders of disease on 10 real-world networks. We find that the relative performance of degree, shell number and other centrality measures can be sensitive to β , the probability that an infected node will transmit the disease to a susceptible node. We also find that eigenvector centrality performs very well in general for values of β above the epidemic threshold.