Threshold and quasistationary distribution for the susceptible-infectious-susceptible model on networks
George T Cantwell1, Cristopher Moore2
1University of Cambridge, Department of Engineering, Cambridge CB2 1PZ, United Kingdom.
Abstract:
We study the Susceptible-Infectious-Susceptible model on arbitrary networks. The well-established pair approximation treats neighboring pairs of nodes exactly while making a mean-field approximation for the rest of the network. We improve the method by expanding the state space dynamically, giving nodes a memory of when they last became susceptible. The resulting approximation is simple to implement and appears to be highly accurate, both in locating the epidemic threshold and in computing the quasistationary fraction of infected individuals above the threshold, for both finite graphs and infinite random graphs.
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