Work

Threshold and quasistationary distribution for the susceptible-infectious-susceptible model on networks

Year: 2026

Type: article

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.

Source: Physical review. E

DOI: 10.1103/385j-2f29

Authors: George T. Cantwell, Cristopher Moore

Institutions: University of Cambridge, Santa Fe Institute

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, Robert Wood Johnson Foundation

Award: BIGDATA: F: Collaborative Research: Mining for Patterns in Graphs and High-Dimensional Data: Achieving the Limits