Stability of SIS Spreading Processes in Networks with Non-Markovian Transmission and Recovery

TL;DR

This paper introduces a generalized SIS model with phase-type distributions for transmission and recovery times, providing bounds on the convergence rate to infection-free state without mean-field assumptions.

Contribution

It extends SIS models to non-Markovian settings using phase-type distributions and derives bounds on the exponential decay rate towards the infection-free equilibrium.

Findings

Distribution shape affects convergence rate

Derived lower bounds on decay rate

Model accommodates non-exponential times

Abstract

Although viral spreading processes taking place in networks are often analyzed using Markovian models in which both the transmission and the recovery times follow exponential distributions, empirical studies show that, in many real scenarios, the distribution of these times are not necessarily exponential. To overcome this limitation, we first introduce a generalized susceptible-infected-susceptible (SIS) spreading model that allows transmission and recovery times to follow phase-type distributions. In this context, we derive a lower bound on the exponential decay rate towards the infection-free equilibrium of the spreading model without relying on mean-field approximations. Based on our results, we illustrate how the particular shape of the transmission/recovery distribution influences the exponential rate of convergence towards the equilibrium.