Phase transition of the susceptible-infected-susceptible dynamics on time-varying configuration model networks

TL;DR

This paper develops a comprehensive degree-based theoretical framework to analyze SIS epidemic dynamics on time-varying networks, elucidating phase transitions, thresholds, and the role of hubs in infection spread.

Contribution

It introduces a unifying analytical approach that captures both collective and hub activation, and reinterprets hub-dominated transitions as heterogeneous critical phenomena.

Findings

Derived a self-consistent expression for the epidemic threshold.

Unified existing SIS network models within a single framework.

Revealed that different degree classes activate sequentially beyond the epidemic threshold.

Abstract

We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework, we provide a detailed analysis of the stationary state that covers, for a given structure, every dynamic regimes easily tuned by the rewiring rate. This analysis is suitable for the characterization of the phase transition and leads to three main contributions. (i) We obtain a self-consistent expression for the absorbing-state threshold, able to capture both collective and hub activation. (ii) We recover the predictions of a number of existing approaches as limiting cases of our analysis, providing thereby a unifying point of view for the SIS dynamics on random networks. (iii) We reinterpret the concept of hub-dominated phase transition. Within our framework, it appears as a heterogeneous critical phenomenon : observables for different degree classes have a different scaling with the infection rate. This leads to the successive activation of the degree classes beyond the epidemic threshold.