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

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.

14 pages, 11 figures

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• An overview of epidemic models with phase transitions to absorbing states running on top of complex networks
• Cumulative Merging Percolation and the epidemic transition of the Susceptible-Infected-Susceptible model in networks
• High prevalence regimes in the pair quenched mean-field theory for the susceptible-infected-susceptible model on networks
• Activation thresholds in epidemic spreading with motile infectious agents on scale-free networks
• Optimal networks for dynamical spreading
• Simple quasistationary method for simulations of epidemic processes with localized states
• Duality between predictability and reconstructability in complex systems
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