Sampling methods for the quasistationary regime of epidemic processes on regular and complex networks

TL;DR

This paper compares various quasistationary simulation methods for epidemic processes on networks, analyzing their effectiveness in capturing phase transitions and localized epidemic phases, with implications for understanding epidemic thresholds.

Contribution

It introduces and evaluates three quasistationary methods, demonstrating their equivalence in epidemic threshold detection and their ability to capture localized phases in network models.

Findings

All methods yield the same epidemic threshold.

SQS and HR capture localized epidemic phases in SIS models.

Auto-correlation time analysis confirms consistent critical scaling.

Abstract

A major hurdle in the simulation of the steady state of epidemic processes is that the system will unavoidably visit an absorbing, disease-free state at sufficiently long times due to the finite size of the networks where epidemics evolves. In the present work, we compare different quasistationary (QS) simulation methods where the absorbing states are suitably handled and the thermodynamical limit of the original dynamics can be achieved. We analyze the standard QS (SQS) method, where the sampling is constrained to active configurations, the reflecting boundary condition (RBC), where the dynamics returns to the pre-absorbing configuration, and hub reactivation (HR), where the most connected vertex of the network is reactivated after a visit to an absorbing state. We apply the methods to the contact process (CP) and susceptible-infected-susceptible (SIS) models on regular and scale free networks. The investigated methods yield the same epidemic threshold for both models. For CP, that undergoes a standard collective phase transition, the methods are equivalent. For SIS, whose phase transition is ruled by the hub mutual reactivation, the SQS and HR methods are able to capture localized epidemic phases while RBC is not. We also apply the auto-correlation time as a tool to characterize the phase transition and observe that this analysis provides the same finite-size scaling exponents for the critical relaxation time for the investigated methods. Finally, we verify the equivalence between RBC method and a weak external field for epidemics on networks.