Emergence of Self-Sustained Oscillations for SIRS Model on Random Networks

TL;DR

This paper investigates how the SIRS disease spreading model on random networks exhibits a phase transition and synchronization phenomena, highlighting the role of clustering coefficient in the emergence of self-sustained oscillations.

Contribution

It demonstrates the emergence of a synchronization phase in the SIRS model on random networks and clarifies the influence of clustering coefficient on this behavior.

Findings

Synchronization phase occurs at low clustering coefficients.

Clustering coefficient influences the emergence of oscillations.

The study confirms prior results on clustering's role in synchronization.

Abstract

We study the phase transition from the persistence phase to the extinction phase for the SIRS (susceptible/ infected/ refractory/ susceptible) model of diseases spreading on random networks. By studying temporal evolution and synchronization parameter of this model on random networks, we find that, this model on random networks, shows a synchronization phase in a narrow range of very small values of clustering coefficient. This finding corroborates the conclusion reached in Ref. [4] that, the clustering coefficient is responsible for the emergence of the synchronization phase in the small world networks.