Phase diagram of epidemic spreading - unimodal vs. bimodal probability distributions

TL;DR

This paper investigates the phase diagram of epidemic spreading on complex networks, revealing bimodal distributions and the impact of network structure through empirical data and theoretical models.

Contribution

It introduces phase diagrams for disease spreading on empirical networks and develops a theoretical m-ary tree model that captures key features of observed epidemic regimes.

Findings

Bimodal probability distributions characterize disease spread.

Two regimes: local containment and epidemic outbreak.

Tree-like network structure influences spreading dynamics.

Abstract

The disease spreading on complex networks is studied in SIR model. Simulations on empirical complex networks reveal two specific regimes of disease spreading: local containment and epidemic outbreak. The variables measuring the extent of disease spreading are in general characterized by a bimodal probability distribution. Phase diagrams of disease spreading for empirical complex networks are introduced. A theoretical model of disease spreading on m-ary tree is investigated both analytically and in simulations. It is shown that the model reproduces qualitative features of phase diagrams of disease spreading observed in empirical complex networks. The role of tree-like structure of complex networks in disease spreading is discussed.