Stochastic approach to epidemic spreading

TL;DR

This paper presents a stochastic modeling framework for epidemic spreading, analyzing the dynamics of infection and recovery through master equations, and characterizes the epidemic onset as a critical phase transition.

Contribution

It introduces a stochastic approach using master equations to model epidemic dynamics and analyzes the critical transition at epidemic onset.

Findings

Epidemic onset characterized as a critical phase transition.

Initial exponential growth of infections identified.

Variance analysis reveals critical behavior.

Abstract

We analyze four models of epidemic spreading using a stochastic approach in which the primary stochastic variables are the numbers of individuals in each class. The stochastic approach is described by a master equation and the transition rate for each process such as infection or recovery are set up by using the law of mass action. We perform numerical simulations as well as numerical integration of the evolution equations for the average number of each class of individuals. The onset of the epidemic spreading is obtained by a linear analysis of the disease free state, from which follows the initial exponential increase of the infected and the frequency of new cases. The order parameter and the variance in the number of individuals are also obtained characterizing the onset of epidemic spreading as a critical phase transition.