The duration of an $SIR$ epidemic on a configuration model

TL;DR

This paper analyzes the duration of large SIR epidemics on configuration model graphs, accounting for non-exponential infectious periods and degree distribution variance, and examines vaccination effects.

Contribution

It provides new limit results for epidemic duration considering general infectious period distributions and degree variances, using branching processes and percolation theory.

Findings

Vaccination can increase epidemic duration if it fails to prevent the outbreak.

The analysis applies to both finite and infinite degree variance networks.

Results include effects of vaccination on epidemic duration.

Abstract

We consider the spread of a supercritical stochastic SIR (Susceptible, Infectious, Recovered) epidemic on a configuration model random graph. We mainly focus on the final stages of a large outbreak and provide limit results for the duration of the entire epidemic, while we allow for non-exponential distributions of the infectious period and for both finite and infinite variance of the asymptotic degree distribution in the graph. Our analysis relies on the analysis of some subcritical continuous time branching processes and on ideas from first-passage percolation. As an application we investigate the effect of vaccination with an all-or-nothing vaccine on the duration of the epidemic. We show that if vaccination fails to prevent the epidemic, it often -- but not always -- increases the duration of the epidemic.