Infection spreading in a population with evolving contacts

TL;DR

This paper investigates how adaptive contact networks, where individuals can break and reconnect links, influence infection spread, showing that moderate reconnection or isolation can effectively prevent endemic infections.

Contribution

It introduces a coevolving network model where contact patterns adapt during infection spread, demonstrating how reconnection strategies can suppress epidemics.

Findings

Moderate reconnection frequency can fully suppress infection.

Partial isolation of infected individuals can eliminate endemic states.

Network coevolution impacts epidemic thresholds.

Abstract

We study the spreading of an infection within an SIS epidemiological model on a network. Susceptible agents are given the opportunity of breaking their links with infected agents. Broken links are either permanently removed or reconnected with the rest of the population. Thus, the network coevolves with the population as the infection progresses. We show that a moderate reconnection frequency is enough to completely suppress the infection. A partial, rather weak isolation of infected agents suffices to eliminate the endemic state.