Anticipating Persistent Infection

TL;DR

This paper investigates how synchronization levels in a population affect the persistence of infection, revealing that higher synchronization reduces persistence and early asynchrony can predict long-term contagion.

Contribution

It demonstrates the counter-intuitive role of synchronization in infection persistence and identifies early asynchrony as a predictor for sustained contagion.

Findings

Higher synchronization hinders infection persistence.

Early asynchrony predicts future infection persistence.

Wider influence range reduces long-term infection.

Abstract

We explore the emergence of persistent infection in a closed region where the disease progression of the individuals is given by the SIRS model, with an individual becoming infected on contact with another infected individual within a given range. We focus on the role of synchronization in the persistence of contagion. Our key result is that higher degree of synchronization, both globally in the population and locally in the neighborhoods, hinders persistence of infection. Importantly, we find that early short-time asynchrony appears to be a consistent precursor to future persistence of infection, and can potentially provide valuable early warnings for sustained contagion in a population patch. Thus transient synchronization can help anticipate the long-term persistence of infection. Further we demonstrate that when the range of influence of an infected individual is wider, one obtains lower persistent infection. This counter-intuitive observation can also be understood through the relation of synchronization to infection burn-out.