Modularity promotes epidemic recurrence

TL;DR

This paper investigates how community structures in contact networks influence the recurrence of epidemics, showing that certain levels of modularity can enable persistent outbreaks of highly contagious diseases.

Contribution

It combines numerical simulations and spectral theory to reveal that optimal modularity in social networks promotes long-term epidemic recurrence.

Findings

Highly contagious diseases can persist indefinitely in networks with specific modularity levels.

Community structure significantly impacts epidemic longevity and recurrence.

Spectral methods help predict conditions for epidemic persistence.

Abstract

The long-term evolution of epidemic processes depends crucially on the structure of contact networks. As empirical evidence indicates that human populations exhibit strong community organization, we investigate here how such mesoscopic configurations affect the likelihood of epidemic recurrence. Through numerical simulations on real social networks and theoretical arguments using spectral methods, we demonstrate that highly contagious diseases that would have otherwise died out rapidly can persist indefinitely for an optimal range of modularity in contact networks.