Disease spreading in populations of moving agents

TL;DR

This paper investigates how agent movement, including long-distance jumps, influences disease spread, revealing that even minimal jumps significantly lower epidemic thresholds by disrupting local correlations.

Contribution

It demonstrates that small percentages of long-distance jumps in moving agents drastically reduce epidemic thresholds, connecting dynamic network structure to disease spreading behavior.

Findings

Long-distance jumps decrease epidemic thresholds.

Disruption of local correlations enhances disease spread.

Mean-field approximation explains the observed effects.

Abstract

We study the effect of motion on disease spreading in a system of random walkers which additionally perform long-distance jumps. A small percentage of jumps in the agent motion is sufficient to destroy the local correlations and to produce a large drop in the epidemic threshold, well explained in terms of a mean-field approximation. This effect is similar to the crossover found in static small-world networks, and can be furthermore linked to the structural properties of the dynamical network of agent interactions.