Suppressing epidemic spreading by risk-averse migration in dynamical networks

TL;DR

This study explores how risk-averse migration behaviors in dynamic networks can effectively suppress epidemic spreading, revealing optimal parameters that maximize epidemic thresholds and control outbreaks.

Contribution

The paper introduces a model where agents' risk-averse migration decisions influence epidemic dynamics, identifying optimal parameters for epidemic control in dynamical networks.

Findings

Existence of an optimal critical infection threshold for maximum epidemic suppression.

Epidemic threshold increases with higher recovery rates.

Epidemic threshold is maximized at an optimal agent moving speed.

Abstract

In this paper, we study the interplay between individual behaviors and epidemic spreading in a dynamical network. We distribute agents on a square-shaped region with periodic boundary conditions. Every agent is regarded as a node of the network and a wireless link is established between two agents if their geographical distance is less than a certain radius. At each time, every agent assesses the epidemic situation and make decisions on whether it should stay in or leave its current place. An agent will leave its current place with a speed if the number of infected neighbors reaches or exceeds a critical value $E$. Owing to the movement of agents, the network's structure is dynamical. Interestingly, we find that there exists an optimal value of $E$ leading to the maximum epidemic threshold. This means that epidemic spreading can be effectively controlled by risk-averse migration. Besides, we find that the epidemic threshold increases as the recovering rate increases, decreases as the contact radius increases, and is maximized by an optimal moving speed. Our findings offer a deeper understanding of epidemic spreading in dynamical networks.