Phase transitions in contagion processes mediated by recurrent mobility patterns

TL;DR

This paper introduces a theoretical framework for understanding how recurrent human mobility patterns influence contagion spread, revealing a phase transition that depends on mobility parameters and can inform control strategies.

Contribution

The study develops a novel model incorporating recurrent mobility and geographic memory, uncovering a phase transition in contagion dynamics not captured by traditional models.

Findings

Identifies a phase transition in contagion spread based on mobility patterns.

Derives an invasion threshold dependent on mobility parameters.

Validates the model using real human commuting data.

Abstract

Human mobility and activity patterns mediate contagion on many levels, including the spatial spread of infectious diseases, diffusion of rumors, and emergence of consensus. These patterns however are often dominated by specific locations and recurrent flows and poorly modeled by the random diffusive dynamics generally used to study them. Here we develop a theoretical framework to analyze contagion within a network of locations where individuals recall their geographic origins. We find a phase transition between a regime in which the contagion affects a large fraction of the system and one in which only a small fraction is affected. This transition cannot be uncovered by continuous deterministic models due to the stochastic features of the contagion process and defines an invasion threshold that depends on mobility parameters, providing guidance for controlling contagion spread by constraining mobility processes. We recover the threshold behavior by analyzing diffusion processes mediated by real human commuting data.