Contagion-diffusion processes with recurrent mobility patterns of distinguishable agents

TL;DR

This paper investigates how recurrent mobility patterns of distinguishable agents influence epidemic spread in large urban areas, providing a model that accurately predicts epidemic thresholds considering individual mobility and distribution.

Contribution

It introduces a novel model incorporating distinguishable agents' residence and destinations, improving epidemic threshold calculations over traditional indistinguishable agent models.

Findings

Recurrent mobility patterns significantly affect epidemic dynamics.

Indistinguishable agent models overestimate epidemic thresholds.

The model enables fast computation and analytical threshold determination.

Abstract

The analysis of contagion-diffusion processes in metapopulations is a powerful theoretical tool to study how mobility influences the spread of communicable diseases. Nevertheless, many metapopulation approaches use indistinguishable agents to alleviate analytical difficulties. Here, we address the impact that recurrent mobility patterns, and the spatial distribution of distinguishable agents, have on the unfolding of epidemics in large urban areas. We incorporate the distinguishable nature of agents regarding both, their residence, and their usual destination. The proposed model allows both a fast computation of the spatio-temporal pattern of the epidemic trajectory and. the analytical calculation of the epidemic threshold. This threshold is found as the spectral radius of a mixing matrix encapsulating the residential distribution, and the specific commuting patterns of agents. We prove that the simplification of indistinguishable individuals overestimates the value of the epidemic threshold.