Effects of city-size heterogeneity on epidemic spreading in a metapopulation: A reaction-diffusion approach

TL;DR

This paper develops a reaction-diffusion model for epidemic spreading in complex networks of cities and villages, analyzing how heterogeneity in city sizes and network topology influences the epidemic threshold and dynamics.

Contribution

It introduces a generalized reaction-diffusion framework that accounts for heterogeneity in city sizes and network topology in epidemic modeling.

Findings

Heterogeneity affects the epidemic threshold non-trivially.

The epidemic threshold depends on reaction rates, network topology, and population size crossover.

Small villages and large cities exhibit different epidemic dynamics.

Abstract

We review and introduce a generalized reaction-diffusion approach to epidemic spreading in a metapopulation modeled as a complex network. The metapopulation consists of susceptible and infected individuals that are grouped in subpopulations symbolising cities and villages that are coupled by human travel in a transportation network. By analytic methods and numerical simulations we calculate the fraction of infected people in the metaopoluation in the long time limit, as well as the relevant parameters characterising the epidemic threshold that separates an epidemic from a non-epidemic phase. Within this model, we investigate the effect of a heterogeneous network topology and a heterogeneous subpopulation size distribution. Such a system is suited for epidemic modeling where small villages and big cities exist simultaneously in the metapopulation. We find that the heterogeneous conditions cause the epidemic threshold to be a non-trivial function of the reaction rates (local parameters), the network's topology (global parameters) and the cross-over population size that separates "village dynamics" from "city dynamics".