Stochastic epidemic dynamics on extremely heterogeneous networks
arXiv:1609.08450 · doi:10.1103/PhysRevE.94.062408
Abstract
Networks of contacts capable of spreading infectious diseases are often observed to be highly heterogeneous, with the majority of individuals having fewer contacts than the mean, and a significant minority having relatively very many contacts. We derive a two-dimensional diffusion model for the full temporal behavior of the stochastic susceptible-infectious-recovered (SIR) model on such a network, by making use of a time-scale separation in the deterministic limit of the dynamics. This low-dimensional process is an accurate approximation to the full model in the limit of large populations, even for cases when the time-scale separation is not too pronounced, provided the maximum degree is not of the order of the population size.
22 pages, 8 figures
References in corpus (14)
- Epidemic processes in complex networks
- Epidemic dynamics and endemic states in complex networks
- Epidemic dynamics in finite size scale-free networks
- Networks and the Epidemiology of Infectious Disease
- Epidemic thresholds of the Susceptible-Infected-Susceptible model on networks: A comparison of numerical and theoretical results
- Edge-Based Compartmental Modeling for Infectious Disease Spread Part I: An Overview
- Avoidable errors in the modeling of outbreaks of emerging pathogens, with special reference to Ebola
- Finite-size scaling in complex networks
- Langevin approach for the dynamics of the contact process on annealed scale-free networks
- Edge-Based Compartmental Modeling for Infectious Disease Spread Part III: Disease and Population Structure
- Fast-mode elimination in stochastic metapopulation models
- Stochastic oscillations in models of epidemics on a network of cities
- Phase lag in epidemics on a network of cities
- Dynamics of Stochastic Epidemics on Heterogeneous Networks