Epidemic spreading in modular time-varying networks
Abstract
We investigate the effects of modular and temporal connectivity patterns on epidemic spreading. To this end, we introduce and analytically characterise a model of time-varying networks with tunable modularity. Within this framework, we study the epidemic size of Susceptible-Infected-Recovered, SIR, models and the epidemic threshold of Susceptible-Infected-Susceptible, SIS, models. Interestingly, we find that while the presence of tightly connected clusters inhibit SIR processes, it speeds up SIS diseases. In this case, we observe that heterogeneous temporal connectivity patterns and modular structures induce a reduction of the threshold with respect to time-varying networks without communities. We confirm the theoretical results by means of extensive numerical simulations both on synthetic graphs as well as on a real modular and temporal network.
Cite
@article{arxiv.1710.01355,
title = {Epidemic spreading in modular time-varying networks},
author = {Matthieu Nadini and Kaiyuan Sun and Enrico Ubaldi and Michele Starnini and Alessandro Rizzo and Nicola Perra},
journal= {arXiv preprint arXiv:1710.01355},
year = {2017}
}