2014/12/26 by Mostafa Salehi, Payam Siyari, Matteo Magnani +1 · 7 citations
Computer Science · Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #Complex network #Component (thermodynamics) #Computer science #Diffusion #Epidemic model #Evolutionary Game Theory and Cooperation #Giant component #Graph #Interdependence #Interdependent networks #Opinion Dynamics and Social Influence #Physics #Population #Random graph #Statistical physics #Theoretical computer science #cs.SI #physics.soc-ph
paper · pdf · doi:10.1016/j.chaos.2014.12.018
published in Chaos Solitons & Fractals 72, 59-67 (Elsevier BV)
arxiv created 2014/12/26 · openalex publication_date 2015/02/17 · arxiv updated 2015/06/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Several systems can be modeled as sets of interdependent networks where each network contains distinct nodes. Diffusion processes like the spreading of a disease or the propagation of information constitute fundamental phenomena occurring over such coupled networks. In this paper we propose a new concept of multidimensional epidemic threshold characterizing diffusion processes over interdependent networks, allowing different diffusion rates on the different networks and arbitrary degree distributions. We analytically derive and numerically illustrate the conditions for multilayer epidemics, i.e., the appearance of a giant connected component spanning all the networks. Furthermore, we study the evolution of infection density and diffusion dynamics with extensive simulation experiments on synthetic and real networks.