Source-linked AI summary
Epidemic spreading on interconnected networks
Anna Saumell-Mendiola, M. Ángeles Serrano, Marián Boguñá
TL;DR
The paper addresses limited understanding of epidemics on coupled networks by developing a heterogeneous mean field analysis of SIS spreading on two interconnected complex networks. It derives the global epidemic threshold and shows analytically and through large-scale simulations that coupling can sustain endemic activity even when neither isolated network supports it.
Problem
Understanding of epidemic spreading on coupled interconnected networks remains limited, despite established knowledge for isolated networks.
Method
The paper applies a heterogeneous mean field study to the SIS model on two interconnected complex networks, using vector degrees, degree correlations, and coupling structure.
Results
Coupling can make the global epidemic threshold smaller than the thresholds of the two networks separately, allowing an endemic state even when neither isolated network is endemic.
Takeaways & Limitations
Two networks below their respective epidemic thresholds may sustain an endemic state when coupling connections are added, even in small numbers, with effects depending on coupling strength and correlations.
Takeaways & Limitations
The mean field approach does not consider dynamical correlations, producing a systematic shift between theory and simulations that is bounded by a limiting correction.
Abstract
from arXiv · showhide
Many real networks are not isolated from each other but form networks of networks, often interrelated in non trivial ways. Here, we analyze an epidemic spreading process taking place on top of two interconnected complex networks. We develop a heterogeneous mean field approach that allows us to calculate the conditions for the emergence of an endemic state. Interestingly, a global endemic state may arise in the coupled system even though the epidemics is not able to propagate on each network separately, and even when the number of coupling connections is small. Our analytic results are successfully confronted against large-scale numerical simulations.