Effect of the interconnected network structure on the epidemic threshold

Huijuan Wang, Qian Li, Gregorio D’Agostino, Shlomo Havlin, H. Eugene Stanley, and Piet Van Mieghem
Phys. Rev. E 88, 022801 – Published 2 August 2013

Abstract

Most real-world networks are not isolated. In order to function fully, they are interconnected with other networks, and this interconnection influences their dynamic processes. For example, when the spread of a disease involves two species, the dynamics of the spread within each species (the contact network) differs from that of the spread between the two species (the interconnected network). We model two generic interconnected networks using two adjacency matrices, A and B, in which A is a 2N×2N matrix that depicts the connectivity within each of two networks of size N, and B a 2N×2N matrix that depicts the interconnections between the two. Using an N-intertwined mean-field approximation, we determine that a critical susceptible-infected-susceptible (SIS) epidemic threshold in two interconnected networks is 1/λ1(A+αB), where the infection rate is β within each of the two individual networks and αβ in the interconnected links between the two networks and λ1(A+αB) is the largest eigenvalue of the matrix A+αB. In order to determine how the epidemic threshold is dependent upon the structure of interconnected networks, we analytically derive λ1(A+αB) using a perturbation approximation for small and large α, the lower and upper bound for any α as a function of the adjacency matrix of the two individual networks, and the interconnections between the two and their largest eigenvalues and eigenvectors. We verify these approximation and boundary values for λ1(A+αB) using numerical simulations, and determine how component network features affect λ1(A+αB). We note that, given two isolated networks G1 and G2 with principal eigenvectors x and y, respectively, λ1(A+αB) tends to be higher when nodes i and j with a higher eigenvector component product xiyj are interconnected. This finding suggests essential insights into ways of designing interconnected networks to be robust against epidemics.

  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Received 22 March 2013

DOI:https://doi.org/10.1103/PhysRevE.88.022801

©2013 American Physical Society

Authors & Affiliations

Huijuan Wang1,2,*, Qian Li2, Gregorio D’Agostino3, Shlomo Havlin4, H. Eugene Stanley2, and Piet Van Mieghem1

  • 1Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, The Netherlands
  • 2Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA
  • 3ENEA, “Casaccia” Research Center, Via Anguillarese 301, I-00123 Roma, Italy
  • 4Department of Physics, Bar-Ilan University, 52900 Ramat-Gan, Israel

  • *H.Wang@tudelft.nl

Article Text (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 88, Iss. 2 — August 2013

Reuse & Permissions
Access Options
CHORUS

Article Available via CHORUS

Download Accepted Manuscript
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review E

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×