Print Email Facebook Twitter Effect of the interconnected network structure on the epidemic threshold Title Effect of the interconnected network structure on the epidemic threshold Author Wang, H. Li, Q. D'Agostino, G. Havlin, S. Stanley, H.E. Van Mieghem, P. Faculty Electrical Engineering, Mathematics and Computer Science Department Intelligent Systems Date 2013-08-02 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/?1(A+?B), where the infection rate is ? within each of the two individual networks and ?? in the interconnected links between the two networks and ?1(A+?B) is the largest eigenvalue of the matrix A+?B. In order to determine how the epidemic threshold is dependent upon the structure of interconnected networks, we analytically derive ?1(A+?B) using a perturbation approximation for small and large ?, the lower and upper bound for any ? 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 ?1(A+?B) using numerical simulations, and determine how component network features affect ?1(A+?B). We note that, given two isolated networks G1 and G2 with principal eigenvectors x and y, respectively, ?1(A+?B) 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. To reference this document use: http://resolver.tudelft.nl/uuid:0114b1b5-0c35-4ab9-9794-27556fd0ec56 DOI https://doi.org/10.1103/PhysRevE.88.022801 Publisher American Physical Society ISSN 1539-3755 Source http://link.aps.org/doi/10.1103/PhysRevE.88.022801 Source Physical Review E, 88 (2), 2013 Part of collection Institutional Repository Document type journal article Rights © 2013 American Physical Society Files PDF Wang_2013.pdf 365.42 KB Close viewer /islandora/object/uuid:0114b1b5-0c35-4ab9-9794-27556fd0ec56/datastream/OBJ/view