DocumentCode :
2904955
Title :
Effect of coupling on the epidemic threshold in interconnected complex networks: A spectral analysis
Author :
Sahneh, Faryad Darabi ; Scoglio, C. ; Chowdhury, Fahmida N.
Author_Institution :
Dept. of Electr. & Comput. Eng., Kansas State Univ., Manhattan, KS, USA
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
2307
Lastpage :
2312
Abstract :
In epidemic spreading models, if the infection strength is higher than a certain critical value - which we define as the epidemic threshold - then the epidemic spreads through the population. For a single arbitrary graph representing the contact network of the population under consideration, the epidemic threshold turns out to be equal to the inverse of the spectral radius of the contact graph. However, in a real world scenario, it is not possible to isolate a population completely: there is always some interconnection with another network, which partially overlaps with the contact network. In this paper, we study the spreading process of a susceptible-infected-susceptible (SIS) epidemic model in an interconnected network of two generic graphs with generic interconnection and different epidemic-related parameters. Using bifurcation theory and spectral graph theory, we find the epidemic threshold of one network as a function of the infection strength of the other coupled network and adjacency matrices of each graph and their interconnection, and provide a quantitative measure to distinguish weak and strong interconnection topology. These results have implications for the broad field of epidemic modeling and control.
Keywords :
bifurcation; complex networks; epidemics; graph theory; network theory (graphs); SIS epidemic model; adjacency matrices; arbitrary graph; bifurcation theory; contact network; coupled network; epidemic spreading models; epidemic threshold; epidemic-related parameters; generic graphs; generic interconnection; infection strength; interconnected complex network; interconnection topology; spectral analysis; spectral graph theory; susceptible-infected-susceptible epidemic model; Couplings; Equations; Mathematical model; Network topology; Sociology; Statistics; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580178
Filename :
6580178
Link To Document :
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