Journal of Applied Probability

Epidemics on random graphs with tunable clustering

Tom Britton, Maria Deijfen, Andreas N. Lagerås, and Mathias Lindholm

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Abstract

In this paper a branching process approximation for the spread of a Reed-Frost epidemic on a network with tunable clustering is derived. The approximation gives rise to expressions for the epidemic threshold and the probability of a large outbreak in the epidemic. We investigate how these quantities vary with the clustering in the graph and find that, as the clustering increases, the epidemic threshold decreases. The network is modeled by a random intersection graph, in which individuals are independently members of a number of groups and two individuals are linked to each other if and only if there is at least one group that they are both members of.

Article information

Source
J. Appl. Probab. Volume 45, Number 3 (2008), 743-756.

Dates
First available in Project Euclid: 26 September 2008

Permanent link to this document
http://projecteuclid.org/euclid.jap/1222441827

Digital Object Identifier
doi:10.1239/jap/1222441827

Mathematical Reviews number (MathSciNet)
MR2455182

Zentralblatt MATH identifier
1147.92034

Subjects
Primary: 92D30: Epidemiology 05C80: Random graphs [See also 60B20]

Keywords
Epidemics random graph clustering branching process epidemic threshold

Citation

Britton, Tom; Deijfen, Maria; Lagerås, Andreas N.; Lindholm, Mathias. Epidemics on random graphs with tunable clustering. J. Appl. Probab. 45 (2008), no. 3, 743--756. doi:10.1239/jap/1222441827. http://projecteuclid.org/euclid.jap/1222441827.


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