## Journal of Applied Probability

### Epidemics on random graphs with tunable clustering

#### 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

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

#### 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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