Epidemics on Random Graphs with Tunable Clustering
By Tom Britton, Maria Deijfen, Andreas N. Lagerås, M. Lindholm. Journal of Applied Probability, 2007
97 citations recorded by the source corpus.
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.
Subfields: Mathematical Physics, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/10bd730e2ad14b271584903bc7119c30ecf6d6ff
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In Mathematical Physics
In Statistical and Nonlinear Physics
Citations in the corpus
- Dynamics and Control of Diseases in Networks with Community Structure (2010, background): “the fraction of closed triplets in a contact network) [20,21,22,23,24].”