Percolation in clustered networks
arXiv:0904.3253
Abstract
The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied clustered networks, but the networks often contain preferential mixing between high degree nodes. We introduce a class of random clustered networks and another class of random unclustered networks with the same preferential mixing. We analytically show that percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks.
The first version is being separated into multiple papers. This is the first of these to be submitted
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