Change points, memory and epidemic spreading in temporal networks

Change points, memory and epidemic spreading in temporal networks

Dynamic networks exhibit temporal patterns that vary across different time scales, all of which can potentially affect processes that take place on the network. However, most data-driven approaches used to model timevarying networks attempt to capture only a single characteristic time scale in isolation — typically associated with the short-time memory of a Markov chain or with long-time abrupt...

Epidemic Spreading and Complex Networks

Epidemic spreading in evolving networks.

A model for epidemic spreading on rewiring networks is introduced and analyzed for the case of scale free steady state networks. It is found that contrary to what one would have naively expected, the rewiring process typically tends to suppress epidemic spreading. In particular it is found, that as in static networks under a mean-field approximation, rewiring networks with degree distribution e...

Epidemic Spreading in Technological Networks

computer security, viruses, worms, infection models, scale-free networks, small world networks, epidemiology, BICAS Recent computer worms pose a major threat to large computer networks, and it is a general belief that understanding their means of propagation will help to devise efficient control strategies. This dissertation proposes a new epidemiological model to account for particular charact...

Epidemic spreading on interconnected networks

Many real networks are not isolated from each other but form networks of networks, often interrelated in nontrivial ways. Here, we analyze an epidemic spreading process taking place on top of two interconnected complex networks. We develop a heterogeneous mean-field approach that allows us to calculate the conditions for the emergence of an endemic state. Interestingly, a global endemic state m...