Epidemic Dynamics in Weighted Adaptive Networks

Adaptive networks are common in real world, describing networks whose links change adaptively with respect to its states, resulting in a dynamical interplay between the state and the topology of the network. Recently, it is demonstrated that the diversity in the interaction intensity is also the crucial feature that reflects the complexity. In fact, when topology alters, the strengths of the connections between nodes change accordingly. Here we propose a weighted adaptive network model, in which the network topology, nodes status and the weights interact mutually. Furthermore, we also study the epidemic dynamics in weighted adaptive networks, and two rewiring strategies based on weights are presented and proved to be well performed on preventing the spread of the disease.