Analysis of Epidemic Spreading Process in Adaptive Networks

In realistic world, vast majority of networks exhibit layered properties, i.e., the same nodes share different links in each layer (referred as multi-layer networks). Here, the epidemic spreading process on multi-layer networks is investigated, where an infectious yet indistinguishable (as symptoms are not presented) state is considered (i.e., an exposed state). Motived by the fact that subjects are inclined to take preventive measure: cutting potential connection with infection sources during undesirable infections, we consider the epidemic spreading process with such an adaptive framework: a susceptible/exposed individual will disconnect with infected neighbors probabilistically. Once a connection is removed, one new connection will be constructed with uninfected one. The epidemic spreading process will be greatly affected with the adoption of adaptive strategy. Furthermore, we also study the effect of varying community number via incorporating new individuals, and find the consideration of community movement plays an important role in the epidemic re-occurrence. Various benchmarks are analyzed via using the proposed model as well to investigating corresponding spreading behaviors.