Epidemic spreading in time-varying networks with activity-driven infectivity

In epidemic models, the infectivity of a node refers to the number of its connections through which virus can spread out. Previous works mostly assumed that the infectivity of a node equals to its degree. However, this hypothesis cannot describe all contagion processes appropriately. In this work, we explore the epidemic spreading in time-varying networks, where the infectivity of a node might be independent of its degree. We study the correlations between infectivity and activity, deduce the expression of epidemic threshold, and focus on how the correlation affects the epidemic threshold. We find that the epidemic threshold increases significantly under some situations and give explanations for the phenomenon. The analytical results are verified by numerical simulations.