Impact of different interaction behavior on epidemic spreading in time-dependent social networks

Social interactions account for the spread of epidemics in population. In this paper, we investigate the impact of pairwise and group interactions on the spread of epidemics through an activity-driven model based on time-dependent networks. The effects of pairwise/group interaction proportion and pairwise/group interaction intensity are explored by extensive simulation and theoretical analysis. It is demonstrated that altering the group interaction proportion can either hinder or enhance the spread of epidemics, depending on the relative social intensity of group and pairwise interactions. As the group interaction proportion decreases, the impact of reducing group social intensity diminishes. The ratio of group and pairwise social intensity can affect the effect of group interaction proportion on the scale of infection. A weak heterogeneous activity distribution can raise the epidemic threshold, and reduce the scale of infection. These results benefit the design of epidemic control strategy.