How the heterogeneous infection rate effect on the epidemic spreading in activity-driven network

Abstract

In this paper, we research the impact of the heterogeneous infection rate on the epidemic spread in the activity-driven networks. By using the mean field approximation, the epidemic threshold is theoretically obtained. Several immunization strategies that could curb the epidemic spread are presented. Based on the theoretical analysis and simulation results, we obtain that the epidemic would be prevented effectively if the infection rate strongly correlates with the individual activity. However, if infection rate has a little correlation with the individual activity, most of the individuals may be infected. In addition, the epidemic can be suppressed soon if the individuals with high activity are immunized preferentially.