Mechanisms of recoverable prevalence and extinction of viruses on linearly growing scale-free networks

Abstract

We investigate mechanisms of the typically observed recoverable prevalence in epidemic spreading. Assuming the time-independent connectivity correlations, we analyze the dynamics of spreading on linearly growing scale-free (SF) networks, and derive the extinction condition related to the rates of network growth, infection, and immunization of viruses. The behavior is consistent with the previous results for SF networks by a mean-field approximation without connectivity correlations. In particular, it is suggested that the growing must be stopped to prevent the spreading of infection. This insight helps to understand the spreading phenomena on communication or social networks.