Controlling epidemic outbreaks and public sentiment spreading by vaccination in complex network

In this paper, an overview of vaccination methods addressing in suppressing the epidemic spreading is given, focusing on modeling the epidemic and public sentiment spreading from real world scenarios, describing models of dynamic spreading, and presenting vaccination strategies and their efficiency. Simulation results on empirical networks and model networks using different vaccination strategies show that vaccination strategies such as centrality-based vaccination, graph partition-based vaccination and acquaintance vaccination are more effective than random vaccination. This implies that vaccination strategy is important and meaningful in suppressing epidemic spreading. In order to reach a better control result, the topological structure and the completeness of network information should be taken into account when choosing a vaccination strategy.