Traffic-driven epidemic spreading in community networks

The development of complex network theory provides new perspectives and ideas for studying the spreading of computer viruses and epidemics. Many real networks have community attributes, and research shows that the traffic flow on the network is closely related to the propagation of the virus. Therefore, we mainly analyze the traffic-driven epidemic spreading dynamics in community networks, reveals the rules and influencing factors of epidemic spreading, and provides reference for the immunization strategy. The results show that under a certain network size, the increase of the number of communities, the increase of the average degree within the community and the increase of the connection probability between the communities will lead to the community structure of the network becoming less obvious, thus promoting the spreading of the epidemic.