Infection spreading, detection and control in community networks

Community structures widely exist in various complex networks. Extensive studies have been carried out on defining and quantifying community structures as well as developing algorithms for detecting them in extra-large complex systems. Despite all these efforts, however, our understanding of why community structures widely exist in so many real-life systems, or in other words, the benefits/drawbacks for real-life systems to have community structures, remains to be rather limited. In this work, we discuss on the effects of community structures on infection propagation, detection and control in complex networks. Specifically, we investigate (i) the effects of community structures on transmission speed and infection size; (ii) when monitors can be deployed in the network to detect the infection spreading, the effects of community structures on early-stage infection detection; and (iii) in adaptive networks with link rewiring for isolating the infected nodes, the effects of community structures on infection control. Our results show that the existence of community structures generally speaking helps slow down the infection spreading; whether it helps reduce the overall infection size when no control method is adopted however depends on the network topology. When infection detection and controlling methods such as link rewiring are adopted, the existence of community structures steadily helps improve the efficiency of infection detection and control, though having too many communities may not necessarily bring along additional benefits.