title: Community Size Effects on Epidemic Spreading in Multiplex Social Networks.
abstract: The dynamical process of epidemic spreading has drawn much attention of the complex network community. In the network paradigm, diseases spread from one person to another through the social ties amongst the population. There are a variety of factors that govern the processes of disease spreading on the networks. A common but not negligible factor is people's reaction to the outbreak of epidemics. Such reaction can be related information dissemination or self-protection. In this work, we explore the interactions between disease spreading and population response in terms of information diffusion and individuals' alertness. We model the system by mapping multiplex networks into two-layer networks and incorporating individuals' risk awareness, on the assumption that their response to the disease spreading depends on the size of the community they belong to. By comparing the final incidence of diseases in multiplex networks, we find that there is considerable mitigation of diseases spreading for full phase of spreading speed when individuals' protection responses are introduced. Interestingly, the degree of community overlap between the two layers is found to be critical factor that affects the final incidence. We also analyze the consequences of the epidemic incidence in communities with different sizes and the impacts of community overlap between two layers. Specifically, as the diseases information makes individuals alert and take measures to prevent the diseases, the effective protection is more striking in small community. These phenomena can be explained by the multiplexity of the networked system and the competition between two spreading processes.
authors.affiliation: Center for Intelligent and Networked Systems, School of Computer Science, Southwest Petroleum University, Chengdu 610500, China.
authors.forename: Ting
authors.initials: T
authors.lastname: Liu
authors.affiliation: Center for Intelligent and Networked Systems, School of Computer Science, Southwest Petroleum University, Chengdu 610500, China.
authors.forename: Ping
authors.initials: P
authors.lastname: Li
authors.affiliation: Center for Intelligent and Networked Systems, School of Computer Science, Southwest Petroleum University, Chengdu 610500, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Center for Computational Systems Biology, Fudan University, Shanghai 200433, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
mesh_terms: D018562:Disease Transmission, Infectious / Q000706:statistics & numerical data*; D058872:Epidemics / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D011156:Population Density; D012111:Residence Characteristics; D012931:Social Environment