Geographical effects on epidemic spreading in scale-free networks

Abstract

Many real networks are embedded in a metric space: the interactions among individuals depend on their spatial distances and usually take place among their nearest neighbors. In this paper, we introduce a modified susceptible-infected-susceptible (SIS) model to study geographical effects on the spread of diseases by assuming that the probability of a healthy individual infected by an infectious one is inversely proportional to the Euclidean distance between them. It is found that geography plays a more important role than hubs in disease spreading: the more geographically constrained the network is, the more highly the epidemic prevails.

4 pages, 5 figures

References in corpus (2)

• Efficient Immunization Strategies for Computer Networks and Populations
• The spatial structure of networks

Cited by in corpus (3)

• Immunization of Susceptible-Infected Model on Scale-Free networks
• Geographical networks evolving with optimal policy
• An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints