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Risk Perception and Epidemic Spreading in Multiplex Networks

  • Franco BagnoliEmail author
  • Emanuele Massaro
Part of the Emergence, Complexity and Computation book series (ECC, volume 14)

Abstract

In this paper we study the interplay between epidemic spreading and risk perception on multiplex networks. The basic idea is that the effective infection probability is affected by the perception of the risk of being infected, which we assume to be related to the number of infected neighbours. We re-derive previous results using a self-organized method, that automatically gives the percolation threshold in just one simulation. We then extend the model to multiplex networks considering that people get infected by contacts in real life but often gather information from an information networks, that may be quite different from the real ones. The similarity between the real and information networks determine the possibility of stopping the infection for a sufficiently high precaution level: if the networks are too different there is no mean of avoiding the epidemics.

Keywords

Risk Perception Percolation Threshold Information Network Virtual Network Contact Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Dept. Physics and Astronomy and CSDCUniversity of FlorenceSesto FiorentinoItaly
  2. 2.Risk and Decision Science TeamUS Army Engineer Research and, Development CenterCOncordUSA
  3. 3.Department of Civil and Environmental EngineeringCarnegie Mellon UniversityPittsburghUSA

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