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 fraction of infected neighbors, as introduced by Bagnoli et al. [Phys. Rev. E 76, 061904 (2007)]. We rederive 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 physical contacts in real life but often gather information from an information network, which may be quite different from the physical ones. The similarity between the physical and the information networks determines the possibility of stopping the infection for a sufficiently high precaution level: if the networks are too different, there is no means of avoiding the epidemics.

Epidemic spreading and risk perception in multiplex networks: A self-organized percolation method / E. Massaro;F. Bagnoli. - In: PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS. - ISSN 1539-3755. - STAMPA. - 90:(2014), pp. 052817-1-052817-8. [10.1103/PhysRevE.90.052817]

Epidemic spreading and risk perception in multiplex networks: A self-organized percolation method

MASSARO, EMANUELE;BAGNOLI, FRANCO
2014

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 fraction of infected neighbors, as introduced by Bagnoli et al. [Phys. Rev. E 76, 061904 (2007)]. We rederive 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 physical contacts in real life but often gather information from an information network, which may be quite different from the physical ones. The similarity between the physical and the information networks determines the possibility of stopping the infection for a sufficiently high precaution level: if the networks are too different, there is no means of avoiding the epidemics.
2014
90
052817-1
052817-8
E. Massaro;F. Bagnoli
File in questo prodotto:
File Dimensione Formato  
MassaroBagnoli-Epidemic spreading and risk perception in multiplex networks: A self-organized percolation method-PhysRevE.90.052817.pdf

Accesso chiuso

Tipologia: Versione finale referata (Postprint, Accepted manuscript)
Licenza: DRM non definito
Dimensione 711.16 kB
Formato Adobe PDF
711.16 kB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/937733
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 80
  • ???jsp.display-item.citation.isi??? 69
social impact