Geodesic
Epidemic spreading and risk perception in multiplex networks: a self-organized percolation method
E. Massaro1 ; F. Bagnoli2
1 Risk and Decision Science Team, US Army Engineer Research and Development Center, 696 Virginia Rd., Concord, MA 01742, and Department of Civil and Environmental Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213;
2 Dipartimento di Fisica ed Astronomia and CSDC, Università degli Studi di Firenze, via G. Sansone 1, 50019 Sesto Fiorentino, Italy. Also INFN, Sez. di Firenze.
ESAIM. Proceedings, Tome 49 (2015), pp. 53-64.

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The contribution of this paper is twofold. First, we develop a self-organized method which is able the evaluate the percolation threshold of the SIS dynamics in general networks by comparing computational results with theoretical ones. Then, we apply this method to the case of risk perception in which the probability of being infected is reduced by a component which is function of the information about the disease. We then study the interplay between epidemic spreading and risk perception on multiplex networks. The system is represented by two layers: one representing the physical contacts and the other one the virtual contacts in which people exchange information and become aware of the disease. The final contribution of this paper is to comprehend the effectiveness of the source of information in modelling the risk perception in epidemic modelling: we found that the similarity between the physical and the 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.
DOI : 10.1051/proc/201549005

E. Massaro 1 ; F. Bagnoli 2

1 Risk and Decision Science Team, US Army Engineer Research and Development Center, 696 Virginia Rd., Concord, MA 01742, and Department of Civil and Environmental Engineering, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213;
2 Dipartimento di Fisica ed Astronomia and CSDC, Università degli Studi di Firenze, via G. Sansone 1, 50019 Sesto Fiorentino, Italy. Also INFN, Sez. di Firenze. 
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     author = {E. Massaro and F. Bagnoli},
     title = {Epidemic spreading and risk perception in multiplex networks: a self-organized percolation method},
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E. Massaro; F. Bagnoli. Epidemic spreading and risk perception in multiplex networks: a self-organized percolation method. ESAIM. Proceedings, Tome 49 (2015), pp. 53-64. doi : 10.1051/proc/201549005. http://geodesic.mathdoc.fr/articles/10.1051/proc/201549005/

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