Literature DB >> 28884277

Global stability for epidemic models on multiplex networks.

Yu-Jhe Huang1, Jonq Juang2, Yu-Hao Liang1, Hsin-Yu Wang1.   

Abstract

In this work, we consider an epidemic model in a two-layer network in which the dynamics of susceptible-infected-susceptible process in the physical layer coexists with that of a cyclic process of unaware-aware-unaware in the virtual layer. For such multiplex network, we shall define the basic reproduction number [Formula: see text] in the virtual layer, which is similar to the basic reproduction number [Formula: see text] defined in the physical layer. We show analytically that if [Formula: see text] and [Formula: see text], then the disease and information free equilibrium is globally stable and if [Formula: see text] and [Formula: see text], then the disease free and information saturated equilibrium is globally stable for all initial conditions except at the origin. In the case of [Formula: see text], whether the disease dies out or not depends on the competition between how well the information is transmitted in the virtual layer and how contagious the disease is in the physical layer. In particular, it is numerically demonstrated that if the difference in [Formula: see text] and [Formula: see text] is greater than the product of [Formula: see text], the deviation of [Formula: see text] from 1 and the relative infection rate for an aware susceptible individual, then the disease dies out. Otherwise, the disease breaks out.

Entities:  

Keywords:  Awareness; Epidemic models; Global stability; Multiplex networks; The basic reproduction number

Mesh:

Year:  2017        PMID: 28884277     DOI: 10.1007/s00285-017-1179-5

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  26 in total

1.  Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission.

Authors:  P van den Driessche; James Watmough
Journal:  Math Biosci       Date:  2002 Nov-Dec       Impact factor: 2.144

2.  Halting viruses in scale-free networks.

Authors:  Zoltán Dezso; Albert-László Barabási
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-05-21

3.  Epidemic spreading in correlated complex networks.

Authors:  Marián Boguñá; Romualdo Pastor-Satorras
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-10-21

4.  Community structure in time-dependent, multiscale, and multiplex networks.

Authors:  Peter J Mucha; Thomas Richardson; Kevin Macon; Mason A Porter; Jukka-Pekka Onnela
Journal:  Science       Date:  2010-05-14       Impact factor: 47.728

Review 5.  Modelling the influence of human behaviour on the spread of infectious diseases: a review.

Authors:  Sebastian Funk; Marcel Salathé; Vincent A A Jansen
Journal:  J R Soc Interface       Date:  2010-05-26       Impact factor: 4.118

6.  Epidemic spreading in a hierarchical social network.

Authors:  A Grabowski; R A Kosiński
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2004-09-21

7.  Dynamical interplay between awareness and epidemic spreading in multiplex networks.

Authors:  Clara Granell; Sergio Gómez; Alex Arenas
Journal:  Phys Rev Lett       Date:  2013-09-17       Impact factor: 9.161

8.  Diffusion dynamics on multiplex networks.

Authors:  S Gómez; A Díaz-Guilera; J Gómez-Gardeñes; C J Pérez-Vicente; Y Moreno; A Arenas
Journal:  Phys Rev Lett       Date:  2013-01-08       Impact factor: 9.161

9.  The impact of awareness on epidemic spreading in networks.

Authors:  Qingchu Wu; Xinchu Fu; Michael Small; Xin-Jian Xu
Journal:  Chaos       Date:  2012-03       Impact factor: 3.642

10.  Responsive immunization and intervention for infectious diseases in social networks.

Authors:  Qingchu Wu; Haifeng Zhang; Guanghong Zeng
Journal:  Chaos       Date:  2014-06       Impact factor: 3.642

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