The impact of multiple information on coupled awareness-epidemic dynamics in multiplex networks

Abstract Growing interest has emerged in the study of the interplay between awareness and epidemics in multiplex networks. However, previous studies on this issue usually assume that all aware individuals take the same level of precautions, ignoring individual heterogeneity. In this paper, we investigate the coupled awareness-epidemic dynamics in multiplex networks considering individual heterogeneity. Here, the precaution levels are heterogeneous and depend on three types of information: contact information and local and global prevalence information. The results show that contact-based precautions can decrease the epidemic prevalence and augment the epidemic threshold, but prevalence-based precautions, regardless of local or global information, can only decrease the epidemic prevalence. Moreover, unlike previous studies in single-layer networks, we do not find a greater impact of local prevalence information on the epidemic prevalence compared to global prevalence information. In addition, we find that the altruistic behaviors of infected individuals can effectively suppress epidemic spreading, especially when the level of contact-based precaution is high.

[1]  Chongjun Fan,et al.  Effect of individual behavior on the interplay between awareness and disease spreading in multiplex networks , 2016 .

[2]  Sergio Gómez,et al.  On the dynamical interplay between awareness and epidemic spreading in multiplex networks , 2013, Physical review letters.

[3]  C. Watkins,et al.  The spread of awareness and its impact on epidemic outbreaks , 2009, Proceedings of the National Academy of Sciences.

[4]  Ming Tang,et al.  Suppression of epidemic spreading in complex networks by local information based behavioral responses , 2014, Chaos.

[5]  Michael Taylor,et al.  Multiple sources and routes of information transmission: Implications for epidemic dynamics. , 2011, Mathematical biosciences.

[6]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[7]  Franco Bagnoli,et al.  Epidemic spreading and risk perception in multiplex networks: A self-organized percolation method. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[8]  C. Scoglio,et al.  An individual-based approach to SIR epidemics in contact networks. , 2011, Journal of theoretical biology.

[9]  Wei Wang,et al.  Unification of theoretical approaches for epidemic spreading on complex networks , 2016, Reports on progress in physics. Physical Society.

[10]  Lewi Stone,et al.  Unexpected epidemic thresholds in heterogeneous networks: the role of disease transmission. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  Neil Ferguson,et al.  Capturing human behaviour , 2007, Nature.

[12]  Sergio Gómez,et al.  Competing spreading processes on multiplex networks: awareness and epidemics , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[13]  Yilun Shang DISCRETE-TIME EPIDEMIC DYNAMICS WITH AWARENESS IN RANDOM NETWORKS , 2013 .

[14]  Xin Jiang,et al.  Two-stage effects of awareness cascade on epidemic spreading in multiplex networks. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  Lin Wang,et al.  Coupled disease–behavior dynamics on complex networks: A review , 2015, Physics of Life Reviews.

[16]  Christos Faloutsos,et al.  Epidemic thresholds in real networks , 2008, TSEC.

[17]  Ming Tang,et al.  Asymmetrically interacting spreading dynamics on complex layered networks , 2014, Scientific Reports.

[18]  Petter Holme,et al.  Solving the Dynamic Correlation Problem of the Susceptible-Infected-Susceptible Model on Networks. , 2016, Physical review letters.

[19]  Piet Van Mieghem,et al.  Generalized Epidemic Mean-Field Model for Spreading Processes Over Multilayer Complex Networks , 2013, IEEE/ACM Transactions on Networking.

[20]  Yilun Shang,et al.  Modeling epidemic spread with awareness and heterogeneous transmission rates in networks , 2013, Journal of biological physics.

[21]  Xin Jiang,et al.  The Role of Node Heterogeneity in the Coupled Spreading of Epidemics and Awareness , 2016, PloS one.

[22]  Jie Zhang,et al.  Community Size Effects on Epidemic Spreading in Multiplex Social Networks , 2016, PloS one.

[23]  Dawei Zhao,et al.  Competing spreading processes and immunization in multiplex networks , 2016, ArXiv.

[24]  Michael Small,et al.  OSCILLATIONS AND PHASE TRANSITION IN THE MEAN INFECTION RATE OF A FINITE POPULATION , 2010 .

[25]  Quan-Hui Liu,et al.  Predicting the epidemic threshold of the susceptible-infected-recovered model , 2015, Scientific Reports.

[26]  Xin Jiang,et al.  Epidemic spreading with activity-driven awareness diffusion on multiplex network , 2016, Chaos.

[27]  Pietro Liò,et al.  Risk perception in epidemic modeling. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Hai-Feng Zhang,et al.  Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - An approach based on multiplex networks , 2015, Communications in Nonlinear Science and Numerical Simulation.

[29]  Michael Small,et al.  The impact of awareness on epidemic spreading in networks , 2012, Chaos.

[30]  Piet Van Mieghem,et al.  Epidemic processes in complex networks , 2014, ArXiv.

[31]  V. Jansen,et al.  Endemic disease, awareness, and local behavioural response. , 2010, Journal of theoretical biology.

[32]  Michael Small,et al.  Threshold analysis of the susceptible-infected-susceptible model on overlay networks , 2014, Commun. Nonlinear Sci. Numer. Simul..

[33]  Matteo Magnani,et al.  Spreading Processes in Multilayer Networks , 2014, IEEE Transactions on Network Science and Engineering.

[34]  Xinchu Fu,et al.  Modelling of discrete-time SIS models with awareness interactions on degree-uncorrelated networks , 2011 .

[35]  Ming Tang,et al.  Impacts of complex behavioral responses on asymmetric interacting spreading dynamics in multiplex networks , 2015, Scientific Reports.

[36]  J. Borge-Holthoefer,et al.  Discrete-time Markov chain approach to contact-based disease spreading in complex networks , 2009, 0907.1313.

[37]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[38]  Ming Tang,et al.  Suppressing disease spreading by using information diffusion on multiplex networks , 2016, Scientific Reports.

[39]  Sergio Gómez,et al.  Nonperturbative heterogeneous mean-field approach to epidemic spreading in complex networks. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  Pietro Liò,et al.  Risk perception and disease spread on social networks , 2010, ICCS.