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Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents

Lingling Xia1, Bo Song2,3, Zhengjun Jing4, Yurong Song5,*, Liang Zhang1
Department of Computer Information and Cyber Security, Jiangsu Police Institute, Nanjing, 210031, China.
College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China.
Global Big Data Technologies Centre, University of Technology Sydney, Sydney, 2007, Australia.
College of Computer Engineering, Jiangsu University of Technology, Changzhou, 213001, China.
College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China.
* Corresponding Author: Yu-Rong Song. Email: .

Computers, Materials & Continua 2018, 57(1), 123-144. https://doi.org/10.32604/cmc.2018.03738

Abstract

Considering dynamical disease spreading network consisting of moving individuals, a new double-layer network is constructed, one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves. On the basis of Markov chains theory, a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment. Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence spreading dynamics. Simulation results show that the increasing of information transmission rate can reduce the scale of disease spreading in some degree. Shortening infection period and strengthening consciousness for self-protection by decreasing individual’s scope of activity both can effectively reduce the final refractory density for the disease but have less effect on the information dissemination. In addition, the increasing of vaccination rate or decreasing of long-range travel can also reduce the scale of disease spreading.

Keywords

Complex networks, Markov chains theory, interaction process, spreading dynamics, double-layer network.

Cite This Article

L. Xia, B. Song, Z. Jing, Y. Song and L. Zhang, "Dynamical interaction between information and disease spreading in populations of moving agents," Computers, Materials & Continua, vol. 57, no.1, pp. 123–144, 2018.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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