Research on transmission model of consciousness of prevention and control among the public in major public health emergencies

被引:0
|
作者
Zhu H. [1 ]
Qi J. [1 ,2 ]
Jin Z. [3 ]
Wang J. [4 ]
机构
[1] School of Management, Institute of Artificial Intelligence and Change Management, Shanghai University of International Business and Economics, Shanghai
[2] Key Laboratory of Trustworthy Distributed Computing and Service, Beijing University of Posts and Telecommunications, Beijing
[3] Institute of Complex Systems, Shanxi University, Taiyuan
[4] Law School, Shanghai University of International Business and Economics, Shanghai
基金
中国国家自然科学基金;
关键词
Consciousness of prevention and control transmission; Major public health emergencies; Multiplex networks; Network structure; Threshold;
D O I
10.12011/SETP2020-2176
中图分类号
学科分类号
摘要
COVID-19 epidemic is a major global public health emergency that rarely happened in a century. China has entered the normal stage of epidemic prevention and control after strenuous struggle. Epidemic prevention and control have been promoted synchronously with economic recovery. It is very important that how to realize the effective transmission for epidemic consciousness of prevention and control in the public at this stage of normalization of the epidemic. For this reason, a transmission dynamic model of consciousness of prevention and control in multiplex social networks formed by multiple channels is firstly established. Model analysis and simulation experiments are carried out to draw that it can make the consciousness of prevention and control transmit among public all the time as long as the proportion of owners with consciousness is above a critical value according to the threshold conditions for distinguishing whether the consciousness propagates. It is difficult to quickly raise consciousness of prevention and control for the public that communicating through a single channel. Online and offline multiple information channels are used in a balanced manner in order to maximize the efficiency of transmission. It can promote the transmission of consciousness of prevention and control as much as possible that scientifically and moderately increasing the number of daily communication. Once the number of public communication through multiple channels exceeds a certain limit, it will reduce the efficiency of transmission for consciousness of prevention and control. © 2021, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
引用
收藏
页码:2865 / 2875
页数:10
相关论文
共 25 条
  • [1] Li J J, He S., Population movement, information dissemination efficiency and disease control: Evidence from coronavirus disease 2019, Journal of Central University of Finance Economics, 4, pp. 116-128, (2020)
  • [2] Leonardi P M., Ambient awareness and knowledge acquisition: Using social media to learn "who knows what" and "who knows whom, Mis Quarterly, 39, 4, pp. 747-762, (2015)
  • [3] Mucha P J, Richardson T, Macon K, Et al., Community structure in time-dependent, multiscale, and multiplex networks, Science, 328, 5980, pp. 876-878, (2010)
  • [4] Kurant M, Thiran P., Layered complex networks, Physical Review Letters, 96, 13, (2006)
  • [5] Parshani R, Buldyrev S V, Havlin S., Interdependent networks: Reducing the coupling strength leads to a change from a first to second order percolation transition, Physical Review Letters, 105, 4, (2010)
  • [6] Saumell-Mendiola A, Serrano M, Bogua M., Epidemic spreading on interconnected networks, Physical Review E, 86, 2, (2012)
  • [7] Sun P, Gao L., A fast iterative-clique percolation method for identifying functional modules in protein interaction networks, Frontiers of Computer Ence in China, 3, 3, pp. 405-411, (2009)
  • [8] Kim S., Adaptive call admission control scheme for heterogeneous overlay networks, Journal of Communications and Netwroks, 14, 4, pp. 461-466, (2012)
  • [9] Liu H K, Tang M., A review on global epidemics spreading, Complex Systems and Complexity Science, 8, 3, pp. 86-94, (2011)
  • [10] Dickison M, Havlin S, Stanley H E., Epidemics on interconnected networks, Physical Review E, 85, 2, (2012)