集合种群
计算机科学
马尔可夫链
统计物理学
马尔科夫蒙特卡洛
马尔可夫过程
人口
蒙特卡罗方法
分布式计算
计量经济学
物理
人工智能
数学
机器学习
贝叶斯概率
统计
人口学
生物扩散
社会学
作者
Shupeng Gao,Xiangfeng Dai,Lin Wang,Nicola Perra,Zhen Wang
标识
DOI:10.1109/tcyb.2022.3198732
摘要
Understanding the feedback loop that links the spatiotemporal spread of infectious diseases and human behavior is an open problem. To study this problem, we develop a multiplex framework that couples epidemic spreading across subpopulations in a metapopulation network (i.e., physical layer) with the spreading of awareness about the epidemic in a communication network (i.e., virtual layer). We explicitly study the interactions between the mobility patterns across subpopulations and the awareness propagation among individuals. We analyze the coupled dynamics using microscopic Markov chains (MMCs) equations and validate the theoretical results via Monte Carlo (MC) simulations. We find that with the spreading of awareness, reducing human mobility becomes more effective in mitigating the large-scale epidemic. We also investigate the influence of varying topological features of the physical and virtual layers and the correlation between the connectivity and local population size per subpopulation. Overall the proposed modeling framework and findings contribute to the growing literature investigating the interplay between the spatiotemporal spread of epidemics and human behavior.
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