Xu Haidong, Xie Weijie, Han Dun
School of Mathematical Sciences, Jiangsu University, Zhenjiang, Jiangsu 212013, China.
School of Management, Zhenjiang, Jiangsu 212013, China.
Chaos. 2023 Jan;33(1):013110. doi: 10.1063/5.0125969.
Social interactions have become more complicated and changeable under the influence of information technology revolution. We, thereby, propose a multi-layer activity-driven network with attractiveness considering the heterogeneity of activated individual edge numbers, which aims to explore the role of heterogeneous behaviors in the time-varying network. Specifically, three types of individual behaviors are introduced: (i) self-quarantine of infected individuals, (ii) safe social distancing between infected and susceptible individuals, and (iii) information spreading of aware individuals. Epidemic threshold is theoretically derived in terms of the microscopic Markov chain approach and the mean-field approach. The results demonstrate that performing self-quarantine and maintaining safe social distance can effectively raise the epidemic threshold and suppress the spread of diseases. Interestingly, individuals' activity and individuals' attractiveness have an equivalent effect on epidemic threshold under the same condition. In addition, a similar result can be obtained regardless of the activated individual edge numbers. The epidemic outbreak earlier in a situation of the stronger heterogeneity of activated individual edge numbers.
在信息技术革命的影响下，社交互动变得更加复杂多变。因此，考虑到激活个体边数的异质性，我们提出了一个具有吸引力的多层活动驱动网络，旨在探索异质行为在时变网络中的作用。具体而言，引入了三种个体行为：（i）感染个体的自我隔离，（ii）感染个体与易感个体之间的安全社交距离，以及（iii）有认知个体的信息传播。从微观马尔可夫链方法和平均场方法的角度理论推导了流行阈值。结果表明，进行自我隔离和保持安全社交距离可以有效提高流行阈值并抑制疾病传播。有趣的是，在相同条件下，个体的活跃度和个体的吸引力对流行阈值具有同等影响。此外，无论激活个体边数如何，都能得到类似的结果。在激活个体边数异质性较强的情况下，疫情爆发更早。
