College of Artificial Intelligence, Southwest University, Chongqing 400715, People's Republic of China.
Chaos. 2022 Aug;32(8):083138. doi: 10.1063/5.0092464.
Recent few years have witnessed a growing interest in exploring the dynamical interplay between awareness and epidemic transmission within the framework of multiplex networks. However, both local and global information have significant impacts on individual awareness and behavior, which have not been adequately characterized in the existing works. To this end, we propose a local and global information controlled spreading model to explore the dynamics of two spreading processes. In the upper layer, we construct a threshold model to describe the awareness diffusion process and introduce local and global awareness information as variables into an individual awareness ratio. In the lower layer, we adopt the classical susceptible-infected-susceptible model to represent the epidemic propagation process and introduce local and global epidemic information into individual precaution degree to reflect individual heterogeneity. Using the microscopic Markov chain approach, we theoretically derive the threshold for epidemic outbreaks. Our findings suggest that the local and global information can motivate individuals to increase self-protection awareness and take more precaution measures, thereby reducing disease infection probability and suppressing the spread of epidemics.
最近几年，人们越来越关注在多重网络框架内探索意识和传染病传播之间的动态相互作用。然而，本地和全球信息对个人意识和行为都有重大影响，这在现有研究中尚未得到充分描述。为此，我们提出了一个本地和全球信息控制传播模型，以探索两个传播过程的动力学。在上层，我们构建了一个阈值模型来描述意识扩散过程，并将本地和全球意识信息作为变量引入个体意识比例中。在下层，我们采用经典的易感染-感染-易感染模型来表示传染病传播过程，并将本地和全球传染病信息引入个体预防程度，以反映个体异质性。通过微观马尔可夫链方法，我们从理论上推导出了传染病爆发的阈值。我们的研究结果表明，本地和全球信息可以激励个人提高自我保护意识并采取更多预防措施，从而降低疾病感染概率并抑制传染病的传播。
