School of Mathematics and Statistics, Southwest University, Chongqing 400715, China.
Chaos. 2022 Nov;32(11):113141. doi: 10.1063/5.0126799.
In order to better study the interaction between epidemic propagation and information diffusion, a new coupling model on multiplex networks with time delay is put forward in this paper. One layer represents the information diffusion about epidemics. There is not only information about the positive prevention of infectious diseases but also negative preventive information. Meanwhile, the dissemination of information at this layer will be influenced by the mass media, which can convey positive and reliable preventive measures to help the public avoid exposure to contagion. The other layer represents the transmission of infectious diseases, and the public in this layer no longer only exchange information related to infectious diseases in the virtual social network like the information layer but spread infectious diseases through contact among people. The classical SIR model is used to model for epidemic propagation. Since each infected individual needs to spend enough time to recover, the infected one at one time does not necessarily change to the recovered one at the next time, so time delay is an essential factor to be considered in the model. Based on the microscopic Markov chain approach, this paper obtains an explicit expression for epidemic threshold in the two-layered multiplex networks with time delay, which reveals some main factors affecting epidemic threshold. In particular, the time delay has a noticeable effect on the epidemic threshold to some extent. Finally, the influence of these main factors on the epidemic threshold and their interaction are proved through numerical simulations.
为了更好地研究传染病传播与信息扩散之间的相互作用,本文提出了一种具有时滞的双层网络的新型耦合模型。其中一层表示传染病的信息扩散,不仅有关于传染病积极预防的信息,还有负面的预防信息。同时,这一层的信息传播会受到大众媒体的影响,大众媒体可以传播积极可靠的预防措施,帮助公众避免接触传染病。另一层表示传染病的传播,这一层的公众不再仅仅在像信息层这样的虚拟社交网络中交换与传染病相关的信息,而是通过人与人之间的接触传播传染病。本文使用经典的 SIR 模型来模拟传染病的传播。由于每个受感染的个体都需要足够的时间来康复,所以在同一时间被感染的人不一定在下一个时间就会康复,因此时滞是模型中需要考虑的一个重要因素。基于微观马尔可夫链方法,本文得到了具有时滞的双层网络中传染病阈值的显式表达式,揭示了影响传染病阈值的一些主要因素。特别是,时滞在一定程度上对传染病阈值有显著影响。最后,通过数值模拟验证了这些主要因素对传染病阈值的影响及其相互作用。