The Effect of Population Flow on Epidemic Spread: Analysis and Control
The Effect of Population Flow on Epidemic Spread: Analysis and Control
复制标题
DOI：
10.1109/cdc45484.2021.9683081
复制
发表时间：
2021-04
期刊：
影响因子：
--
通讯作者：
Brooks A. Butler;Ciyuan Zhang;I. Walter;N. Nair;Raphael E. Stern;Philip E. Par'e
中科院分区：
文献类型：
--
作者：
Brooks A. Butler;Ciyuan Zhang;I. Walter;N. Nair;Raphael E. Stern;Philip E. Par'e
在本文中，我们提出了一个离散时间网络SEIR模型，人口流，它的推导，并假设下，这个模型是很好地定义。我们确定系统的平衡，即健康状态的属性。我们表明，健康状态的集合是渐近稳定的，并且由于网络流模型的结果，平衡值在所有子群体中变得相等。此外，我们探讨了闭环反馈控制的系统，通过限制子种群之间的流量作为当前感染状态的函数。这些结果通过基于美国主要机场之间的航班流量的模拟来说明。我们发现，考虑到最初的流量限制反应没有延迟，与疫苗推出相结合的流量限制策略显着减少了在流行病过程中的感染总数。
In this paper, we present a discrete-time networked SEIR model using population flow, its derivation, and assumptions under which this model is well defined. We identify properties of the system’s equilibria, namely the healthy states. We show that the set of healthy states is asymptotically stable, and that the value of the equilibria becomes equal across all sub-populations as a result of the network flow model. Furthermore, we explore closed-loop feedback control of the system by limiting flow between sub-populations as a function of the current infected states. These results are illustrated via simulation based on flight traffic between major airports in the United States. We find that a flow restriction strategy combined with a vaccine roll-out significantly reduces the total number of infections over the course of an epidemic, given that the initial flow restriction response is not delayed.