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用于在多个社交网络上控制流行病传播的三层模型。

Three-layer model for the control of epidemic infection over multiple social networks.

作者信息

Nasir Ali

机构信息

Control and Instrumentation Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.

Interdisciplinary Research Center for Intelligent Manufacturing and Robotics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.

出版信息

SN Appl Sci. 2023;5(5):152. doi: 10.1007/s42452-023-05373-0. Epub 2023 Apr 29.

Abstract

ABSTRACT

This paper presents a hierarchical approach for controlling the spread of an epidemic disease. The approach consists of a three-layer architecture where a set of two-layer multiple social networks is governed by a (third) top-layer consisting of an optimal control policy. Each of the two-layer social networks is modeled by a microscopic Markov chain. On top of all the two-layer networks is an optimal control policy that has been developed by using an underlying Markov Decision Process (MDP) model. Mathematical models pertaining to the top-level MDP as well as two-layer microscopic Markov chains have been presented. Practical implementation methodology using the proposed models has also been discussed along with a numerical example. The results in the numerical example illustrate the control of an epidemic using the optimal policy. Directions for further research and characterization of the optimal policy have also been discussed with the help of the same numerical example.

ARTICLE HIGHLIGHTS

An optimal approach for controlling the spread of an epidemic infection.The approach is able to model the uncertainties involved in the problem.The approach is able to cater for the underlying social network.

摘要

摘要

本文提出了一种用于控制传染病传播的分层方法。该方法由三层架构组成,其中一组双层多重社交网络由(第三层)顶层的最优控制策略管理。每个双层社交网络都由微观马尔可夫链建模。在所有双层网络之上是通过使用基础马尔可夫决策过程(MDP)模型开发的最优控制策略。给出了与顶层MDP以及双层微观马尔可夫链相关的数学模型。还讨论了使用所提出模型的实际实施方法以及一个数值示例。数值示例中的结果说明了使用最优策略对传染病的控制。借助同一个数值示例,还讨论了进一步研究的方向以及最优策略的特征。

文章亮点

一种控制传染病传播的最优方法。该方法能够对问题中涉及的不确定性进行建模。该方法能够适应基础社交网络。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f565/10148634/647824211642/42452_2023_5373_Fig1_HTML.jpg

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