文献类型：会议论文

英文题名：Distributed Link Removal Strategy for Networked Meta-Population Epidemics and Its Application to the Control of the COVID-19 Pandemic

作者：Liu, Fangzhou[1];Chen, Yuhong[1];Liu, Tong[1];Xue, Dong[2];Buss, Martin[1]

机构：[1]Tech Univ Munich, Dept Elect & Comp Engn, Chair Automat Control Engn LSR, Theresienstr 90, D-80333 Munich, Germany;[2]East China Univ Sci & Technol ECUST, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai, Peoples R China

会议论文集：60th IEEE Conference on Decision and Control (CDC)

会议日期：DEC 13-17, 2021

会议地点：ELECTR NETWORK

语种：英文

外文关键词：Distributed link removal; networked epidemics; controlling of COVID-19 pandemic

摘要：This paper studies the distributed link removal problem for controlling epidemic spreading in a networked meta-population system. A deterministic networked susceptible-infected-recovered (SIR) model is considered to describe the epidemic evolving process. To curb the spread of epidemics, we reformulate the original topology design problem into a minimization program of the Perron-Frobenius eigenvalue of the matrix involving the network topology and transition rates. A modified distributed link removal strategy is developed such that it can be applied to the SIR model with heterogeneous transition rates on weighted digraphs. The proposed approach is implemented to control the COVID-19 pandemic by using the infected and recovered data reported by the German federal states. The numerical experiment shows that the infected percentage can be significantly reduced by employing the distributed link removal strategy.