文献类型：期刊文献

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]; Zhou, Zibo[1]; Xue, Dong[2]; Buss, Martin[1]

机构：[1] Chair of Automatic Control Engineering [LSR], Department of Electrical and Computer Engineering, Technical University of Munich, Theresienstr. 90, Munich, 80333, Germany; [2] Key Laboratory of Advanced Control and Optimization for Chemical Processes, East China University of Science and Technology, Shanghai, 200237, China

年份：2020

外文期刊名：arXiv

收录：EI(收录号：20200558406)

语种：英文

外文关键词：Epidemiology

摘要：In this paper, we investigate the distributed link removal strategy for networked meta-population epidemics. In particular, a deterministic networked susceptible-infected-recovered (SIR) model is considered to describe the epidemic evolving process. In order to curb the spread of epidemics, we present the spectrum-based optimization problem involving the Perron-Frobenius eigenvalue of the matrix constructed by 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 reported infected and recovered data in each state of Germany. The numerical experiment shows that the infected percentage can be significantly reduced by using the distributed link removal strategy. Copyright ? 2020, The Authors. All rights reserved.