2020/06/29 by Fangzhou Liu, Yuhong Chen, Liu, Fangzhou +9
Computer Science · Engineering · Mathematics · Physics and Astronomy · #COVID-19 epidemiological studies #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Electrical engineering #FOS: Physical sciences #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Systems and Control (eess.SY) #cs.SI #cs.SY #eess.SY #electronic engineering #information engineering #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.2006.16221
arxiv created 2020/06/29 · openalex publication_date 2020/06/29 · arxiv updated 2020/06/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.