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.

中文翻译：

---

网络元种群流行病的分布式链接删除策略及其在控制 COVID-19 大流行中的应用

在本文中，我们研究了网络元种群流行病的分布式链接删除策略。特别是，确定性网络易感感染恢复（SIR）模型被认为是描述流行病演变过程。为了遏制流行病的传播，我们提出了基于频谱的优化问题，该问题涉及由网络拓扑和转换率构建的矩阵的 Perron-Frobenius 特征值。开发了一种改进的分布式链路去除策略，以便它可以应用于在加权有向图中具有异构转换率的 SIR 模型。所提议的方法是通过使用德国每个州报告的感染和恢复数据来控制 COVID-19 大流行的。