Motivated by the challenge related to the COVID-19 epidemic and the seek for optimal containment strategies, we present a robustness analysis into an inter-cities mobility complex network. We abstract municipal initiatives as nodes' failures and the federal actions as targeted attacks. The geo(graphs) approach is applied to visualize the geographical graph and produce maps of topological indexes, such as degree and vulnerability. A Brazilian data of 2016 is considered a case study, with more than five thousand cities and twenty-seven states. Based on the Network Robustness index, we show that the most efficient attack strategy shifts from a topological degree-based, for the all cities network, to a topological vulnerability-based, for a network considering the Brazilian States as nodes. Moreover, our results reveal that individual municipalities' actions do not cause a high impact on mobility restrain since they tend to be punctual and disconnected to the country scene as a whole. Oppositely, the coordinated isolation of specific cities is key to detach entire network areas and thus prevent a spreading process to prevail.

中文翻译：

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城市间移动网络的稳健性分析：将市政、州和联邦举措建模为失败和攻击

在与 COVID-19 流行相关的挑战和寻求最佳遏制策略的推动下，我们对城市间移动复杂网络进行了稳健性分析。我们将市政举措抽象为节点的故障，将联邦行动抽象为有针对性的攻击。geo(graphs) 方法用于可视化地理图并生成拓扑索引图，例如程度和脆弱性。巴西 2016 年的数据被视为案例研究，涉及 5000 多个城市和 27 个州。基于网络鲁棒性指数，我们表明最有效的攻击策略从针对所有城市网络的基于拓扑度的攻击转变为基于拓扑脆弱性的基于巴西国家作为节点的网络。而且，我们的结果表明，个别城市的行动不会对流动性限制产生很大的影响，因为它们往往是准时的，并且与整个乡村场景脱节。相反，特定城市的协调隔离是分离整个网络区域的关键，从而防止传播过程盛行。