National stay-at-home orders, or lockdowns, were imposed in several countries to drastically reduce the social interactions mainly responsible for the transmission of the SARS-CoV-2 virus. Despite being essential to slow down the COVID-19 pandemic, these containment measures are associated with an economic burden. In this work, we propose a network approach to model the implementation of a partial lockdown, breaking the society into disconnected components, or partitions. Our model is composed by two main ingredients: a multiplex network representing human contacts within different contexts, formed by a Household layer, a Work layer, and a Social layer including generic social interactions, and a Susceptible-Infected-Recovered process that mimics the epidemic spreading. We compare different partition strategies, with a twofold aim: reducing the epidemic outbreak and minimizing the economic cost associated to the partial lockdown. We also show that the inclusion of unconstrained social interactions dramatically increases the epidemic spreading, while different kinds of restrictions on social interactions help in keeping the benefices of the network partition.

一些国家实施了全国性的居家令或封锁，以大幅减少主要导致 SARS-CoV-2 病毒传播的社会互动。尽管对于减缓 COVID-19 大流行至关重要，但这些遏制措施与经济负担有关。在这项工作中，我们提出了一种网络方法来模拟部分锁定的实施，将社会分解为不相连的组件或分区。我们的模型由两个主要组成部分组成：一个表示不同上下文中的人类接触的多重网络，由一个家庭层、一个工作层和一个包括通用社交互动的社交层组成，以及一个模拟流行病的易感-感染-恢复过程传播。我们比较不同的分区策略，有两个目的：减少流行病的爆发并最大限度地减少与部分封锁相关的经济成本。我们还表明，不受约束的社交互动的包含极大地增加了流行病的传播，而对社交互动的不同类型的限制有助于保持网络分区的好处。