When considering airborne epidemic spreading in social systems, a natural connection arises between mobility and epidemic contacts. As individuals travel, possibilities to encounter new people either at the final destination or during the transportation process appear. Such contacts can lead to new contagion events. In fact, mobility has been a crucial target for early non-pharmaceutical containment measures against the recent COVID-19 pandemic, with a degree of intensity ranging from public transportation line closures to regional, city or even home confinements. Nonetheless, quantitative knowledge on the relationship between mobility-contagions and, consequently, on the efficiency of containment measures remains elusive. Here we introduce an agent-based model with a simple interaction between mobility and contacts. Despite its simplicity our model shows the emergence of a critical mobility level, inducing major outbreaks when surpassed. We explore the interplay between mobility restrictions and the infection in recent intervention policies seen across many countries, and how interventions in the form of closures triggered by incidence rates can guide the epidemic into an oscillatory regime with recurrent waves. We consider how the different interventions impact societal well-being, the economy and the population. Finally, we propose a mitigation framework based on the critical nature of mobility in an epidemic, able to suppress incidence and oscillations at will, preventing extreme incidence peaks with potential to saturate health care resources.

翻译：考虑社会系统中的空气传播流行病时，流动性（mobility）与流行病接触之间存在着天然的联系。随着个体移动，在最终目的地或运输过程中都可能遇到新的人群，这种接触可能导致新的传染事件。事实上，流动性已成为应对近期COVID-19疫情早期非药物防控措施的关键目标，其强度从公共交通线路关闭到区域、城市甚至居家隔离各不相同。然而，关于流动性-传染之间关系的定量知识，以及由此产生的防控措施效率，仍然难以捉摸。本文引入了一个基于智能体的模型，该模型具有流动性与接触之间的简单相互作用。尽管模型简洁，但它揭示了关键流动性水平的出现，当超过这一水平时会导致重大疫情暴发。我们探讨了许多国家近期干预政策中流动性限制与感染之间的相互作用，以及由发病率触发的封锁式干预如何引导流行病进入具有反复波动特征的振荡模式。我们考虑了不同干预措施对社会福祉、经济和人口的影响。最后，我们提出了一种基于流行病中流动性关键性质的缓解框架，能够任意抑制发病率和振荡，防止可能使医疗资源饱和的极端发病高峰。