The spreading of infectious diseases including COVID-19 depends on human interactions. In an environment where behavioral patterns and physical contacts are constantly evolving according to new governmental regulations, measuring these interactions is a major challenge. Mobility has emerged as an indicator for human activity and, implicitly, for human interactions. Here, we study the coupling between mobility and COVID-19 dynamics and show that variations in global air traffic and local driving mobility can be used to stratify different disease phases. For ten European countries, our study shows a maximal correlation between driving mobility and disease dynamics with a time lag of \(14.6 \pm 5.6\) days. Our findings suggest that trends in local mobility allow us to forecast the outbreak dynamics of COVID-19 for a window of two weeks and adjust local control strategies in real time.

包括 COVID-19 在内的传染病的传播取决于人类的互动。在行为模式和身体接触根据新的政府法规不断发展的环境中，衡量这些互动是一项重大挑战。流动性已成为人类活动的指标，并且隐含地成为人类互动的指标。在这里，我们研究了机动性与 COVID-19 动力学之间的耦合，并表明全球空中交通和本地驾驶机动性的变化可用于对不同的疾病阶段进行分层。对于 10 个欧洲国家，我们的研究显示驾驶流动性与疾病动态之间存在最大相关性，时滞为\(14.6 \pm 5.6\)天。我们的研究结果表明，当地流动性的趋势使我们能够在两周的时间内预测 COVID-19 的爆发动态，并实时调整当地的控制策略。