While severe social-distancing measures have proven effective in slowing the coronavirus disease 2019 (COVID-19) pandemic, second-wave scenarios are likely to emerge as restrictions are lifted. Here we integrate anonymized, geolocalized mobility data with census and demographic data to build a detailed agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in the Boston metropolitan area. We find that a period of strict social distancing followed by a robust level of testing, contact-tracing and household quarantine could keep the disease within the capacity of the healthcare system while enabling the reopening of economic activities. Our results show that a response system based on enhanced testing and contact tracing can have a major role in relaxing social-distancing interventions in the absence of herd immunity against SARS-CoV-2.

虽然严格的社交距离措施已被证明可以有效减缓 2019 年冠状病毒病 (COVID-19) 的流行，但随着限制的取消，第二波情况可能会出现。在这里，我们将匿名的地理定位移动数据与人口普查和人口统计数据相结合，构建了波士顿大都市区严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 传播的详细的基于代理的模型。我们发现，一段时期的严格社会隔离，随后进行高水平的检测、接触者追踪和家庭隔离，可以将疾病控制在医疗系统的承受范围内，同时使经济活动能够重新开放。我们的结果表明，在缺乏针对 SARS-CoV-2 的群体免疫力的情况下，基于加强检测和接触者追踪的响应系统可以在放松社交距离干预方面发挥重要作用。