Institute for Scientific Interchange Foundation, Turin, Italy.
Department of Mathematics and GISC, Universidad Carlos III de Madrid, Leganés, Spain.
Nat Hum Behav. 2020 Sep;4(9):964-971. doi: 10.1038/s41562-020-0931-9. Epub 2020 Aug 5.
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.
尽管严格的社交隔离措施已被证明可有效减缓 2019 年冠状病毒病(COVID-19)大流行,但随着限制的解除,第二波疫情可能会出现。在这里,我们将匿名、地理位置定位的移动数据与人口普查和人口数据相结合,建立了一个针对波士顿大都市区严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2)传播的详细基于代理的模型。我们发现,严格的社交隔离措施后,再加上强有力的检测、接触者追踪和家庭隔离,可使疾病保持在医疗体系的承受能力范围内,同时使经济活动重新开放。我们的研究结果表明,在缺乏针对 SARS-CoV-2 的群体免疫力的情况下,基于增强检测和接触者追踪的应对系统可以在放松社交隔离干预方面发挥重要作用。