Nielsen Bjarke Frost, Sneppen Kim, Simonsen Lone, Mathiesen Joachim
Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen, Denmark.
Department of Science and Environment, Roskilde University, 4000 Roskilde, Denmark.
Eur Phys J B. 2021;94(10):209. doi: 10.1140/epjb/s10051-021-00222-8. Epub 2021 Oct 19.
Digital contact tracing has been suggested as an effective strategy for controlling an epidemic without severely limiting personal mobility. Here, we use smartphone proximity data to explore how social structure affects contact tracing of COVID-19. We model the spread of COVID-19 and find that the effectiveness of contact tracing depends strongly on social network structure and heterogeneous social activity. Contact tracing is shown to be remarkably effective in a workplace environment and the effectiveness depends strongly on the minimum duration of contact required to initiate quarantine. In a realistic social network, we find that forward contact tracing with immediate isolation can reduce an epidemic by more than 70%. In perspective, our findings highlight the necessity of incorporating social heterogeneity into models of mitigation strategies.
The online version supplementary material available at 10.1140/epjb/s10051-021-00222-8.
数字接触者追踪被认为是一种在不过度限制个人行动的情况下控制疫情的有效策略。在此，我们使用智能手机的接近度数据来探究社会结构如何影响新冠病毒病（COVID-19）的接触者追踪。我们对COVID-19的传播进行建模，发现接触者追踪的有效性在很大程度上取决于社会网络结构和异质性社会活动。研究表明，接触者追踪在工作场所环境中非常有效，其有效性在很大程度上取决于启动隔离所需的最短接触时长。在一个现实的社会网络中，我们发现立即隔离的正向接触者追踪可将疫情减少70%以上。从长远来看，我们的研究结果凸显了将社会异质性纳入缓解策略模型的必要性。
在线版本的补充材料可在10.1140/epjb/s10051-021-00222-8获取。
