Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Department of Biology and the Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
Nat Commun. 2020 Sep 30;11(1):4961. doi: 10.1038/s41467-020-18190-5.
The ongoing coronavirus disease 2019 (COVID-19) pandemic has heightened discussion of the use of mobile phone data in outbreak response. Mobile phone data have been proposed to monitor effectiveness of non-pharmaceutical interventions, to assess potential drivers of spatiotemporal spread, and to support contact tracing efforts. While these data may be an important part of COVID-19 response, their use must be considered alongside a careful understanding of the behaviors and populations they capture. Here, we review the different applications for mobile phone data in guiding and evaluating COVID-19 response, the relevance of these applications for infectious disease transmission and control, and potential sources and implications of selection bias in mobile phone data. We also discuss best practices and potential pitfalls for directly integrating the collection, analysis, and interpretation of these data into public health decision making.
正在持续的 2019 年冠状病毒病(COVID-19)大流行加剧了关于在疫情应对中使用手机数据的讨论。有人提议使用手机数据来监测非药物干预措施的效果,评估时空传播的潜在驱动因素,并支持接触者追踪工作。虽然这些数据可能是 COVID-19 应对的重要组成部分,但在考虑使用这些数据时,必须结合对其捕获的行为和人群的仔细了解。在这里,我们回顾了手机数据在指导和评估 COVID-19 应对方面的不同应用,这些应用与传染病传播和控制的相关性,以及手机数据中选择偏差的潜在来源和影响。我们还讨论了将这些数据的收集、分析和解释直接纳入公共卫生决策制定的最佳实践和潜在陷阱。