Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
The Center for RNA Science and Therapeutics, Case Western University, Cleveland, OH, USA.
Nat Biomed Eng. 2020 Dec;4(12):1208-1220. doi: 10.1038/s41551-020-00640-6. Epub 2020 Nov 18.
Consumer wearable devices that continuously measure vital signs have been used to monitor the onset of infectious disease. Here, we show that data from consumer smartwatches can be used for the pre-symptomatic detection of coronavirus disease 2019 (COVID-19). We analysed physiological and activity data from 32 individuals infected with COVID-19, identified from a cohort of nearly 5,300 participants, and found that 26 of them (81%) had alterations in their heart rate, number of daily steps or time asleep. Of the 25 cases of COVID-19 with detected physiological alterations for which we had symptom information, 22 were detected before (or at) symptom onset, with four cases detected at least nine days earlier. Using retrospective smartwatch data, we show that 63% of the COVID-19 cases could have been detected before symptom onset in real time via a two-tiered warning system based on the occurrence of extreme elevations in resting heart rate relative to the individual baseline. Our findings suggest that activity tracking and health monitoring via consumer wearable devices may be used for the large-scale, real-time detection of respiratory infections, often pre-symptomatically.
消费者可穿戴设备可以持续测量生命体征，已被用于监测传染病的发作。在这里，我们展示了消费者智能手表的数据可用于对 2019 冠状病毒病（COVID-19）的症状前检测。我们分析了近 5300 名参与者队列中被识别出的 32 名感染 COVID-19 个体的生理和活动数据，发现其中 26 人（81%）的心率、每日步数或睡眠时间发生了变化。在有生理变化检测到的 25 例 COVID-19 病例中，我们有症状信息，其中 22 例在症状出现前（或同时）被检测到，4 例至少提前 9 天被检测到。使用回顾性智能手表数据，我们表明，通过基于静息心率相对于个体基线的极端升高的两层预警系统，实时情况下 63%的 COVID-19 病例可能在症状出现前被检测到。我们的研究结果表明，通过消费者可穿戴设备进行的活动跟踪和健康监测可能用于大规模、实时检测呼吸道感染，通常是在症状出现前。
