Population-scale pervasive health research attempts to harness large-scale data that has already been collected through commercial devices and web applications to study human behaviors and the links between that data and health and well-being. Leveraging these existing datasets enables studies of behaviors and health at an unprecedented scale, resolution, and duration relatively inexpensively and quickly. Yet although there are great advantages in leveraging large-scale datasets for individual and population health, specialized computational methods are needed to overcome the limitations of this approach. Here, the author reviews lessons learned from his own work and from the works of other researchers, and he presents current challenges and opportunities.

中文翻译：

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人口规模普遍健康

人口规模的普遍健康研究试图利用已经通过商业设备和网络应用程序收集的大规模数据来研究人类行为以及这些数据与健康和福祉之间的联系。利用这些现有的数据集，可以相对便宜且快速地以前所未有的规模、分辨率和持续时间研究行为和健康。然而，尽管利用大规模数据集进行个人和人群健康有很大的优势，但需要专门的计算方法来克服这种方法的局限性。在这里，作者回顾了从他自己的工作和其他研究人员的工作中吸取的经验教训，并提出了当前的挑战和机遇。