School of Public Health and Health Systems, University of Waterloo, Waterloo, ON, Canada.
David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada.
Front Public Health. 2021 Apr 6;9:561873. doi: 10.3389/fpubh.2021.561873. eCollection 2021.
The field of precision medicine explores disease treatments by looking at genetic, socio-environmental, and clinical factors, thus trying to provide a holistic view of a person's health. Public health, on the other hand, is focused on improving the health of populations through preventive strategies and timely interventions. With recent advances in technology, we are able to collect, analyze and store for the first-time large volumes of real-time, diverse and continuous health data. Typically, the field of precision medicine deals with a huge amount of data from few individuals; public health, on the other hand, deals with limited data from a population. With the coming of Big Data, the fields of precision medicine and public health are converging into precision public health, the study of biological and genetic factors supported by large amounts of population data. In this paper, we explore through a comprehensive review the data types and use cases found in precision medicine and public health. We also discuss how these data types and use cases can converge toward precision public health, as well as challenges and opportunities provided by research and analyses of health data.
精准医学领域通过研究遗传、社会环境和临床因素来探索疾病治疗方法，从而试图提供对个人健康的整体看法。另一方面，公共卫生专注于通过预防策略和及时干预来提高人口的健康水平。随着技术的最新进展，我们第一次能够收集、分析和存储大量实时、多样化和连续的健康数据。通常，精准医学领域处理来自少数个体的大量数据；另一方面，公共卫生处理来自人群的有限数据。随着大数据的到来，精准医学和公共卫生领域正在融合为精准公共卫生，即通过大量人口数据支持的生物和遗传因素的研究。在本文中，我们通过全面回顾精准医学和公共卫生中发现的数据类型和用例来进行探讨。我们还讨论了这些数据类型和用例如何朝着精准公共卫生方向融合，以及健康数据分析所带来的挑战和机遇。
