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从天花到大数据:流行病学方法的下一个 100 年。

From Smallpox to Big Data: The Next 100 Years of Epidemiologic Methods.

出版信息

Am J Epidemiol. 2016 Mar 1;183(5):423-6. doi: 10.1093/aje/kwv150. Epub 2015 Oct 6.

Abstract

For more than a century, epidemiology has seen major shifts in both focus and methodology. Taking into consideration the explosion of "big data," the advent of more sophisticated data collection and analytical tools, and the increased interest in evidence-based solutions, we present a framework that summarizes 3 fundamental domains of epidemiologic methods that are relevant for the understanding of both historical contributions and future directions in public health. First, the manner in which populations and their follow-up are defined is expanding, with greater interest in online populations whose definition does not fit the usual classification by person, place, and time. Second, traditional data collection methods, such as population-based surveillance and individual interviews, have been supplemented with advances in measurement. From biomarkers to mobile health, innovations in the measurement of exposures and diseases enable refined accuracy of data collection. Lastly, the comparison of populations is at the heart of epidemiologic methodology. Risk factor epidemiology, prediction methods, and causal inference strategies are areas in which the field is continuing to make significant contributions to public health. The framework presented herein articulates the multifaceted ways in which epidemiologic methods make such contributions and can continue to do so as we embark upon the next 100 years.

摘要

一个多世纪以来,流行病学在研究重点和方法上都发生了重大转变。考虑到“大数据”的爆发、更复杂的数据收集和分析工具的出现,以及对循证解决方案的兴趣日益增加,我们提出了一个框架,总结了与理解公共卫生领域的历史贡献和未来方向相关的 3 个基本流行病学方法领域。首先,人群及其随访的定义方式正在扩大,人们对不符合通常按人、地点和时间分类的在线人群更感兴趣。其次,传统的数据收集方法,如基于人群的监测和个体访谈,已经通过测量方法得到了补充。从生物标志物到移动健康,暴露和疾病测量方面的创新使数据收集的准确性得到了提高。最后,人群比较是流行病学方法的核心。危险因素流行病学、预测方法和因果推断策略是该领域继续为公共卫生做出重大贡献的领域。本文提出的框架阐明了流行病学方法在多方面做出此类贡献的方式,并且随着我们进入下一个 100 年,它可以继续这样做。

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