大数据与流行病学在流行病学研究中的交叉应用：新冠疫情的影响
The intersection of big data and epidemiology for epidemiologic research: The impact of the COVID-19 pandemic.
作者信息
Tang Chunlei, Plasek Joseph M, Zhang Suhua, Xiong Yun, Zhu Yangyong, Ma Jing, Zhou L I, Bates David W
机构信息
Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA.
Harvard Medical School, Boston, MA, USA.
出版信息
Int J Qual Health Care. 2021 Sep 25;33(3). doi: 10.1093/intqhc/mzab134.
Abstract
Big data epidemiology facilitates pandemic response by providing data-driven insights by utilizing big data tools that differ from traditional methods. Aspects regarding 'garbage in, garbage out', such as insufficient data, inaccessibility of data, missing data, uncertainty in handling data and bias in analysis or common findings are addressable by combining techniques across disciplines.
摘要
大数据流行病学通过利用不同于传统方法的大数据工具提供数据驱动的见解，从而促进对大流行的应对。通过跨学科结合技术，可以解决诸如数据不足、数据不可获取、数据缺失、数据处理中的不确定性以及分析或常见发现中的偏差等“输入垃圾，输出垃圾”方面的问题。
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