[Systems epidemiology]
- PMID: 29860821
- DOI: 10.3760/cma.j.issn.0254-6450.2018.05.031
[Systems epidemiology]
Abstract
The era of medical big data, translational medicine and precision medicine brings new opportunities for the study of etiology of chronic complex diseases. How to implement evidence-based medicine, translational medicine and precision medicine are the challenges we are facing. Systems epidemiology, a new field of epidemiology, combines medical big data with system biology and examines the statistical model of disease risk, the future risk simulation and prediction using the data at molecular, cellular, population, social and ecological levels. Due to the diversity and complexity of big data sources, the development of study design and analytic methods of systems epidemiology face new challenges and opportunities. This paper summarizes the theoretical basis, concept, objectives, significances, research design and analytic methods of systems epidemiology and its application in the field of public health.
医学大数据、转化医学、精准医学时代为慢性复杂疾病及其病因的研究带来新的契机。如何实现循证医学、科学转化、合理精准是我们目前面临的任务和挑战。系统流行病学是一种进行疾病危险因素风险识别的流行病学方法，是流行病学的新领域，其利用系统生物学、流行病学、计算数学等技术将健康大数据与系统生物学结合起来，在分子、细胞、组织、人群社会行为和生态环境等多水平、多组学上深入研究疾病发生风险的统计学模型，并对未来风险状况进行计算模拟和预警预测。由于数据来源的多样性、复杂性以及大数据的特征，为系统流行病学的设计方法和分析方法提出了新的挑战。本文详细介绍了系统流行病学的理论基础、概念、研究目的、研究内容、研究意义、研究设计、分析方法及其在公共卫生领域的应用。.
Keywords: Big data; Data integration; Multi-omic data; Network analysis; Precision medicine; System theory; Systems epidemiology; Translational medicine.
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