生态流行病学研究设计与统计分析策略

薛付忠

doi:10.16462/j.cnki.zhjbkz.2022.10.008

生态流行病学研究设计与统计分析策略

doi: 10.16462/j.cnki.zhjbkz.2022.10.008

薛付忠^{1, 2, ,}

1.
250012 济南, 山东大学齐鲁医学院公共卫生学院生物统计学系
2.
250003 济南, 国家健康医疗大数据研究院

基金项目:

国家重点研发计划 2020YFC2003500

详细信息

通讯作者:
薛付忠, E-mail: xuefzh@sdu.edu.cn

中图分类号: R181.2
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- 文章访问数: 352
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- PDF下载量: 116
- 被引次数: 0
出版历程
- 收稿日期: 2022-07-22
- 修回日期: 2022-09-02
- 刊出日期: 2022-10-10

The research design and statistical analysis strategy of eco-epidemiology

XUE Fu-zhong^{1, 2
, ,}

1.
Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
2.
National Institute of Health Data Science of China, Jinan 250003, China

Funds:

National Key Research and Development Program of China 2020YFC2003500

More Information

Corresponding author: XUE Fu-zhong, E-mail: xuefzh@sdu.edu.cn

摘要

摘要: 大数据生态流行病学理论范式阐明了一个更全面的生态流行病学视角，承认和捕捉现实世界和虚拟世界中的众多健康决定因素具有等级镶嵌和交互博弈的复杂网络特征。在这种镶嵌分层相互作用及其网络博弈的复杂背景下，传统的基于独立随机假设的传统流行病学抽样调查方法、传统分析流行病学和实验流行病学设计策略及统计分析方法，均面临巨大挑战。取而代之的是，系统动力学模型、网络分析及网络动力学模型、多智能体系统模型以及未来需要发展的生态流行病学超图因果推断模型。从而，由新理论范式、新设计策略和新统计方法，构成了大数据生态流行病学理论方法体系。
- 生态流行病学 /
- 系统动力学模型 /
- 网络分析及网络动力学模型 /
- 多智能体系统模型 /
- 超图因果推断模型
Abstract: The theoretical paradigm of big data eco-epidemiology illustrates a more comprehensive perspective of eco-epidemiology, acknowledging and capturing the complex network characteristics of hierarchical mosaic and interactive games of many health determinants in the real and virtual worlds. Under the complex background of mosaic layered interaction and network-game, the traditional epidemiological sampling methods based on independent random assumptions, traditional analytical and experimental epidemiological design strategies and statistical analysis methods, all face huge challenges. Furthermore, they could be replaced by system dynamics models, network analysis and network dynamics models, multi-agent system models, and causal inference hypergraph models that need to be developed in the future. Thus, a new theoretical paradigm, new design strategy and new statistical method constitute a theoretical method system of big data eco-epidemiology.
- Eco-epidemiology /
- System dynamics model /
- Network analysis and network dynamics model /
- Multi-agent system model /
- Causal inference hypergraph model

HTML全文

图 1 基于全球新冠病毒疫情大数据的系统流行动力学模型

Figure 1. The systematic epidemic dynamics model based on big data of global novel coronavirus epidemic

下载: 全尺寸图片幻灯片

图 2 烟草控制的生态流行病学网络

注：修改自Bethesda. NCI. Greater than the sum: systems thinking in tobacco control. 2007^[15-16]。

Figure 2. The eco-epidemiological network for tobacco control

下载: 全尺寸图片幻灯片

图 3 多智能体系统及其代理人基模型

注：主体为独立个体或共同群体，交互的对象为虚拟世界和现实世界中的因素(详见图 1)。

Figure 3. Multi-agent system and its agent-based model

下载: 全尺寸图片幻灯片

图 4 生态流行病学超网络因果推断模型

Figure 4. Eco-epidemiological causal inference hypergraph model

下载: 全尺寸图片幻灯片

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