基于贝叶斯网络的非传统公共卫生紧急情况的场景构建和进化分析
Yutao Zhu1, Qing Yang2, Lingmei Fu3
1School of Management, Wuhan University of Technology, Wuhan, China.
Frontiers in public health
|February 24, 2025
概括
本研究分析了非传统的公共卫生紧急情况 (NCPHEs),以预测其演变并改进应对策略. 通过模拟NCPHE场景,研究人员旨在减少社会影响,提高公共卫生安全.
科学领域:
- 公共卫生 公共卫生
- 应急管理 应急管理
- 流行病学 流行病学
背景情况:
- 非传统的公共卫生紧急情况 (NCPHEs) 为降低风险和减少社会影响带来了独特的挑战.
- 处理NCPHE的现有策略需要改进,以应对复杂和不断变化的场景.
研究的目的:
- 汇总和分析NCPHE场景的演变模式.
- 开发更好的策略来管理NCPHE和减少其社会影响.
主要方法:
- 分析了新闻报道,以识别和分类NCPHE场景元素到扩散或衍生阶段.
- 德姆斯特-沙弗 (DS) 理论和贝叶斯网络 (BNs) 被应用于数据推理.
- 构建了一个衍生于传播的合场景-响应理论模型,使用COVID-19数据来推导场景演变路径.
主要成果:
- 总结了26个NCPHE差价场景和41个NCPHE衍生场景.
- 优化和悲观的NCPHE场景路径被生成.
- 该模型有助于决策者预测NCPHE的发展,并及时实施应急响应.
结论:
- 该研究引入了一种新的方法来理解和管理NCPHEEs.
- 一个上下文导出模型和紧急决策系统为增强应对能力提供了实际工具.
- 有效管理NCPHE对于促进公共健康和安全至关重要.
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