中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (8): 236-243.doi: 10.16265/j.cnki.issn1003-3033.2025.08.1142

• 应急技术与管理 • 上一篇    下一篇

基于贝叶斯网络的突发公共卫生事件应急响应关键路径研究

赵泽斌(), 程瑞   

  1. 哈尔滨工业大学 经济与管理学院, 黑龙江 哈尔滨 150001
  • 收稿日期:2025-04-16 修回日期:2025-06-14 出版日期:2025-08-28
  • 作者简介:

    赵泽斌 (1976—),男,云南曲靖人,博士,教授,博士生导师,主要从事应急管理与数字治理方面的研究。E-mail:

  • 基金资助:
    国家自然科学基金资助(72174044)

Research on critical path of emergency response to public health emergencies based on Bayesian networks

ZHAO Zebin(), CHENG Rui   

  1. School of Management, Harbin Institute of Technology, Harbin Heilongjiang 150001, China
  • Received:2025-04-16 Revised:2025-06-14 Published:2025-08-28

摘要: 为提升公立医院突发公共卫生事件应急响应能力,基于贝叶斯网络方法,从公立医院视角提取突发公共卫生事件中的情景要素、任务与能力,构建应急响应网络,该网络以应急领导小组为核心节点,对内统筹应急专家小组、医疗科室等核心部门及药剂等支持部门,对外联动属地疾控、公安、社区等行政机构,形成内外部协同的应急响应架构。结果表明:通过诊断分析明确应对目标优先级,“防止院感事件发生”为首要目标(占比为40%);成立应急领导小组-成立应急专家小组、成立应急领导小组-严格执行各项防控制度、成立应急领导小组-病毒检测为应对突发公共卫生事件的3条关键路径。

关键词: 贝叶斯网络, 突发公共卫生事件, 应急响应, 关键路径, 情景推演, 公立医院

Abstract:

To enhance the emergency response capacity of public hospitals in dealing with public health emergencies, the Bayesian network approach was adopted in this study. From the perspective of public hospitals, scenario elements, tasks, and capabilities of public health emergencies were extracted and an emergency response network was constructed. The network was centred around the emergency leading group as the core node, the emergency expert group, medical departments and other core departments as well as pharmacy and other supporting departments were collaborated internally. And it linked with local disease control, public security, communities and other administrative agencies externally, thus forming an emergency response structure with internal and external collaboration. Through diagnostic analysis, the priority of response objectives was clarified. The results show that "preventing nosocomial infection incidents" is the primary objective (accounting for 40%). Three key paths are identified: establishing the emergency leading group-establishing the emergency expert group, establishing the emergency leading group - strictly implementing various prevention and control systems, and establishing the emergency leading group - virus testing.

Key words: Bayesian network, public health emergency, emergency response, critical path, scenario deduction, public hospitals

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