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贝叶斯网络模型揭示了医院对洪水疏散计划的决策理由
Takashi Nagata1, Takeru Abe2, Koji Nishiyama3
1Department of Emergency Medicine, https://ror.org/05jr18655Japan Self Defense Forces Central Hospital, Setagaya, Tokyo, Japan.
Disaster medicine and public health preparedness
|June 25, 2025
概括
政府提供的洪水和山体滑坡地图显著改善了医院对大雨事件的准备. 最近的洪水经历并不自动导致疏散计划,强调需要更好地传播信息.
科学领域:
- 灾害管理 灾害管理
- 公共卫生准备情况 公共卫生准备情况
- 环境健康 环境健康
背景情况:
- 越来越频繁的暴雨和洪水需要强大的医院准备.
- 在洪水事件中确保患者安全需要有效的疏散规划和演习.
- 了解影响医院准备的因素对于减轻洪水影响至关重要.
研究的目的:
- 分析各种因素与医院应对大雨引发洪水的准备情况之间的关系.
- 确定开发和实施医院疏散计划和演习的关键驱动因素.
主要方法:
- 利用了2022年在日本765家灾难基地医院的互联网调查数据.
- 采用贝叶斯网络分析来研究影响因素之间的相互关系.
- 分析了符合纳入标准的430家医院的数据.
主要成果:
- 42.1%的医院位于指定洪水区,但只有33.7%的医院有疏散计划.
- 政府显示的洪水和山体滑坡预警区域的可用性与疏散规划和演习相关.
- 医院最近的洪水或山体滑坡经历与疏散计划或演习没有直接相关.
结论:
- 政府提供的洪水和山体滑坡预警信息有效地提高了医院的防洪准备.
- 积极的措施,如清晰地绘制危险区,对于改善医院反应至关重要.
- 研究结果为加强医院应对暴雨和洪水的准备策略提供了见解.
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