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在COVID-19大流行期间人员安排:一种基于概率图的概率分析方法
Mansoor Davoodi1, Ana Batista1, Abhishek Senapati1
1Center for Advanced Systems Understanding (CASUS), Helmholtz-Zentrum Dresden Rossendorf (HZDR), 01328 Görlitz, Germany.
Healthcare (Basel, Switzerland)
|July 14, 2023
概括
优化员工安排和测试计划可以显著减少25-60%的感染风险. 计划测试策略是最有效的,以尽量减少工作场所的病毒传播.
科学领域:
- 运营研究 运营研究
- 流行病学 流行病学
- 公共卫生 公共卫生
背景情况:
- 有效的人员安排对组织至关重要,但易受流行病等干扰的影响.
- 传染病爆发需要战略,平衡运营需求与员工安全.
- 在疫情爆发期间的工作场所安全需要管理现场密度和实施测试协议.
研究的目的:
- 开发和评估最优的员工安排和测试策略的数学模型.
- 尽量减少员工之间的感染风险,同时满足组织需求.
- 为了比较计划与随机测试策略的有效性.
主要方法:
- 两种混合整数非线性编程 (MINLP) 模型的制定.
- 开发一种用于解决问题的正规遗传算法.
- 使用真实和合成的员工联系网络数据进行分析.
主要成果:
- 推的占用和测试策略在各种场景中将感染风险降低了25-60%.
- 计划测试策略被发现优于随机测试,以尽量减少感染风险.
- 员工的疫苗接种情况和相互作用率是影响感染风险的关键因素.
结论:
- 优化调度和测试计划对于减轻工作场所感染的传播至关重要.
- 积极主动,有计划的测试显著提高了感染控制策略的有效性.
- 整合疫苗接种和相互作用率等个别因素可以提高调度模型的有效性.
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