公平有效的疫苗接种,考虑到疫苗的犹和能力限制
Irem Sengul Orgut1, Nickolas Freeman1, Dwight Lewis2
1Department of Information Systems, Statistics, and Management Science, The University of Alabama, 361 Stadium Dr, Tuscaloosa, AL 35487, United States.
Omega
|June 5, 2023
概括
这项研究引入了公平分配COVID-19疫苗的新模型,减少了旅行时间和浪费. 拟议的方法通过考虑疫苗犹和当地能力,优于标准政策.
科学领域:
- 运营研究 运营研究
- 公共卫生政策 公共卫生政策
- 流行病学 流行病学
背景情况:
- 随着COVID-19的流行,疫苗的快速部署变得必要,这带来了复杂的分配挑战.
- 公平的疫苗分配需要尽量减少旅行时间,防止浪费.
- 诸如疫苗犹和不同区域能力等因素使分配策略复杂化.
研究的目的:
- 为公平有效地分配COVID-19疫苗开发和评估新方法.
- 解决简单的比例分配政策的局限性.
- 将旅行时间公平,疫苗犹和区域能力纳入分配模型.
主要方法:
- 开发了一种混合整数线性编程 (MILP) 模型,以最大限度地减少患者的旅行时间.
- 创建了一个启发式方法,作为MILP模型的可访问替代方案.
- 两种方法均使用阿拉巴马州的现实数据进行评估,并与标准分配政策进行比较.
主要成果:
- 拟议的MILP模型和启发式方法表明,旅行时间公平性得到了实质性的改善.
- 在特定县的能力提升显著改善了公平的疫苗接种.
- MILP模型在整体公平分配方面表现出色,而启发式模型在最小化平均旅行时间方面表现出色.
结论:
- 数学建模和启发式方法为比例的疫苗分配提供了更好的替代方案.
- 有针对性的能力改进可以显著提高疫苗的可访问性和公平性.
- 未来的扩展可以解决疫苗犹问题,并优先考虑高风险人群.
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