基于分发点的影响的位置分配方法
Nusaybah Alghanmi1, Reem Alotaibi2, Sultanah Alshammari3,4
1Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia. nayyadahalghanmi@stu.kau.edu.sa.
Scientific reports
|July 28, 2025
概括
这项研究引入了一种基于影响的方法,以优化公共卫生分发点 (POD) 的放置. 新模型有效地确定POD位置和数量,改善紧急情况期间的人口覆盖率.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 运营研究 运营研究
背景情况:
- 公共卫生紧急情况需要通过分发点 (POD) 高效地分发医疗用品.
- 现有的POD定位研究通常依赖于预先数据或特定约束,限制灵活性.
- 优化POD网络设计对于及时响应和有效覆盖人口至关重要.
研究的目的:
- 开发一种新的,基于影响的方法来确定新POD的最佳数量和位置.
- 在POD规划中克服基于查询和基于优化的方法的局限性.
- 在公共卫生危机期间,提高人口覆盖率和资源分配.
主要方法:
- 引入基于影响的POD位置分配 (IPLA) 模型.
- 开发影响力亲和传播 (IAP) 集群算法,将现有的POD影响作为新型权重.
- 该模型应用于合成数据集和现实世界的案例研究 (沙特阿拉伯吉达的COVID-19流行病).
主要成果:
- 与其他方法相比,IPLA模型显示出优越的人口覆盖率.
- 使用拟议的IPLA模型,需要较少的新POD.
- 该模型的预测与案例研究的实际POD数量,位置和性能密切匹配.
结论:
- 使用IAP算法的IPLA模型为公共卫生POD网络规划提供了有效的解决方案.
- 这种基于影响力的方法提高了在紧急响应场景中的效率和人口覆盖率.
- 该模型在现实世界流行病中的成功应用凸显了其实际实用性和预测准确性.
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