适应性资源分配CUSUM用于对称计数数据监测,适用于COVID-19热点检测
Jiuyun Hu1, Yajun Mei2, Sarah Holte3
1School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA.
Journal of applied statistics
|October 9, 2023
概括
本研究引入了一种有效的统计方法,用于使用有限资源检测热点. 适应性资源分配CUSUM结合了多臂盗和变化点检测,以提高准确性和减少延迟.
科学领域:
- 统计方法 统计方法
- 流行病学监测 流行病学监测
- 公共卫生信息学 公共卫生信息学
背景情况:
- 热点检测对于在疫情期间有效分配资源至关重要.
- 有限的采样资源在准确识别疾病热点方面带来了重大挑战.
- 现有的方法往往难以平衡资源的勘探和开发.
研究的目的:
- 开发一种高效的统计方法,以有限的抽样资源进行可靠的热点检测.
- 整合多臂盗和变化点检测,以优化资源配置.
- 为了提高准确性和减少识别疾病热点的延迟.
主要方法:
- 适应性资源分配的CUSUM (ARACUSUM) 方法.
- 多臂强盗 (MAB) 的组合用于勘探-开采平衡.
- 对感染率后部分布的贝叶斯加权更新.
- 资源分配和规划的上置信限 (UCB).
- 用于变化点和位置检测的CUSUM监控统计.
主要成果:
- 与基准标准相比,拟议的ARACUSUM方法显示了较低的检测延迟.
- 在识别热点时实现更高的检测精度.
- 有效地应用于现实世界的COVID-19病例数据在华盛顿州.
- 即使使用非常有限的分布式样本,也显示出有效性.
结论:
- 在资源有限的情况下,ARACUSUM方法为热点检测提供了一种高效和强大的方法.
- 综合MAB和变化点检测为流行病监测提供了一个强大的战略.
- 这种方法对于管理有限数据的公共卫生危机具有实际意义.
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