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基于废水的监测可以用于模拟COVID-19相关的劳动力缺勤和缺勤

Nicole Acosta¹, Xiaotian Dai², Maria A Bautista³

¹Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta T2N 4N1, Canada.

The Science of the total environment

|June 28, 2023

概括

废水监测有效地预测了COVID-19相关的劳动力缺勤,为雇主提供了一个星期的领先时间. 这种方法有助于管理COVID-19等呼吸道疾病的人力资源.

科学领域:

环境科学环境科学
公共卫生公共卫生
流行病学流行病学

背景情况:

建立了基于废水的监测 (WBS),以追踪社区中的传染病.
它的应用在预测对非医疗保健环境的影响,如劳动力缺勤等方面,仍未得到充分探索.
了解COVID-19的社区负担,将为公共卫生政策和资源分配提供信息.

研究的目的:

调查废水中的SARS-CoV-2水平与劳动力缺勤之间的相关性.
利用废水数据,开发一个用于COVID-19相关缺席的预测模型.
评估WBS对雇主在呼吸道疾病爆发期间管理劳动力动力学的有用性.

主要方法:

来自三个污水处理厂的废水中的定量SARS-CoV-2RNA (N1和N2),为140万居民提供服务.
从2020年6月到2022年3月,每周三次收集废水样本.
将废水数据与来自大型雇主 (>15,000名员工) 的劳动力缺勤记录 (COVID-19相关,已确认和无关) 进行比较.
采用波桑回归来构建COVID-19缺勤率的预测模型,使用废水数据作为主要指标.

主要成果:

在95.5%的评估周中检测到SARS-CoV-2RNA.
使用废水数据作为COVID-19确诊缺席的一周领先指标,开发了一种统计学上显著的预测模型 (P < 0.0001).
结合废水数据的模型显示,与零模型相比,预测准确度 (较低的AIC) 显著提高.
模型预测密切跟踪了实际的缺勤数据,证明了可靠性.

结论:

基于废水的监测可以作为与COVID-19相关的劳动力缺勤率的有价值的领先指标.
雇主可以利用WBS预测员工需求并优化资源分配.
这种方法适用于管理其他可追踪的呼吸道疾病在非医疗机构.

关键词:

流行病学流行病学劳动时间安排.预测预测预测这就是SARS-CoV-2病毒.污水污水处理污水污水处理提供工作人员.

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