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一个建模管道,将市政废水监测与区域公共卫生数据联系起来

Katelyn Plaisier Leisman¹, Christopher Owen², Maria M Warns¹

¹Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL, USA.

|February 3, 2024

概括

对SARS-CoV-2RNA的废水监测提供了COVID-19趋势的有价值的被动指标. 这项研究开发了一条管道,以提高废水数据的准确性,发现它可以在其他指标之前预测升.

科学领域:

环境科学环境科学
病毒学病毒学
公共卫生公共卫生

背景情况:

COVID-19监测依赖于自愿测试,造成数据缺口.
对SARS-CoV-2RNA的废水监测是一个有希望的被动指标.
环境样本呈现出高噪音,挑战了准确的流行率估计.

研究的目的:

开发和验证用于分析废水SARS-CoV-2 RNA的通用管道.
评估不同校正模型在减少测量方差方面的有效性.
评估废水数据作为COVID-19趋势的领先指标.

主要方法:

开发了一个通用的管道,包括样本内和样本外的模型选择.
对比的多线性回归模型,包括PMMoV,BCoV和流量.
将管道应用于芝加哥污水处理厂的废水数据.
统计比较废水趋势与其他COVID-19流行指标.

主要成果:

结合牛冠状病毒 (BCoV) 的模型表现出比使用胡轻型斑点病毒 (PMMoV) 的模型更好的性能.
开发的管道有效地减少了废水SARS-CoV-2 RNA测量的差异.
废水监测数据显示,对COVID-19的急剧增长具有领先的预测能力.

结论:

基于废水的流行病学提供了一个强大的,被动的监测工具,用于流行COVID-19.
一般化管道提供了一种灵活的方法,可以适应不同的数据源和条件.
废水SARS-CoV-2 RNA趋势可以作为社区传播的早期预警系统.

关键词:

模型选择模型选择规范化模型的规范化模型流行病情报流行病情报这就是SARS-CoV-2病毒.趋势预测趋势预测基于废水的流行病学.

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