PDF(Pubmed)
Abstract：
Wastewater based epidemiology has become a widely used tool for monitoring trends of concentrations of different pathogens, most notably and widespread of SARS-CoV-2. Therefore, in 2022, also in Rhineland-Palatinate, the Ministry of Science and Health has included 16 wastewater treatment sites in a surveillance program providing biweekly samples. However, the mere viral load data is subject to strong fluctuations and has limited value for political deciders on its own. Therefore, the state of Rhineland-Palatinate has commissioned the University Medical Center at Johannes Gutenberg University Mainz to conduct a representative cohort study called SentiSurv, in which an increasing number of up to 12,000 participants have been using sensitive antigen self-tests once or twice a week to test themselves for SARS-CoV-2 and report their status. This puts the state of Rhineland-Palatinate in the fortunate position of having time series of both, the viral load in wastewater and the prevalence of SARS-CoV-2 in the population. Our main contribution is a calibration study based on the data from 2023-01-08 until 2023-10-01 where we identified a scaling factor ( 0.208 ± 0.031 ) and a delay ( 5.07 ± 2.30 days) between the virus load in wastewater, normalized by the pepper mild mottle virus (PMMoV), and the prevalence recorded in the SentiSurv study. The relation is established by fitting an epidemiological model to both time series. We show how that can be used to estimate the prevalence when the cohort data is no longer available and how to use it as a forecasting instrument several weeks ahead of time. We show that the calibration and forecasting quality and the resulting factors depend strongly on how wastewater samples are normalized.
摘要：
基于废水的流行病学已成为监测不同病原体浓度趋势的广泛使用的工具。最值得注意和广泛的SARS-CoV-2。因此,2022年，也在莱茵兰-普法尔茨，科学和卫生部已将16个废水处理点纳入一个提供双周样本的监测计划。然而,单纯的病毒载量数据会受到强烈的波动，对政治决策者本身的价值有限。因此,莱茵兰-普法尔茨州委托美因茨约翰内斯·古腾堡大学医学中心进行一项名为SentiSurv的代表性队列研究，其中，越来越多的多达12,000名参与者每周使用一次或两次敏感抗原自检来测试SARS-CoV-2并报告其状态。这使得莱茵兰-普法尔茨州处于幸运的位置，废水中的病毒载量和SARS-CoV-2在人群中的流行。我们的主要贡献是基于2023-01-08到2023-10-01的数据进行的校准研究，我们确定了废水中病毒载量之间的比例因子（0.208±0.031）和延迟（5.07±2.30天），通过辣椒轻度斑驳病毒（PMMoV）归一化，以及SentiSurv研究中记录的患病率。通过将流行病学模型拟合到两个时间序列来建立关系。我们展示了当队列数据不再可用时，如何使用它来估计患病率，以及如何提前几周将其用作预测工具。我们表明，校准和预测质量以及由此产生的因素在很大程度上取决于废水样品的归一化方式。
