Research Center for Environmental Quality Management, Graduate School of Engineering, Kyoto University, 1-2 Yumihama, Otsu, Shiga 520-0811, Japan.
Water and Sewage Management Department, Water and Disaster Management Bureau, Ministry of Land, Infrastructure, Transportation and Tourism, Japan.
Sci Total Environ. 2024 Nov 25;953:176073. doi: 10.1016/j.scitotenv.2024.176073. Epub 2024 Sep 7.
Wastewater surveillance for COVID-19 and other pathogens has expanded globally. Rapid development and availability of various assays has facilitated swift adoption of wastewater surveillance in localities with diverse requirements. However, it presents challenges in comparing data due to methodological variations. Using surrogates for recovery control to address quantification biases has limitations as the recovery of surrogates and target pathogens often diverges significantly. Using non-spiked field-obtained wastewater samples as reference samples in an inter-lab study, this article proposes a straightforward, inexpensive, and most representative way of measuring relative quantification biases that occurs in analyzing field wastewater samples. Five labs participated in the study, testing five types of assays, resulting in a total of seven methods of lab-assay combinations. Each method quantified the concentration of SARS-CoV-2 and pepper mild mottle virus (PMMoV) RNAs in two types of reference samples. The results showed significant variations in quantification among methods, but the relative quantification biases were consistent across reference samples. This suggests that relative quantification biases measured with the reference samples are contingent on methods rather than wastewater samples, and that the once-determined method-specific factors can be used to correct for quantification biases in routine wastewater surveillance results. Subsequent data standardization was performed on year-long observational data from seven cities, serving as a preliminary validation of the proposed approach. This process demonstrated the potential for quantitative data comparison through the bias correction factors obtained in this inter-lab study.
新冠病毒和其他病原体的污水监测在全球范围内得到了扩展。各种检测方法的快速发展和可用性促进了在具有不同需求的地方迅速采用污水监测。然而,由于方法学的差异,这在比较数据时带来了挑战。使用回收控制的替代物来解决定量偏差存在局限性,因为替代物和目标病原体的回收率通常存在显著差异。本文提出了一种直接、廉价且最具代表性的方法,使用未经加标处理的现场污水样本作为实验室间研究的参考样本,来测量分析现场污水样本时发生的相对定量偏差。五个实验室参与了这项研究,测试了五种类型的检测方法,总共产生了七种实验室检测方法组合。每种方法都定量分析了两种参考样本中 SARS-CoV-2 和辣椒轻斑驳病毒(PMMoV)RNA 的浓度。结果表明,方法之间的定量存在显著差异,但参考样本的相对定量偏差是一致的。这表明,用参考样本测量的相对定量偏差取决于方法而不是污水样本,并且一旦确定了特定于方法的因素,可以用于纠正常规污水监测结果中的定量偏差。随后对来自七个城市的长达一年的观测数据进行了数据标准化,作为对所提出方法的初步验证。这个过程展示了通过在这个实验室间研究中获得的偏差校正因子来进行定量数据比较的潜力。