Enabling quantitative comparison of wastewater surveillance data across methods through data standardization without method standardization

Abstract

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.