One for all and all for one health: Harmonizing SARS-CoV-2 wastewater surveillance results across a laboratory network

Reliable and comparable data from multiple laboratories are essential for networks relying on reverse transcription quantitative polymerase chain reaction (RT-qPCR)-based surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic material in wastewater. Large-scale networks, such as those spanning Canada and the United States, depend on multiple laboratories deploying varied methods. However, the comparability of these methods and implications for data interoperability have not been rigorously examined. Split-sample results from an inter-laboratory study conducted across 15 laboratory methods over 15 rounds in Canada were analyzed. This study focused on assessing the consistency of SARS-CoV-2 signal levels, as well as an indicator of fecal content, Pepper Mild Mottle Virus (PMMoV). Linear mixed models and associated intraclass correlation coefficients (ICC) were applied to gain insights to inter and intra-laboratory method variability. Wastewater SARS-CoV-2 signal levels were moderately concordant across laboratories, even without a single standardized protocol (ICC ≈ 0.70, p < 0.01). Laboratories generally distinguished and aligned on different levels of SARS-CoV-2 present in wastewater samples. However, assays targeting PMMoV displayed significant method-specific variability (ICC = 0.22, p < 0.01). This variability may be attributable to differences in standard quantification materials and different partitioning behaviour of PMMoV relative to SARS-CoV-2 within wastewater matrices. These results highlight the robustness of SARS-CoV-2 surveillance methods across laboratories, demonstrating reliable data comparability despite methodological differences. In contrast, PMMoV assays exhibited greater methodological variability, thereby inflating inter-lab PMMoV-normalized SARS-CoV-2 variability. This suggests the need for careful evaluation of the purpose of-and scale at-which PMMoV normalization is applied. Insights into the impacts of SARS-CoV-2 mutations on assay performance highlight the necessity of routine evaluation to ensure methods remain reliable and fit-for-purpose.