Consistent trends from different methods for monitoring SARS-CoV-2 in urban wastewater during a 29-month longitudinal study

Rigorous method development and validation to detect and quantify SARS-CoV-2 RNA in wastewater has led to important advances in community disease surveillance using quantitative molecular biology tools. Despite this progress, agreement on standardized workflows for this important public health objective has been elusive. Multiple studies have compared different protocols but have been limited by short periods of observation or low numbers of test sites. Here we compare results from two parallel workflows for wastewater processing and quantifying SARS-CoV-2 gene targets from five wastewater treatment plants in three large cities in Alberta, Canada for up to 29-months. In total 1,482 wastewater samples were processed using either affinity columns followed by RT-qPCR with DNA-based standards or using ultrafiltration followed by RT-qPCR with RNA-based standards. Results from either workflow correlated well with each other, and with 5-day rolling averages of clinically diagnosed COVID-19 cases (i.e., in the early part of the 29-month study period when clinical testing was performed routinely). This highlights that different workflows both effectively and reliably monitored SARS-CoV-2 trends in wastewater. Parallel quantification of pepper mild mottle virus genomes and normalization were inconsistent between the two workflows, suggesting that normalization strategies may require adjustment for different wastewater processing protocols. Freezing wastewater samples diminished measured SARS-CoV-2 RNA levels significantly, whereas short term sample storage at +4°C gave consistent results. Overall, this work demonstrates that different workflows can deliver similarly effective wastewater-based surveillance for community COVID-19 burden. As this emerging technology is used more routinely, investigators should prioritize consistent application of a given workflow to a high-quality standard over time, whereas focusing on all testing programs adopting identical workflows and methods may be unnecessary.