Detection of SARS-CoV-2 in wastewater in Halifax, Nova Scotia, Canada, using four RT-qPCR assays

Abstract

Wastewater-based surveillance methods have been implemented in several countries as a tool for monitoring SARS-CoV-2 at a community scale. A variety of methods have been used for concentrating, extracting, and detecting the virus, with no clear consensus on the most effective approach. In this note, we report preliminary findings from a study that is tracking SARS-CoV-2 in wastewater in Halifax, Nova Scotia, with a specific focus on the use of four reverse transcriptase quantitative PCR (RT-qPCR) assays for detecting the virus in wastewater. We were able to detect the virus in wastewater samples during the initial rise of cases in the Halifax region in early November 2020. Levels of the targeted SARS-CoV-2 gene fragments increased and fell in response to reported cases of COVID-19. The CDC N1 and E RT-qPCR assays demonstrated greater relative sensitivity than the CDC N2 and N3 assays for detection of SARS-CoV-2 in raw sewage samples.

Correlation between SARS-CoV-2 RNA concentration in wastewater and COVID-19 cases in community: A systematic review and meta-analysis

“…active cases, daily new cases, and future cases etc., that C RNA correlated with, and the strength of the correlation varied greatly in different studies. For instance, Huang et al (2021) found a strong correlation (Pearson’s correlation coefficient, R= 0.98) between the C RNA and active cases. D'Aoust et al (2021b) observed that C RNA correlated better with daily new cases (R=0.37) than active cases (R=0.21), although both correlations are weak.…”

“…( Li et al, 2021b , Pan et al, 2020 , van Doorn et al, 2020 ). The viral shedding allows the application of wastewater-based epidemiology (WBE) in estimating the community prevalence or incidence of COVID-19 as a complementary approach to clinical testing ( Huang et al, 2021 , Nemudryi et al, 2020 , Róka et al, 2021 ). By systematic collection and analysis of wastewater samples for the virus, either at the inlet of wastewater treatment plants (WWTPs), sewer pumping stations, or manholes, WBE provides an estimation of COVID-19 case numbers in the connected population ( Betancourt et al, 2021 , Rusiñol et al, 2021 , Wong et al, 2021 ).…”

Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology

“…However, to inform the pandemic management and policymaking, different parameters of prevalence or incidence, i.e. daily new cases, future daily new cases, rolling average cases, future average cases, total active cases, and effective reproductive number (also known as effective reproduction rate, R i ) etc., were adopted and the WBE performance in estimating these epidemiological parameters varied greatly in different studies ( D'Aoust et al, 2021 ; Huang et al, 2021 ; Huisman et al, 2021a ; Huisman et al, 2021b ; Róka et al, 2021 ; Weidhaas et al, 2021 ). The usually conflicting and variable observations in literature imply extra factors need to be considered in addition to the C RNA and those parameters as dictated in conventional WBE back-estimation ( Eq.1 ).…”

Underestimation of SARS-CoV-2 in wastewater due to single or double mutations in the N1 qPCR probe binding region

“…Although our investigation focused on the impact of mutations in the N1 qPCR probe binding region on the quantification of SARS-CoV-2, the lessons learned from this study are applicable to other biomarkers for SARS-CoV-2 and beyond. Biomarkers that are currently used by other Canadian labs include a subregion of the envelope protein coding gene (E gene) ( Huang et al, 2021 ), and a different subregion of the N-gene (i.e., N200 universal) ( Fuzzen et al, 2023 ). As the SARS-CoV-2 virus evolves, mutations have also been observed in the primer binding regions of the E gene and N200 biomarkers (Fig S5).…”