Canadian Wastewater Survey (CWS)

Detailed information for December 2021 to January 2022

To detect and measure trends in the viral load of SARS-CoV-2 through wastewater epidemiological surveillance.

Data release - February 18, 2022

• Description
• Data sources and methodology
• Data accuracy

Description

This survey is conducted in collaboration with the Public Health Agency of Canada.

The goal of this work is to detect and measure trends in the viral load of SARS-CoV-2 through wastewater epidemiological surveillance, which could be used as an indicator for the total community burden of COVID-19 infections. These data have the potential to be used as an early-warning system for outbreaks of the disease in previously virus-free communities, or to monitor the effectiveness of public health measures in areas with significant case-numbers. The drug component of this survey is collected on a monthly basis, and estimates the load per capita of various drugs of concern.

Reference period: Daily

Collection period: Variable - Currently twice weekly

Subjects

• Health
• Lifestyle and social conditions

Data sources and methodology

Target population

Wastewater treatment plants in Metro Vancouver , Edmonton, Toronto, Montreal and Halifax.

Instrument design

PDF questionnaire is a one-time questionnaire, comprised of variables compiled by engineers at wastewater treatment plants based on the treatment plant design and coverage area.

The Excel questionnaire, is a weekly questionnaire, comprise of variables compiled by engineers at wastewater treatment plants such as water flow data, water quality testing results, and weather or other events that could have an impact on results.

The questionnaires were developed in consultation with subject matter experts, potential respondents, data users and questionnaire design specialists. They are submitted via email, or through an electronic file transfer (EFT) service.

Sampling

This survey is a census with a longitudinal design.

Sampling unit:
Wastewater treatment plants.

Data sources

Responding to this survey is voluntary.

Data are collected directly from survey respondents.

Engineers in wastewater treatment plants collect twice weekly 24 h composite wastewater samples during the collection period. The samples are delivered to the National Microbiology Laboratory (NML) for analysis. The results of the analysis, as well as the recorded wastewater inflows and other relevant metadata at the time of sampling, are sent to Statistics Canada.

Error detection

Wastewater samples are analyzed in technical duplicates against two targets each (N1/N2) to validate the measurement of SAR-CoV-2.

Imputation

For the purpose of estimating the viral load, concentration measurements below the limit of detection are imputed with a value below the limit. For the purpose of viral detection, these measurements are treated as non-detections and are not imputed.

Estimation

The concentration of viral particles of SARS-CoV-2 in wastewater primary influent as measured in triplicate by RT-qPCR. In addition, the concentrations of murine hepatitis virus (MHV) and of the pepper mild mottle virus (PMMV) are also measured by the same means for quality assurance and normalization purposes. Metadata encompassing epidemiology indicators, wastewater plant characteristics and environmental factors is released to assist in interpreting the data.

Quality evaluation

Data are verified for reasonableness and coherence. Where lack of reliability is suspected, results are withheld.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

Data may be subject to revision if experimental or metadata errors are detected, if laboratory analyses are repeated, or if additional scientific knowledge of the supporting data becomes available. As of now, no revision calendar has been established. No seasonal adjustment will be made for this short period pilot.

Data accuracy

SARS-CoV-2 concentration from wastewater is determined at NML based upon previously developed methodologies for viruses similar in structure to SARS-CoV-2. RNA is extracted from wastewater solids on an automated nucleic acid platform, and subsequently quantitated by the reverse transcriptase quantitative polymerase chain reaction (RT-qPCR).

The limit of detection (LOD) was estimated by NML to be 4 genome copies per milliliter of raw wastewater influent. The performance of the method was compared to peer-reviewed and pre-print studies employing similar methods directed against the same SARS-CoV-2 molecular targets in longitudinal studies of real-world wastewater samples. The range of viral concentrations reported in the previous studies was greater than the LOD determined by NML for the majority of samples, suggesting that the test employed here would be sensitive to the same range of viral input material, and provides confidence that NML's wastewater test is performing adequately.

The NML has also led an interlab study with eight other laboratories across Canada performing similar analysis of SARS-CoV-2 in wastewater. Based on the results of this study, the NML method has better than average sensitivity.