Detection of SARS-CoV-2 in wastewater in Halifax, Nova Scotia, Canada, using four RT-qPCR assays
Bibliographic record
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".