Monitoring SARS-CoV-2 in Municipal Wastewater and Correlation of Results with Covid-19 Cases from Five Municipalities in Ontario, Canada
Bibliographic record
Abstract
This study investigated the wastewater SARS-CoV-2 RNA signal correlations with community COVID-19 cases and compared results from five municipal wastewater treatment plants in Ontario, Canada, monitored from October 2021 to April 2022. 24-hour composite wastewater samples were collected three times a week at each site and analyzed for SARS-CoV-2, using pepper mild mottle virus (PMMoV) as the main inhibition control. Viral copies were quantified using RT-qPCR. Temperature, pH, turbidity, TS, VS, and UV-Vis scans were measured for all samples. Viral RNA signal was normalized by PMMoV, TS and VS. Correlations between wastewater SARS-CoV-2 RNA signal and COVID-19 case numbers were statistically significant at all sites, showing stronger correlations when comparing normalized data. Results from the five sites were ranked based on the strength of their statistical correlations, with differences potentially attributed to sewer and site characteristics such as populations, sewer sizes or sewer types (combined or separate).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".