Testing specificity and sensitivity of wastewater-based epidemiology for detecting SARS-CoV-2 in four communities on Vancouver Island, Canada
Bibliographic record
Abstract
We report wastewater surveillance of the spread of SARS-CoV-2 based upon 24-h composite influent samples taken weekly from four wastewater treatment plants (WWTP) on Vancouver Island, BC, Canada between January 3, 2021 and July 10, 2021. Samples were analyzed by reverse transcription quantitative polymerase chain reaction targeting the N1 and N2 gene fragments of SARS-CoV-2 and a region of the replication associate protein of the pepper mottle mosaic virus (PMMoV) serving as endemic control. Only a small proportion of samples had quantifiable levels of N1 or N2. Overall case rates are weakly correlated with the concentration (gene copies/L) and with the flux of viral material influent to the WWTP (gene copies/day); the latter accounts for influent flow variations. Poisson multimodal rank correlation accounts for differences between the four WWTP and shows a significant correlation with a significant positive intercept. Receiver operator characteristics (ROC) analysis confirms a cut-off of cases based on amplified/not-amplified experimental data. At the optimal cut point of 19 (N1) or 17 (N2) cases/week/100,000 the sensitivity and specificity is about 75% for N1 and 67% for N2.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".