Sporadic detection of vaccine-derived poliovirus type 2 using next-generation sequencing in Canadian wastewater in August of 2022
Bibliographic record
Abstract
In July 2022, an unvaccinated young adult living in Rockland County, New York became paralyzed due to a vaccine-derived poliovirus type 2 (VDPV2) infection that was internationally transmitted. Wastewater surveillance in New York State uncovered VDPV2 in neighboring counties, showing silent community spread. These communities have strong epidemiological links to some vaccine-hesitant communities in Canada, spurring the need to monitor these populations for potential poliovirus importation. At the time, Canada did not have an established poliovirus wastewater method. We initiated this study to apply molecular methods to detect poliovirus in these communities and establish poliovirus wastewater surveillance capabilities in Canada. We sequence confirmed one poliovirus detection on August 30th, 2022 using both viral isolation and direct detection methods. Subsequent retrospective and prospective sampling was initiated, resulting in another sequence confirmed detection of VDPV2 in an overlapping catchment area collected on August 27th, 2022. Both VDPV2 detections were genetically linked to the New York clinical case. No clinical cases of poliomyelitis were detected in Canada during this study. The sporadic detection of VDPV2 in Canadian wastewater supports a travel-related shedding event without community transmission. Furthermore, we show that a direct detection method is sensitive to sequence confirm poliovirus in wastewater samples.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".