Detection of Measles Virus Genotype A in a Non-Endemic Wastewater Setting: Insights from Measles Wastewater and Environmental Monitoring in Canada’s Capital Region
Bibliographic record
Abstract
The recent global resurgence of measles in 2023-2024, despite vaccine preventability, underscores a critical public health issue, largely due to reduced vaccination coverage during the SARS-CoV-2 pandemic. In response, Ottawa Public Health intensified vaccination efforts in 2023 and 2024. Additionally, a research initiative began in April 2024 to monitor Ottawa wastewater for measles virus (MeV) using established wastewater and environmental surveillance (WES) protocols. Unexpected positive MeV detections through RT-qPCR in Ottawa wastewater-despite no active regional cases-prompted genotypic and retrospective analyses of archived RNA samples dating back to 2020. The genotypic analysis identified positive detection to belong to genotype A, the progenitor strain of the viral vaccines, marking the first report of MeV vaccine RNA in a large catchment area. Linear regression analysis revealed detections aligned with intensified vaccination efforts by Ottawa Public Health. These findings emphasize the importance of integrating genotypic analysis into WES practices to mitigate possible confounding factors, such as vaccine shedding into wastewater. Additionally, this research highlights potential public health applications using MeV WES as a complementary tool. Implementing the findings of this study for MeV WES, and for other re-emerging viruses, could improve public health response and resource allocation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".