An assessment of mumps vaccine effectiveness by dose during an outbreak in Canada
Bibliographic record
Abstract
BACKGROUND: This investigation was done to assess vaccine effectiveness of one and two doses of the measles, mumps and rubella (MMR) vaccine during an outbreak of mumps in Ontario. The level of coverage required to reach herd immunity and interrupt community transmission of mumps was also estimated. METHODS: Information on confirmed cases of mumps was retrieved from Ontario's integrated Public Health Information System. Cases that occurred between Sept. 1, 2009, and June 10, 2010, were included. Selected health units supplied coverage data from the Ontario Immunization Record Information System. Vaccine effectiveness by dose was calculated using the screening method. The basic reproductive number (R(0)) represents the average number of new infections per case in a fully susceptible population, and R(0) values of between 4 and 10 were considered for varying levels of vaccine effectiveness. RESULTS: A total of 134 confirmed cases of mumps were identified. Information on receipt of MMR vaccine was available for 114 (85.1%) cases, of whom 63 (55.3%) reported having received only one dose of vaccine; 32 (28.1%) reported having received two doses. Vaccine effectiveness of one dose of the MMR vaccine ranged from 49.2% to 81.6%, whereas vaccine effectiveness of two doses ranged from 66.3% to 88.0%. If we assume vaccine effectiveness of 85% for two doses of the vaccine, vaccine coverage of 88.2% and 98.0% would be needed to interrupt community transmission of mumps if the corresponding reproductive values were four and six. INTERPRETATION: Our estimates of vaccine effectiveness of one and two doses of mumps-containing vaccine were consistent with the estimates that have been reported in other outbreaks. Outbreaks occurring in Ontario and elsewhere serve as a warning against complacency over vaccination programs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".