Single-dose Effectiveness of Mpox Vaccine in Quebec, Canada: Test-negative Design With and Without Adjustment for Self-reported Exposure Risk
Bibliographic record
Abstract
INTRODUCTION: During the 2022 mpox outbreak, the province of Quebec, Canada, prioritized first doses for pre-exposure vaccination of people at high mpox risk, delaying second doses due to limited supply. We estimated single-dose mpox vaccine effectiveness (VE) adjusting for virus exposure risk based only on surrogate indicators available within administrative databases (eg, clinical record of sexually transmitted infections) or supplemented by self-reported risk factor information (eg, sexual contacts). METHODS: We conducted a test-negative case-control study between 19 June and 24 September 2022. Information from administrative databases was supplemented by questionnaire collection of self-reported risk factors specific to the 3-week period before testing. Two study populations were assessed: all within the administrative databases (All-Admin) and the subset completing the questionnaire (Sub-Quest). Logistic regression models adjusted for age, calendar-time and exposure-risk, the latter based on administrative indicators only (All-Admin and Sub-Quest) or with questionnaire supplementation (Sub-Quest). RESULTS: There were 532 All-Admin participants, of which 199 (37%) belonged to Sub-Quest. With exposure-risk adjustment based only on administrative indicators, single-dose VE estimates were similar among All-Admin and Sub-Quest populations at 35% (95% confidence interval [CI]:-2 to 59) and 30% (95% CI:-38 to 64), respectively. With adjustment supplemented by questionnaire information, the Sub-Quest VE estimate increased to 65% (95% CI:1-87), with overlapping confidence intervals. CONCLUSIONS: Using only administrative data, we estimate one vaccine dose reduced the mpox risk by about one-third; whereas, additionally adjusting for self-reported risk factor information revealed greater vaccine benefit, with one dose instead estimated to reduce the mpox risk by about two-thirds. Inadequate exposure-risk adjustment may substantially under-estimate mpox VE.
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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 | 0.001 | 0.008 |
| 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 | 0.000 |
| 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".