Single-Dose Messenger RNA Vaccine Effectiveness Against Severe Acute Respiratory Syndrome Coronavirus 2 in Healthcare Workers Extending 16 Weeks Postvaccination: A Test-Negative Design From Québec, Canada
Bibliographic record
Abstract
BACKGROUND: In Canada, first and second doses of messenger RNA (mRNA) vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were uniquely spaced 16 weeks apart. We estimated 1- and 2-dose mRNA vaccine effectiveness (VE) among healthcare workers (HCWs) in Québec, Canada, including protection against varying outcome severity, variants of concern (VOCs), and the stability of single-dose protection up to 16 weeks postvaccination. METHODS: A test-negative design compared vaccination among SARS-CoV-2 test-positive and weekly matched (10:1), randomly sampled, test-negative HCWs using linked surveillance and immunization databases. Vaccine status was defined by 1 dose ≥14 days or 2 doses ≥7 days before illness onset or specimen collection. Adjusted VE was estimated by conditional logistic regression. RESULTS: Primary analysis included 5316 cases and 53 160 controls. Single-dose VE was 70% (95% confidence interval [CI], 68%-73%) against SARS-CoV-2 infection; 73% (95% CI, 71%-75%) against illness; and 97% (95% CI, 92%-99%) against hospitalization. Two-dose VE was 86% (95% CI, 81%-90%) and 93% (95% CI, 89%-95%), respectively, with no hospitalizations. VE was higher for non-VOCs than VOCs (73% Alpha) among single-dose recipients but not 2-dose recipients. Across 16 weeks, no decline in single-dose VE was observed, with appropriate stratification based upon prioritized vaccination determined by higher vs lower likelihood of direct patient contact. CONCLUSIONS: One mRNA vaccine dose provided substantial and sustained protection to HCWs extending at least 4 months postvaccination. In circumstances of vaccine shortage, delaying the second dose may be a pertinent public health strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".