Two-dose SARS-CoV-2 vaccine effectiveness with mixed schedules and extended dosing intervals: test-negative design studies from British Columbia and Quebec, Canada
Bibliographic record
Abstract
ABSTRACT Background The Canadian COVID-19 immunization strategy deferred second doses and allowed mixed schedules. We compared two-dose vaccine effectiveness (VE) by vaccine type (mRNA and/or ChAdOx1), interval between doses, and time since second dose in two of Canada’s larger provinces. Methods Two-dose VE against infections and hospitalizations due to SARS-CoV-2, including variants of concern, was assessed between May 30 and October 2, 2021 using test-negative designs separately conducted among community-dwelling adults ≥18-years-old in British Columbia (BC) and Quebec, Canada. Findings In both provinces, two doses of homologous or heterologous SARS-CoV-2 vaccines were associated with ∼95% reduction in the risk of hospitalization. VE exceeded 90% against SARS-CoV-2 infection when at least one dose was an mRNA vaccine, but was lower at ∼70% when both doses were ChAdOx1. Estimates were similar by age group (including adults ≥70-years-old) and for Delta-variant outcomes. VE was significantly higher against both infection and hospitalization with longer 7-8-week vs. manufacturer-specified 3-4-week interval between doses. Two-dose mRNA VE was maintained against hospitalization for the 5-7-month monitoring period and while showing some decline against infection, remained ≥80%. Interpretation Two doses of mRNA and/or ChAdOx1 vaccines gave excellent protection against hospitalization, with no sign of decline by 5-7 months post-vaccination. A 7-8-week interval between doses improved VE and may be optimal in most circumstances. Findings indicate prolonged two-dose protection and support the use of mixed schedules and longer intervals between doses, with global health, equity and access implications in the context of recent third-dose proposals.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".