Effectiveness of COVID-19 vaccines against Omicron or Delta symptomatic infection and severe outcomes
Bibliographic record
Abstract
ABSTRACT Background The incidence of SARS-CoV-2 infection, including among those who have received 2 doses of COVID-19 vaccines, increased substantially following the emergence of Omicron in Ontario, Canada. Methods Applying the test-negative study design to linked provincial databases, we estimated vaccine effectiveness (VE) against symptomatic infection and severe outcomes (hospitalization or death) caused by Omicron or Delta between December 6 and 26, 2021. We used multivariable logistic regression to estimate the effectiveness of 2 or 3 COVID-19 vaccine doses by time since the latest dose, compared to unvaccinated individuals. Results We included 16,087 Omicron-positive cases, 4,261 Delta-positive cases, and 114,087 test-negative controls. VE against symptomatic Delta infection declined from 89% (95%CI, 86-92%) 7-59 days after a second dose to 80% (95%CI, 74-84%) after ≥240 days, but increased to 97% (95%CI, 96-98%) ≥7 days after a third dose. VE against symptomatic Omicron infection was only 36% (95%CI, 24-45%) 7-59 days after a second dose and provided no protection after ≥180 days, but increased to 61% (95%CI, 56-65%) ≥7 days after a third dose. VE against severe outcomes was very high following a third dose for both Delta and Omicron (99% [95%CI, 98-99%] and 95% [95%CI, 87-98%], respectively). Conclusions In contrast to high levels of protection against both symptomatic infection and severe outcomes caused by Delta, our results suggest that 2 doses of COVID-19 vaccines only offer modest and short-term protection against symptomatic Omicron infection. A third dose improves protection against symptomatic infection and provides excellent protection against severe outcomes for both variants.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".