Prior infection- and/or vaccine-induced protection against Omicron BA.1, BA.2 and BA.4/BA.5-related hospitalisations in older adults: a test-negative case-control study in Quebec, Canada
Bibliographic record
Abstract
ABSTRACT Background Due to severe outcomes, elderly adults 60 years or older are prioritized for COVID-19 vaccination but accumulated SARS-CoV-2 infection and vaccination likely modifies their risk. We estimated vaccine effectiveness against omicron-associated hospitalisation among elderly adults, by number of doses, prior infection history and time since last immunological event. Methods We conducted a test-negative case-control study among symptomatic elderly adults tested for SARS-CoV-2 in Quebec, Canada during BA.1-, BA.2- and BA.4/5-dominant periods. Relative to unvaccinated, infection-naïve participants, we compared COVID-19 hospitalisation risk by mRNA vaccine dose and/or prior infection (pre-omicron or omicron) history. Findings During BA.1, BA.2 and BA.4/5 periods, two- vs. four-dose vaccine effectiveness alone against hospitalisation was: 78% (95%CI:75-80) vs. 96% (95%CI:93-98); 60% (95%CI:50-97) vs. 84% (95%CI:81-87); and 40% (95%CI:30-49) vs. 68% (95%CI:63-72), respectively, consistent with longer median time since second vs fourth dose. By respective period, effectiveness of pre-omicron vs. omicron infection alone against hospitalisation was: 93% (95%CI:80-97) vs. [not estimable]; 88% (95%CI:50-97) vs. 96% (95%CI:68-99); and 69% (95%CI:30-85) vs. 90% (95%CI:79-95). Regardless of doses (2-5) or prior infection type, hybrid protection was ≥90%, lasting at least 6-8 months during the BA.4/5 period. Prior omicron infection alone reduced BA.4/5 hospitalisation risk by >80% for at least 6-8 months. Interpretation Elderly adults with history of both prior SARS-CoV-2 infection and ≥2 vaccine doses appear well-protected for a prolonged period against omicron hospitalisation, including BA.4/5. Ensuring infection-naïve older adults remain up-to-date with vaccination may further reduce COVID-19 hospitalisations most efficiently. Funding Ministère de la Santé et des Services sociaux du Québec.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".