Effectiveness of BNT162b2 and CoronaVac vaccines in preventing SARS-CoV-2 Omicron infections, hospitalizations, and severe complications in the pediatric population in Hong Kong: a case-control study
Bibliographic record
Abstract
Severe COVID-19 appears to be disproportionately more common in children and adolescents since the emergence of Omicron. More evidence regarding vaccine effectiveness (VE) is urgently needed to assist policymakers in making decisions and minimize vaccine hesitancy among the public. This was a case-control study in the pediatric population using data extracted from the electronic health records database in Hong Kong. Individuals aged 3-17 with COVID-19 confirmed by polymerase chain reaction were included in the study. Each case was matched with up to 10 controls based on age, gender, and index date (within 3 calendar days). The VE of BNT162b2 and CoronaVac in preventing COVID-19, hospitalizations, and severe outcomes were estimated using conditional logistic regression adjusted by patients' comorbidities and medication history during the outbreak from January to August 2022. A total of 36,434 COVID-19 cases, 2231 COVID-19-related hospitalizations, and 1918 severe COVID-19 cases were matched to 109,004, 21,788, and 18,823 controls, respectively. Compared to the unvaccinated group, three doses of BNT162b2 or CoronaVac was associated with reduced risk of infection [VE: BNT162b2: 56.0% (95% CI: 49.6-61.6), CoronaVac: 39.4% (95% CI: 25.6-50.6)], hospitalization [VE: BNT162b2: 58.9% (95% CI: 36.1-73.6), CoronaVac: 51.7% (11.6-73.6)], and severe outcomes [VE: BNT162b2: 60.2% (95% CI: 33.7-76.1), CoronaVac: 42.2% (95% CI: -6.2-68.6)]. Our findings showed that three doses of BNT162b2 or CoronaVac was effective in preventing COVID-19, hospitalizations, and severe outcomes among the pediatric population during Omicron-dominant pandemic, which was further enhanced after a booster dose.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".