BNT162b2 mRNA COVID-19 against symptomatic Omicron infection following a mass vaccination campaign in southern Brazil: A prospective test-negative design study
Bibliographic record
Abstract
BACKGROUND: Evidence regarding effectiveness of BNT162b2 mRNA COVID-19 vaccine against Omicron in Latin America is limited. We estimated BNT162b2 effectiveness against symptomatic COVID-19 in Brazil when Omicron was predominant. METHODS: This prospective test-negative, case-control study was conducted in Toledo, Brazil, following a mass COVID-19 vaccination with BNT162b2. Patients were included if they were aged ≥12 years, sought care for acute respiratory symptoms in the public health system between November 3, 2021 and June 20, 2022, and were tested for SARS-CoV-2 using RT-PCR. In the primary analysis, we determined the effectiveness of two doses of BNT162b2 against symptomatic COVID-19. RESULTS: A total of 4,574 were enrolled; of these, 1,758 patients (586 cases and 1,172 controls) were included in the primary analysis. Mean age was 27.7 years, 53.8 % were women, and 90.1 % had a Charlson comorbidity index of zero. Omicron accounted for >97 % of all identified SARS-CoV-2 variants, with BA.1 and BA.2 accounting for 84.3 % and 12.6 %, respectively. Overall adjusted estimate of two-dose vaccine effectiveness against symptomatic COVID-19 was 46.7 % (95 %CI, 19.9 %-64.6 %) after a median time between the second dose and the beginning of COVID-19 symptoms of 94 days (IQR, 60-139 days). Effectiveness waned from 77.7 % at 7-29 days after receipt of a second dose to <30 % (non-significant) after ≥120 days. CONCLUSION: In a relatively young and healthy Brazilian population, two doses of BNT162b2 provided protection against symptomatic Omicron infection. However, this protection waned significantly over time, underscoring the need for boosting with variant-adapted vaccines in this population prior to waves of disease activity. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov number, NCT05052307 (https://clinicaltrials.gov/ct2/show/NCT05052307).
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".