Live virus neutralizing antibodies against pre and post Omicron strains in food and retail workers in Québec, Canada
Bibliographic record
Abstract
Abstract Objectives To assess the neutralization activity pre and post Omicron BA.1 emergence in a unique cohort of 280 vaccinated restaurant/bar, grocery and hardware store workers in Québec, Canada. Methods Participants were recruited during the emergence of Omicron BA.1 variant. The neutralizing activity of participant sera was assessed by microneutralization assay. Results Serum neutralizing antibody (NtAb) titers of all participants against the ancestral SARS-CoV-2 strain was comparable with the response against Delta variant, however, their response was significantly reduced against Omicron BA.1, BA2, BA.2.12.1, BA.4 and BA.5. The neutralizing response of each group of workers was similar. Individuals who received 2 doses of vaccine had significantly reduced NtAb titers against all SARS-CoV-2 strains compared to those infected and then vaccinated (≥1 dose), vaccinated (≥2 doses) and then infected, or those who received 3 doses of vaccine. Participants vaccinated with 2 or 3 doses of vaccine and then infected had the highest NtAb titers against all SARS-CoV-2 strains tested. Conclusion We assessed for the first time the NtAb response in food and retail workers. Individuals infected after ≥2 doses of vaccine had the highest levels of NtAbs against Omicron BA.1, BA.2 and BA.5 variants and might be better protected against reinfection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".