Safety and Efficacy of Preventative COVID Vaccines: The StopCoV Study
Bibliographic record
Abstract
Abstract Background To partially immunize more persons against COVID-19 during a time of limited vaccine availability, Canadian public health officials recommended extending the vaccine dose interval and brand mixing. Impact on the antibody response among the older ambulatory population was unclear. Methods Decentralized prospective cohort study with self-report of adverse events and collection of dried blood spots. Data is presented for 1193 (93%) of the 911 older (aged >70 years) and 375 younger (30-50 years) recruits. Findings Local and systemic reactivity rates were high but short-lived, particularly in the younger cohort and with mRNA-1273 vaccine. After a single COVID-19 vaccine, 84% younger but only 46% older participants had positive IgG antibodies to both spike protein and receptor binding domain (RBD) antigens, increasing to 100/98% with the second dose respectively. In multivariable linear regression model, lower normalized IgG RBD antibody ratios two weeks after the second dose were statistically associated with older age, male gender, cancer diagnosis, lower body weight, BNT162b2 relative to mRNA-1273 and longer dose intervals. Antibody ratios in both cohorts declined 12 weeks post second vaccine dose. Interpretation We report success of a decentralized serology study. Antibody responses were higher in the younger than older cohort and were greater for those with at least one mRNA-1273 dose. The immunity threshold is unknown but correlations between binding and neutralizing antibodies are strongly positive. Trends with time and at breakthrough infection will inform vaccine booster strategies. Funding Supported by the Public Health Agency of Canada and the University Health Network Foundation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".