Initial COVID-19 Vaccination is Highly Immunogenic and Safe: A Stop the Spread Ottawa Cohort Analysis
Bibliographic record
Abstract
INTRODUCTION: Predictors of COVID-19 vaccine immunogenicity and the influence of prior SARS-CoV-2 infection require elucidation. METHODS: Stop the Spread Ottawa is a prospective cohort of individuals at-risk for or who have been infected with SARS-CoV-2, initially enrolled for 10 months beginning October 2020. This analysis focuses on safety and immunogenicity of the initial two doses of COVID-19 vaccine. RESULTS: Post-vaccination data with blood specimens were available for 930 participants. 22.8% were SARS-CoV2 infected prior to first vaccine dose. Cohort characteristics include: median age 44 (22, 56), 66.6% female, 89.0% white, 83.2% employed. 38.1% reported two or more comorbidities and 30.8% reported immune compromising condition(s). Over 95% possessed IgG spike and RBD titres 3 months post second vaccine dose. By multivariable analysis, increasing age and high-level immune compromise predicted diminishing IgG spike and RBD titres at month 3 post second dose. IgG spike and RBD titres were higher immediately post vaccination in those with SARS-CoV-2 infection prior to first vaccination and spike titres were higher at 6 months in those with wider time intervals between dose 1 and 2. IgG spike and RBD titres and neutralization were generally similar by sex, weight and whether receiving homogeneous or heterogeneous combinations of vaccines. Common post dose 1 vaccine symptoms included fatigue (64.7%), injection site pain (47.5%), headache (27.2%), fever/chills (26.2%), body aches (25.3%). These symptoms are similar with subsequent doses. CONCLUSION: The initial two COVID-19 vaccine doses are safe, well-tolerated and highly immunogenic across a broad spectrum of vaccine recipients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".