Predictors of SARS-CoV-2 anti-spike IgG antibody levels following two COVID-19 vaccine doses among children and adults in the CHILD COVID-19 Add-On Study
Bibliographic record
Abstract
Vaccination remains the most effective way to prevent SARS-CoV-2 infection or severe outcomes following infection. However, COVID-19 vaccine-induced humoral immune responses vary among individuals and wane over time. The variation and timing of this immune response is not fully understood, particularly in children. This research aims to 1) describe the SARS-CoV-2 anti-spike IgG antibody response to vaccination and 2) identify the health and demographic factors associated with this response among double-vaccinated children and adults in the Canadian CHILD Cohort. This study included a subset of children (n= 153; mean age: 12 ±1.5 years, 46% female) and adults (n= 978; 44 ±6.0 years, 60% female) vaccinated with two doses. Blood samples were collected over two time-points- March 2021 to September 2021 (Phase A) and October 2021 to January 2022 (Phase B) using Dried Blood Spot (DBS) kits. SARS-CoV-2 anti-spike IgG antibody levels were quantified using automated chemiluminescent ELISAs and expressed in scaled luminescence. Demographic, vaccination, and health information were collected via online questionnaires. Associations were determined by linear regression. In our cross-sectional data, we found a seropositivity rate of 95% following two COVID-19 vaccine doses for both children and adults. 14% (n= 157/1131) of participants had evidence of prior COVID-19. In both children and adults, the highest antibody levels were observed around three months post-vaccination and did not differ by biological sex. In a multivariable model, higher antibody levels were associated with: prior SARS-CoV-2 infection (β= 0.21 scaled luminescence units), age <18 years (β= 0.14) and receiving the Moderna mRNA (β= 0.20) or Moderna mRNA and Pfizer BioNTech vaccines (β= 0.20) vs. a combination of Moderna mRNA or Pfizer BioNTech vaccines and AstraZeneca Oxford vaccines. We did not observe any differences in antibody levels between a 3-8 compared to 9–16-week interval between first and second vaccine dose receipt. In summary, we evaluated and characterized the anti-spike IgG antibody response following receipt of two COVID-19 vaccines and found antibody levels to be associated with age, previous SARS-CoV-2 infection, vaccine type, and time since vaccination. Understanding the determinants of vaccine responsiveness is an important research priority that could provide more insights into ways to improve vaccine immunogenicity and efficacy among different population subgroups.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".