Neutralizing antibodies to SARS-CoV-2 variants of concern: a pediatric surveillance study
Bibliographic record
Abstract
Knowledge regarding the pediatric immune response to SARS-CoV-2 infection and/or vaccination remains limited, particularly for the variants of concern (VOC). Our objective was to evaluate the neutralizing antibody response against SARS-CoV-2 VOC in the naturally infected and/or vaccinated pediatric population. Participants aged 5-12 years who presented to either an outpatient clinic or emergency room were eligible for participation in this study. Participants were divided into four groups based on infection and vaccination status. Plasma was tested using immunoassays targeting anti-SARS-CoV-2 IgG, spike protein, and nucleocapsid. A total of 619 participants met study inclusion. Natural infection was identified in 189/619 children (31%), 284/619 were vaccinated (46%) and 69/619 were both naturally infected and vaccinated (11%). Participants that were vaccinated had received one (n = 169/619; 27%) or two (n = 115/619; 19%) vaccine doses. The median time between the 1st and 2nd vaccine doses was 56 days, interquartile range 50-56. A general upward trend in antibody positivity was observed across all VOC as the study proceeded over a 5-month period. Omicron antibody responses were lower than those of other VOC, both in relation to the percentage of positive cases and over time. Neither asthma nor diabetes altered antibody responses, but antibody titres were reduced for a variety of VOC in those children receiving immunotherapy or with leukopenia. This study demonstrated decreased neutralizing antibody responses against the Omicron variant, regardless of past infection or vaccination status. These findings emphasize the need for continued neutralizing antibody surveillance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".