COVID-19 Vaccination of Individuals with Down Syndrome—Data from the Trisomy 21 Research Society Survey on Safety, Efficacy, and Factors Associated with the Decision to Be Vaccinated
Bibliographic record
Abstract
Individuals with Down syndrome (DS) are among the groups with the highest risk for severe COVID-19. Better understanding of the efficacy and risks of COVID-19 vaccines for individuals with DS may help improve uptake of vaccination. The T21RS COVID-19 Initiative launched an international survey to obtain information on safety and efficacy of COVID-19 vaccines for individuals with DS. De-identified survey data collected between March and December 2021 were analyzed. Of 2172 individuals with DS, 1973 (91%) had received at least one vaccine dose (57% BNT162b2), 107 (5%) were unvaccinated by choice, and 92 (4%) were unvaccinated for other reasons. Most participants had either no side effects (54%) or mild ones such as pain at the injection site (29%), fatigue (12%), and fever (7%). Severe side effects occurred in <0.5% of participants. About 1% of the vaccinated individuals with DS contracted COVID-19 after vaccination, and all recovered. Individuals with DS who were unvaccinated by choice were more likely to be younger, previously recovered from COVID-19, and also unvaccinated against other recommended vaccines. COVID-19 vaccines have been shown to be safe for individuals with DS and effective in terms of resulting in minimal breakthrough infections and milder disease outcomes among fully vaccinated individuals with DS.
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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 | 0.004 |
| 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 | 0.000 |
| 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".