Reduced Magnitude and Durability of Humoral Immune Responses to COVID-19 mRNA Vaccines Among Older Adults
Bibliographic record
Abstract
BACKGROUND: The magnitude and durability of immune responses to coronavirus disease 2019 (COVID-19) mRNA vaccines remain incompletely characterized in the elderly. METHODS: Anti-spike receptor-binding domain (RBD) antibodies, angiotensin-converting enzyme 2 (ACE2) competition, and virus neutralizing activities were assessed in plasma from 151 health care workers and older adults (range, 24-98 years of age) 1 month following the first vaccine dose, and 1 and 3 months following the second dose. RESULTS: Older adults exhibited significantly weaker responses than younger health care workers for all humoral measures evaluated and at all time points tested, except for ACE2 competition activity after 1 vaccine dose. Moreover, older age remained independently associated with weaker responses even after correction for sociodemographic factors, chronic health condition burden, and vaccine-related variables. By 3 months after the second dose, all humoral responses had declined significantly in all participants, and remained significantly lower among older adults, who also displayed reduced binding antibodies and ACE2 competition activity towards the Delta variant. CONCLUSIONS: Humoral responses to COVID-19 mRNA vaccines are significantly weaker in older adults, and antibody-mediated activities in plasma decline universally over time. Older adults may thus remain at elevated risk of infection despite vaccination.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".