Vaccination programs for older adults in an era of demographic change
Bibliographic record
Abstract
OBJECTIVES: Populations are aging worldwide. This paper summarizes some of the challenges and opportunities due to the increasing burden of infectious diseases in an aging population. RESULTS: Older adults typically suffer elevated morbidity from infectious disease, leading to increased demand for healthcare resources and higher healthcare costs. Preventive medicine, including vaccination can potentially play a major role in preserving the health and independence of older adults. However, this potential of widespread vaccination is rarely realized. Here, we give a brief overview of the problem, discuss concrete obstacles and the potential for expanded vaccination programs to promote healthy aging. CONCLUSION: The increasing healthcare burden of infectious diseases expected in aging populations could, to a large extent, be reduced by achieving higher vaccination coverage among older adults. Vaccination can thus contribute to healthy aging, alongside healthy diet and physical exercise. The available evidence indicates that dedicated programs can achieve substantial improvements in vaccination coverage among older adults, but more research is required to assess the generalizability of the results achieved by specific interventions (see Additional file 1).
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".