Report on WHO meeting on immunization in older adults: Geneva, Switzerland, 22–23 March 2017
Bibliographic record
Abstract
Many industrialized countries have implemented routine immunization policies for older adults, but similar strategies have not been widely implemented in low- and middle-income countries (LMICs). In March 2017, the World Health Organization (WHO) convened a meeting to identify policies and activities to promote access to vaccination of older adults, specifically in LMICs. Participants included academic and industry researchers, funders, civil society organizations, implementers of global health interventions, and stakeholders from developing countries with adult immunization needs. These experts reviewed vaccine performance in older adults, the anticipated impact of adult vaccination programs, and the challenges and opportunities of building or strengthening an adult and older adult immunization platforms. Key conclusions of the meeting were that there is a need for discussion of new opportunities for vaccination of all adults as well as for vaccination of older adults, as reflected in the recent shift by WHO to a life-course approach to immunization; that immunization in adults should be viewed in the context of a much broader model based on an individual's abilities rather than chronological age; and that immunization beyond infancy is a global priority that can be successfully integrated with other interventions to promote healthy ageing. As WHO is looking ahead to a global Decade of Healthy Ageing starting in 2020, it will seek to define a roadmap for interdisciplinary collaborations to integrate immunization with improving access to preventive and other healthcare interventions for adults worldwide.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 0.017 |
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".