Exploring off-label vaccine use: a survey of the global national immunization technical advisory group network
Bibliographic record
Abstract
BACKGROUND: National Immunization Technical Advisory Groups (NITAGs) are crucial for enhancing vaccine use in immunization programs, particularly through off-label recommendations. This study sought to assess the adoption and trends of off-label vaccine recommendations made by NITAGs across low-, middle-, and high-income countries since the COVID-19 pandemic. METHODS: An online survey was distributed to NITAG representatives in World Health Organization (WHO) member states, asking questions related to off-label use of vaccines including policies, procedures, legislation, and regulations for NITAGs in participants' countries. Respondents across all six WHO regions were invited to participate. RESULTS: Respondents from 76 countries participated in the survey (55 %) were NITAG representatives, and 45 % were immunization program managers or from the NITAG secretariat). Most respondents 52 (68 %) reported their NITAG makes off-label recommendations, 18 (24 %) indicated their NITAG does not make off-label recommendations, and 6 (8 %) were unsure of their NITAG's role. There was a noticeable shift relating to off-label vaccine recommendations observed pre, during, and post-pandemic period. Prior to 2022, 25 (48 %) respondents indicated their country recommended off-label vaccines, 11 (21 %) specified off-label recommendations were limited to emergencies as temporary or conditional expansions, and 6 (12 %) were unsure. After 2022, 30 (58 %) respondents indicated their country recommended off-label vaccines, 4 (8 %) specified off-label recommendations were limited to emergencies as temporary or conditional expansions, 18 (35 %) selected no, and 0 (0%) were unsure. While most countries make off-label recommendations, few (15 %) have policies and procedures to support implementation. CONCLUSIONS: Although WHO broadly provides guidance on the mandate and core functions of NITAGs, globally, they have differing mandates and operational capacities related to off-label vaccine use. These findings suggest the need for increased awareness of off-label vaccine recommendations and strengthened dialogue around implementation of off-label recommendations.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".