Vaccine hesitancy around the globe: Analysis of three years of WHO/UNICEF Joint Reporting Form data-2015–2017
Bibliographic record
Abstract
In order to gather a global picture of vaccine hesitancy and whether/how it is changing, an analysis was undertaken to review three years of data available as of June 2017 from the WHO/UNICEF Joint Report Form (JRF) to determine the reported rate of vaccine hesitancy across the globe, the cited reasons for hesitancy, if these varied by country income level and/or by WHO region and whether these reasons were based upon an assessment. The reported reasons were classified using the Strategic Advisory Group of Experts (SAGE) on Immunization matrix of hesitancy determinants (www.who.int/immunization/sage/meetings/2014/october/SAGE_working_group_revised_report_vaccine_hesitancy.pdf). Hesitancy was common, reported by >90% of countries. The list of cited reasons was long and covered 22 of 23 WHO determinants matrix categories. Even the most frequently cited category, risk- benefit (scientific evidence e.g. vaccine safety concerns), accounted for less than one quarter of all reasons cited. The reasons varied by country income level, by WHO region and over time and within a country. Thus based upon this JRF data, across the globe countries appear to understand the SAGE vaccine hesitancy definition and use it to report reasons for hesitancy. However, the rigour of the cited reasons could be improved as only just over 1/3 of countries reported that their reasons were assessment based, the rest were opinion based. With respect to any assessment in the previous five years, upper middle income countries were the least likely to have done an assessment. These analyses provided some of the evidence for the 2017 Assessment Report of the Global Vaccine Action Plan recommendation that each country develop a strategy to increase acceptance and demand for vaccination, which should include ongoing community engagement and trust-building, active hesitancy prevention, regular national assessment of vaccine concerns, and crisis response planning (www.who.int/immunization/sage/meetings/2017/october/1_GVAP_Assessment_report_web_version.pdf).
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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 | 0.029 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.013 | 0.024 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".