Education components of school vaccine mandates: An environmental scan
Bibliographic record
Abstract
BACKGROUND: School vaccine mandates (SVMs) are population health interventions that require monitoring and communicating about vaccination of school-aged children, with an aim of controlling infectious disease outbreaks. While 43 % of World Health Organization member states report having some sort of SVM, their details vary. A newer element of some SVMs is an "education component" requiring compulsory information, education, or counseling of parents/guardians who decline to vaccinate their children for non-medical reasons. METHODS: This environmental scan sought, mapped, and synthesized evidence on the existence, format, and impacts of education components of SVMs in 18 affluent Organization for Economic Co-operation and Development comparator countries. FINDINGS: We found current SVMs in nine of the 18 comparator countries, but education components to those SVMs only in Canada (n = 2) and the U.S. (n = 9), where such policies were made at the provincial/state level. The earliest was implemented in 2011 and most recent has not yet been implemented. Education components were used as requirements for obtaining non-medical exemptions from SVMs, and involved either an informational paper to be read and signed, a counseling or information session from a health professional (public health worker or licensed provider such as family doctor), or an online module to be completed. Peer-reviewed research on in-person sessions suggests association with at least short-term increased vaccine uptake and reduction of non-medical exemptions. Available data on online module education components suggests similar impacts, but research to date is limited. CONCLUSION: SVMs with educational components are uncommon but have been increasing since 2011. The details of these education components vary, although topics covered in online modules are relatively consistent. Evidence to date suggests at least short-term reduction in non-medical exemptions associated with implementation of SVM education components, but additional research is required to follow-up and confirm, especially as regards online education modules.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 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) | 0.006 | 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".