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Record W3094013382 · doi:10.1016/j.vaccine.2020.09.063

Global assessment of national mandatory vaccination policies and consequences of non-compliance

2020· article· en· W3094013382 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueVaccine · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsMcGill University Health CentreMcGill University
FundersNational Institute of Allergy and Infectious DiseasesUniversity of Minnesota
KeywordsMandateVaccinationCompliance (psychology)Vaccination policyLimitingMedicineBusinessEnvironmental healthPolitical sciencePsychologyLawImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Declining vaccination coverage and increasing hesitancy is a worldwide concern. Many countries have implemented mandatory vaccination policies to promote vaccination. However, mandatory vaccination policies differ significantly by country. Beyond case studies, no comprehensive study has compared these policies or the penalties for non-compliance on a global scale. METHODS: We conducted extensive keyword, policy, and literature searches to identify mandatory national vaccination policies globally and develop a comprehensive database. A mandatory national vaccination policy was defined as a policy from a national authority that requires individuals to receive at least one vaccination based on age or to access a service. Two reviewers independently evaluated evidence for a mandate and whether non-compliance penalties were incorporated. We categorized penalties into four types, based on the nature of the penalty. These penalties impact an individual's financial, parental rights, educational (i.e., child's school entry and access), and liberty status. We rated the severity within each category. RESULTS: Of 193 countries investigated, 54% (n = 105) had evidence of a nationwide mandate as of December 2018. The frequency, types, and severity of penalties varied widely across all regions. We found that 59% (n = 62) of countries with national mandates defined at least one penalty for non-compliance with a vaccine mandate. Among those, educational penalties (i.e., limiting a child's entry or ongoing access to school) were the most common (69%; n = 43), with most countries with educational penalties refusing school enrollment until vaccination requirements are met (81%; n = 35). CONCLUSION: We undertook a comprehensive assessment of national mandatory vaccination policies and identified a diversity of penalties in place to promote compliance. Our results highlight the need to critically evaluate the implementation of non-compliance penalties in order to determine their effectiveness and to define best practices for sustaining high vaccination uptake worldwide.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.371
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it