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Record W6922161216 · doi:10.11575/prism/39437

Hit Me with Your Best Shot: Policy Options to Improve Immunization Rates in Alberta

2020· other· en· W6922161216 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsImmunizationHerd immunityVaccinationCapstonePublic healthRoutine immunizationInfluenza vaccine

Abstract

fetched live from OpenAlex

Both childhood immunizations and seasonal influenza immunizations in Alberta consistently fall below the provincial immunization coverage targets. These targets are set to establish herd immunity, which blocks infectious diseases from spreading throughout communities and causing outbreaks. Alberta’s failure to reach immunization targets may produce adverse health and economic consequences, due to the lack of herd immunity for vaccine-preventable diseases. This Capstone explores immunization policies that promote immunization coverage and address vaccine hesitancy to provide policy options for Alberta to increase immunization coverage. These options can help increase coverage for current immunizations such as childhood and seasonal influenza immunizations and allow Alberta to be better prepared to implement policy for future immunizations such as the COVID-19 immunization. This Capstone examines policies, studies, and reports related to immunization in Alberta, Canada, and throughout the globe. This Capstone attempts to identify reasons for insufficient immunization coverage and recommends policy options to increase immunization coverage in an Alberta-specific context. Recent immunization data suggests that previous efforts were unable to improve childhood immunization coverage in Alberta, as immunization rates remain similar to rates in 2007. Alberta’s seasonal influenza immunization rate remains low at 32% coverage, which is a slight increase from previous years. Alberta focuses seasonal influenza immunization efforts on vulnerable groups yet does not meet coverage targets for these groups. Academic literature identifies vaccine hesitancy as the predominant reasons for choosing not to immunize. Literature also indicates the need to address these concerns rather than focus on educating the public on the benefits of immunization. However, there is little reporting done on Albertan’s reasoning for choosing not to immunize. Alberta Health reports that promoting high immunization rates for disease prevention is a primary health objective but does not detail specific plans to reach this objective other than cover the costs of immunizations. Alberta’s current immunization policy (AIP) faces criticism for being too relaxed and insufficient in addressing vaccine hesitancy and promoting immunization coverage. Alberta recently introduced new legislation to amend Alberta’s Public Health Act with the aim of collecting more accurate immunization reporting information and identifying unimmunized populations. An examination of reports at the national level demonstrates that federal immunization reporting systems provide inaccurate and potentially inconsistent data due to differences in provincial immunization schedules and reporting standards. The Federal government has launched strategies to increase inter-jurisdictional immunization efforts and provide funding grants to jurisdictions with projects aimed at enhancing immunization coverage and reporting. At a provincial level, British Columbia recently created an immunization registry for more accurate reporting. BC also has an Influenza Control Program, which increased seasonal influenza immunization rates but faced issues in implementation. Ontario has a mandatory childhood immunization policy, yet the province has similar childhood immunization coverage rates to provinces without mandatory policies. Ontario’s mandatory policy is criticized for relying on self-reported data, late data collection, and allowing for nonmedical immunization exemptions. Concerning seasonal influenza immunizations, Ontario employs a less-targeted approach than Alberta. This approach produces higher seasonal influenza immunization coverage compared to provinces with more targeted approaches and may be a more economic approach. This Capstone also explores policies from abroad. Each region was chosen to illustrate policy options that could be applied in an Albertan context, as well as options that may not be effective in Alberta. The policy approaches from abroad include incentive programs demonstrated through a large study in Singapore and Australian policy, reporting systems such as the United Kingdom’s “MMR Catch-up Campaign”, the complexities of mandatory immunization policy demonstrated in the evolution of Californian immunization legislation and a comparison of European countries’ immunization rates. Based on a review of Alberta’s current immunization circumstances, and the policy options reviewed, this Capstone recommends three policy options: (1) introduce more comprehensive immunization measures, evaluations, and reporting; (2) launch pilot programs to study the impact of financial incentives for immunizations in Alberta; and (3) expand Alberta’s seasonal influenza immunization program to become more universal rather than targeted, while also considering mandating influenza immunizations for target populations such as healthcare workers. These policy options may also be applicable to future COVID-19 immunization policy. However, prior to any large immunization reforms, Alberta must focus on enhancing immunization reporting and evaluation measures to better understand demographics of unimmunized populations and their reasons for remaining unimmunized.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.085
Threshold uncertainty score0.619

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0050.002
Scholarly communication0.0070.002
Open science0.0050.004
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.038
GPT teacher head0.339
Teacher spread0.301 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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