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Record W7117652231 · doi:10.1186/s12982-025-01317-8

Equity-informed strategies to promote COVID-19 vaccination uptake undertaken by public health units in Ontario, Canada

2025· article· en· W7117652231 on OpenAlexafffundabout
Ana Paula Belon, Naomi Schwartz, Stephen Hunter, Candace I. J. Nykiforuk, Brendan T. Smith, Roman Pabayo

Bibliographic record

VenueDiscover Public Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsPublic Health OntarioWomen and Children’s Health Research InstituteAlberta Health
FundersCanadian Institutes of Health ResearchWomen and Children's Health Research InstituteChildren's Health Research Institute
KeywordsPublic healthVaccinationGovernment (linguistics)PopulationHealth promotion

Abstract

fetched live from OpenAlex

This paper examined local public health strategies to promote COVID-19 vaccination equity in Ontario, Canada between 2020 and 2023. Our descriptive mixed-methods study gathered data from local public health units (PHUs) in Ontario on public health's COVID-19 equity-driven vaccination efforts. PHUs are responsible for delivering local public health services in the province and are provincially mandated to address health equity in their geographic boundaries. Data was collected through a seven-item questionnaire. Open-ended questions were analyzed through an inductive content analysis. From all 34 PHUs, 25 agreed to participate. Eighty-percent of the participating PHUs reported provision of information, community engagement, and improved physical accessibility to COVID-19 vaccines were high/very high priorities. Only 39.1% of PHUs indicated social determinants of health-related data collection as a high/very high priority. Overall, 90% of PHUs reported prioritizing groups, including those with lower socioeconomic status, Indigenous populations, and people experiencing homelessness or precarious housing, in their vaccination response. Four emergent themes included: (1) defining priority populations with data-driven and health equity-oriented processes; (2) promoting vaccination through health equity-informed strategies; (3) prioritizing Indigenous health and sovereignty in vaccination efforts; and (4) recommendations to address health equity-related barriers to COVID-19 vaccination. Examples of recommendations included: adopting culturally-sensitive and context-relevant communication strategies; enabling data linkage of data sources; and providing guidance on the development of intersectoral collaborations. Health equity-informed efforts in COVID-19 vaccination decision-making and actions were broadly adopted to better respond to local needs. Recommendations made by PHUs to address the gaps hindering COVID-19 vaccine equity promotion should be considered before future health crises. Supplementary Information: The online version contains supplementary material available at 10.1186/s12982-025-01317-8.

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 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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.713
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.393
Teacher spread0.285 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2025
Admission routes3
Has abstractyes

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