“None of it was especially easy”: improving COVID-19 vaccine equity for people with disabilities
Bibliographic record
Abstract
OBJECTIVES: Our study aimed to (1) identify barriers to equitable access to COVID-19 vaccines for Canadians with disabilities and (2) present recommendations made by study participants to improve immunization programs in terms of inclusivity and equitable access. METHODS: We invited Manitobans living with disabilities to participate in online focus groups. Focus groups were conducted across multiple disability experiences, although one focus group was advertised explicitly as offering simultaneous American Sign Language interpretation to encourage people who are d/Deaf or hard of hearing to participate. Participants were asked about their perspectives on the management of COVID-19 public health measures and vaccination program rollout. Participants were also asked about barriers and facilitators of their vaccination experiences and if they had recommendations for improvement. RESULTS: The participants identified three areas where they encountered routine barriers in accessing the COVID-19 vaccines: (1) vaccine information and appointment booking, (2) physical access to vaccination clinics, and (3) vaccination experience. While participants identified specific recommendations to improve vaccine accessibility for people with disabilities, the single most crucial advice consistently identified was to involve people with disabilities in developing accessible immunization programs. CONCLUSION: Meaningful engagement with people living with disabilities in immunization program planning would help ensure that people with disabilities, who already face significant challenges due to COVID-19, are offered the same protections as the rest of the population. These recommendations could be easily transferred to the administration of other large-scale immunization campaigns (e.g., influenza vaccines).
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".