COVID-19 Vaccination Uptake Among Individuals With Immune-mediated Inflammatory Diseases in Ontario, Canada, Between December 2020 and October 2021: A Population-based Analysis
Bibliographic record
Abstract
OBJECTIVE: We assessed coronavirus disease 2019 (COVID-19) vaccine uptake among individuals with immune-mediated inflammatory diseases (IMIDs) and the Ontario general population. METHODS: We studied all residents aged ≥ 16 years who were alive and enrolled in the Ontario Health Insurance Plan as of December 14, 2020, when vaccination commenced (n = 12,435,914). Individuals with rheumatoid arthritis (RA), ankylosing spondylitis (AS), psoriatic arthritis (PsA), psoriasis (PsO), and inflammatory bowel disease (IBD) were identified using established disease-specific case definitions applied to health administrative data. Vaccination status was extracted from the provincial COVaxON registry. Weekly cumulative proportions of first and second doses up until October 3, 2021, were expressed as the vaccinated percentage of each disease group, compared to the general Ontario population, and stratified by age. RESULTS: By October 3, 2021, the cumulative percentage with at least 1 dose was 82.1% for the general population, 88.9% for those with RA, 87.4% for AS, 90.6% for PsA, 87.3% for PsO, and 87.0% for IBD. There was also a higher total cumulative percentage with 2 doses among IMIDs (83.8-88.2%) vs the general population (77.9%). The difference was also evident when stratifying by age. Individuals with IMIDs in the youngest age group initially had earlier uptake than the general population but remain the lowest age group with 2 doses (70.6% in the general population vs. 73.7-79.2% across IMID groups). CONCLUSION: While implementation of COVID-19 vaccination programs has differed globally, these Canadian estimates are the first to reassuringly show higher COVID-19 vaccine uptake among individuals with IMIDs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".