SARS-CoV-2 testing, test positivity and vaccination in social housing residents compared with the general population: a retrospective population-based cohort study
Bibliographic record
Abstract
BACKGROUND: The consideration of unique social housing needs has largely been absent from the COVID-19 response, particularly in tailoring strategies to improve access to testing and vaccine uptake among vulnerable and high-risk populations in Ontario. Given the growing population of social housing residents, this study aimed to compare SARS-CoV-2 testing, positivity, and vaccination rates in a social housing population with those in a general population cohort in Ontario, Canada. METHODS: This population-based cohort study used administrative health data from Ontario to examine SARS-CoV-2 testing, positivity and vaccination rates in social housing residents compared with the general population from 1 January 2020 to 31 December 2021. All comparisons were unadjusted, stratified by sex and age and evaluated using standardised differences. RESULTS: The rates of SARS-CoV-2 PCR testing were lower among younger age groups and higher among older adults within the social housing cohort, compared with the general population cohort. SARS-CoV-2 test positivity was higher in social housing than in the general population among individuals aged 60-79 years (7.9% vs 5.3%, respectively) and 80 years and older (12.0% vs 7.9%, respectively). Overall, 34.3% of social housing residents were fully vaccinated, compared with 29.6% of the general population cohort. However, a smaller proportion of social housing residents had received a booster vaccine (36.7%) compared with the general population (52.4%). CONCLUSION: Improved and targeted outreach strategies are needed to increase the uptake of COVID-19 booster vaccines among social housing residents.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".