Racial disparities in HIV pre-exposure prophylaxis (PrEP) awareness and uptake among white, Black, and Indigenous men in Canada: Analysis of data from the I’m Ready national HIV self-testing study
Bibliographic record
Abstract
OBJECTIVES: Black and Indigenous men in Canada continue to experience significant and disproportionate burden of new HIV infection. The purpose of this study was to understand racial differences in PrEP awareness and use, and PrEP cascade among white, Black, and Indigenous men in Canada with the intention to provide evidence for immediate action in our publicly funded health care system. METHODS: We performed a secondary analysis (n = 4294) of cross-sectional data from the I'm Ready national HIV self-testing research program launched in June 2021 and running through December 2023. Binary logistic regression was used to assess racial differences in PrEP awareness and uptake. A proposed PrEP cascade was developed using the data on awareness, uptake, and retention in PrEP care. RESULTS: Black participants (OR = 0.34, CI 0.29, 0.39), who are gbMSM (OR = 0.27, CI 0.21, 0.35), aged 18-45 (OR = 0.35, CI 0.30, 0.40), living in urban (OR = 0.41, CI 0.33, 0.51) or rural areas (OR = 0.33, CI 0.26, 0.44), and who are PrEP-eligible (OR = 0.34, CI 0.28, 0.40), were less likely to be aware of PrEP than white participants. Indigenous participants (OR = 0.57, CI 0.44, 0.75), aged 18-45 (OR = 0.57, CI 0.43, 0.75), living in rural communities (OR = 0.15, CI 0.25, 0.57), and who are PrEP-eligible (OR = 0.62, CI 0.46, 0.83), were less likely to be aware of PrEP than white participants. For PrEP uptake, Black participants (OR = 0.61, CI 0.46, 0.82), aged 18-45 (OR = 0.59, CI 0.44, 0.80), living in rural communities (OR = 0.44, CI 0.23, 0.84), and PrEP-eligible (OR = 0.62, CI 0.46, 0.85), were less likely to be on PrEP than white participants. Also, Indigenous men living in urban areas were more likely to be on PrEP than white participants (OR = 1.65, CI 1.01, 2.69). CONCLUSION: Community-based and public health interventions are immediately needed to increase PrEP awareness, access, and uptake for Black and Indigenous communities in Canada.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".