Prevalence of HIV and sexually transmitted and blood-borne infections, and related preventive and risk behaviours, among gay, bisexual and other men who have sex with men in Montreal, Toronto and Vancouver: results from the Engage Study
Bibliographic record
Abstract
OBJECTIVES: The last Canadian biobehavioural surveillance study of HIV and other sexually transmitted and blood-borne infections (STBBI) among gay, bisexual and other men who have sex with men (GBM) was conducted in 2010. We designed a study to measure STBBI prevalence among GBM in metropolitan Montreal, Toronto and Vancouver and to document related preventive and risk behaviours. METHODS: The Engage Cohort Study used respondent-driven sampling (RDS) to recruit GBM who reported sex with another man in the past 6 months. At baseline, we examined recruitment characteristics of the samples, and the RDS-II-adjusted distributions of socio-demographics, laboratory-confirmed HIV and other STBBI prevalence, and related behaviours, with a focus on univariate differences among cities. RESULTS: A total of 2449 GBM were recruited from February 2017 to August 2019. HIV prevalence was lower in Montreal (14.2%) than in Toronto (22.2%) or Vancouver (20.4%). History of syphilis infection was similar across cities (14-16%). Vancouver had more HIV-negative/unknown participants who reported never being HIV tested (18.6%) than Toronto (12.9%) or Montreal (11.5%). Both Montreal (74.9%) and Vancouver (78.8%) had higher proportions of men who tested for another STBBI in the past 6 months than Toronto (67.4%). Vancouver had a higher proportion of men who used pre-exposure prophylaxis (PrEP) in the past 6 months (18.9%) than Toronto (11.1%) or Montreal (9.6%). CONCLUSION: The three largest cities of Canada differed in HIV prevalence, STBBI testing and PrEP use among GBM. Our findings also suggest the need for scale-up of both PrEP and STI testing among GBM 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".