Impact of sex work on risk behaviours and their association with HIV positivity among people who inject drugs in Eastern Central Canada: cross-sectional results from an open cohort study
Bibliographic record
Abstract
OBJECTIVES: The objectives of this study were: (1) to examine the correlates of HIV positivity among participants who injected drugs and engaged in sex work (PWID-SWs) in the SurvUDI network between 2004 and 2016, after stratification by sex, and (2) to compare these correlates with those of sexually active participants who did not engage in sex work (PWID non-SWs). DESIGN AND SETTING: This biobehavioural survey is an open cohort of services where participants who had injected in the past 6 months were recruited mainly through harm reduction programmes in Eastern Central Canada. PARTICIPANTS: Data from 5476 participants (9223 visits in total; 785 not included in multivariate analyses due to missing values) were included. METHODS: Participants completed an interviewer-administered questionnaire and provided saliva samples for anti-HIV antibody testing. Generalised estimating equations taking into account multiple participations were used. RESULTS: Baseline HIV prevalence was higher among SWs compared with non-SWs (women: 13.0% vs 7.7%; P<0.001, and men: 17.4% vs 10.8%; P<0.001). PWID-SWs were particularly susceptible to HIV infection as a result of higher levels of vulnerability factors and injection risk behaviours. They also presented different risk-taking patterns than their non-SWs counterparts, as shown by differences in correlates of HIV positivity. Additionally, the importance of sex work for HIV infection varies according to gender, as suggested by a large proportion of injection risk behaviours associated with HIV among women and, conversely, a stronger association between sexual behaviours and HIV positivity observed among men. CONCLUSION: These results suggest that sex work has an impact on the risk of HIV acquisition and that risk behaviours vary according to gender. Public health practitioners should take those specificities into account when designing HIV prevention interventions aimed at PWIDs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".