The Epidemiology of HIV Among Sex Workers Around the World: Implications for Research, Programmes, and Policy
Bibliographic record
Abstract
Abstract Globally, sex workers of all genders and identities continue to face disproportionately high burdens of HIV, demonstrating the need for programmes better tailoring services to their unmet needs. The reasons for this high burden are complex, intersecting across behavioural, social, and structural realities experienced by sex workers. Here, we build on systematic reviews of HIV among sex workers and case studies rooted in sex workers’ lived experience to describe: (1) the global HIV burden among sex workers; (2) the factors and determinants that influence the HIV burden; (3) intervention coverage and gaps to reduce HIV-related inequities faced by sex workers, over the past decade. Sex workers living with HIV have not benefited enough from significant increases in HIV treatment among the general population. Engagement in this HIV treatment cascade is hindered by structural factors including stigma, migration, policing, criminalisation, and violence, as well as substance use, which present increasingly concurrent risks with HIV among sex workers. Emerging biomedical HIV prevention innovations exist to support the health and human rights of sex workers and reduce onward transmission risk, but persistent data gaps remain, and should be addressed via community-driven implementation research. Epidemiologic research engaging sex workers who are cismen and transgender persons is similarly crucial. Community empowerment approaches have reduced the odds of HIV infection, highlighting the case for greater investments in structural interventions. These investments, combined with filling data gaps and national action towards sex work decriminalisation alongside legal protections, are critical to achieving reductions in sex workers’ HIV burden.
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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 | 0.019 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".