Physical and Sexual Violence Affecting Female Sex Workers in Abidjan, Côte d'Ivoire: Prevalence, and the Relationship with the Work Environment, HIV, and Access to Health Services
Bibliographic record
Abstract
BACKGROUND: Violence is a human rights violation, and an important measure in understanding HIV among female sex workers (FSW). However, limited data exist regarding correlates of violence among FSW in Côte d'Ivoire. Characterizing prevalence and determinants of violence and the relationship with structural risks for HIV can inform development and implementation of comprehensive HIV prevention and treatment programs. METHODS: FSW > 18 years were recruited through respondent driven sampling (RDS) in Abidjan, Côte d'Ivoire. In total, 466 participants completed a socio-behavioral questionnaire and HIV testing. Prevalence estimates of violence were calculated using crude and RDS-adjusted estimates. Relationships between structural risk factors and violence were analyzed using χ tests and multivariable logistic regression. RESULTS: The prevalence of physical violence was 53.6% (250/466), and sexual violence was 43.2% (201/465) among FSW in this study. Police refusal of protection was associated with physical (adjusted Odds Ratio [aOR]: 2.8; 95% confidence interval [CI]: 1.7 to 4.4) and sexual violence (aOR: 3.0; 95% CI: 1.9 to 4.8). Blackmail was associated with physical (aOR: 2.5; 95% CI: 1.5 to 4.2) and sexual violence (aOR: 2.4; 95% CI: 1.5 to 4.0). Physical violence was associated with fear (aOR: 2.2; 95% CI: 1.3 to 3.1) and avoidance of seeking health services (aOR: 2.3; 95% CI: 1.5 to 3.8). CONCLUSIONS: Violence is prevalent among FSW in Abidjan and associated with features of the work environment and access to care. These relationships highlight layers of rights violations affecting FSW, underscoring the need for structural interventions and policy reforms to improve work environments, and to address police harassment, stigma, and rights violations to reduce violence and improve access to HIV interventions.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".