HIV Infection Among Sex Workers in Accra: Need to Target New Recruits Entering the Trade
Bibliographic record
Abstract
OBJECTIVE: Description of the epidemiology of HIV infection among sex workers (SW) in Accra, Ghana. METHODS: In all, 1013 SW working out of their homes ( seaters ) or finding customers in bars, hotels, brothels or on the street ( roamers ) were interviewed and tested for HIV. RESULTS: Overall, prevalence of HIV infection was nearly 50% (506 of 1013), varying from 26% (133 of 507) among the roamers to 74% (368 of 496) among the seaters. Profound differences were noted between these two categories of SW with regard to age, number of clients per day, price per instance of intercourse, condom use, and other characteristics. Respectively, 27% and 58% of roamers and seaters were infected with HIV within their first 6 months of sex work, despite a limited number of unprotected sex acts with seropositive clients. Independent risk factors for HIV infection varied between types of SW: age among the roamers; region of origin and duration of sex work among the seaters; number of clients per day, and presence of current or past genital ulcer and gonococcal cervicitis in both groups. CONCLUSION: In Accra, considerable heterogeneity exists in the population of SWs. In both categories of SW, new recruits become rapidly infected with HIV after entering the trade. The 25-fold higher prevalence of HIV among SWs than in the general adult population suggests that in Accra, as in many cities of West Africa, a high fraction of new cases of HIV infection continue to be acquired from SWs. Intervention programs targeting SW should be an essential component of national AIDS control strategies. Special efforts should be made to identify and offer preventive services to new sex workers.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".