Is Sexual Contact With Sex Workers Important in Driving the HIV Epidemic Among Men in Rural Zimbabwe?
Bibliographic record
Abstract
OBJECTIVE: To establish the importance of commercial sex in driving the HIV epidemic in the general population by determining risk factors for HIV infection among male mine and farm workers and estimating the fraction of prevalent HIV infections attributable to sexual contact with sex workers (SWs). SETTING: Five commercial farms and 2 mines in Mashonaland West, Zimbabwe. METHODS: A cross-sectional interviewer-administered questionnaire and urine survey of 1405 male workers. Urine samples were tested for HIV antibodies by a particle agglutination test and enzyme-linked immunosorbent assay and for Chlamydia trachomatis and Neisseria gonorrhoeae using a polymerase chain reaction assay. RESULTS: The overall prevalence of HIV antibodies was 27.3% (95% confidence interval [CI]: 24.8 to 29.5), that of C. trachomatis was 1.5% (95% CI: 1.0 to 2.1), and that of N. gonorrhoeae was 0.5% (95% CI: 0.1 to 0.9). A total of 48.4% (95% CI: 45.8 to 51.0) of men reported ever having had sexual contact with an SW, and 29.3% (95% CI: 26.9 to 31.7) reported contact in the past year. HIV was more common among men who reported SW contact on univariate (1.9% [95% CI: 1.5 to 2.4]) and multivariate (1.4% [95% CI: 1.0 to 1.8]) analysis after adjusting for confounding. HIV was also strongly associated with self-reported genital ulceration in the previous 6 months (adjusted odds ratio [OR] = 3.1, 95% CI: 2.2 to 4.3). Genital ulceration and SW contact were highly correlated. A total of 19.6% of HIV infections in men could be attributed to ever having had sexual contact with an SW (95% CI: 10.8 to 27.6). CONCLUSIONS: An appreciable proportion of HIV infection in men is attributable to sexual contact with SWs. Consideration should be given to developing interventions that target male clients of SWs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".