HIV Prevalence, Virological Suppression, and Consistent Condom Use among Social Venue-Going Men in Zimbabwe: Insights from the 2022 Priorities for Local AIDS Control Efforts (PLACE) Surveys
Bibliographic record
Abstract
Abstract Introduction Men attending social venues face barriers to accessing HIV prevention and care services. These venues—such as bars, guesthouses, nightclubs, and transport hubs—facilitate new sexual partnerships but lack cohesive social networks, making it challenging to design and implement effective HIV prevention strategies. Men who attend social venues are more likely to pay for sex, potentially increasing their risk of acquiring or transmitting HIV. However, data on how HIV-related behaviours and service engagement differ between men who do and do not pay for sex among those attending venues remain limited. This study examines whether men who pay for sex have higher rates of HIV prevalence, lower rates of virological suppression, and poor HIV-prevention-related behaviours compared to those who do not. Methods Using the Priorities for Local AIDS Control Efforts (PLACE) methodology, we collected cross-sectional data from April to December 2022 across 190 venues in four cities and towns in Zimbabwe. Participants underwent finger-prick HIV testing; those testing positive provided dried blood spots (DBS) for viral load measurement. We also collected sexual behaviour data, including condom use. We applied survey weights and used weighted Poisson regression models with robust standard errors to investigate factors associated with HIV status, virological suppression, and condom use among venue-going men, treating paying for sex as the primary exposure variable. All reported percentages are weighted. Results Among venue-going 2,827 men, 984 (40.1%) reported paying for sex in the past 12 months, and 531 (15.1%) reported consistent condom use in the past month. Overall, HIV prevalence was 10.7%. Among men living with HIV, virological suppression was 67.9%. In adjusted analyses, there were no significant associations between paying for sex and HIV status (adjusted prevalence ratio (aPR) = 0.89, 95% CI: 0.52–1.55), self-reported consistent condom use in the past month (aPR = 0.87, 95% CI: 0.57–1.34), or rates of virological suppression among men living with HIV (aPR = 1.03, 95% CI: 0.75–1.42) Conclusion Findings indicate substantial HIV risk and suboptimal prevention and treatment engagement among men frequenting social venues, irrespective of paying for sex. Therefore, targeted interventions are needed for both paying and non-paying men.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".