HIV Incidence and Transactional Sex Among Men Who Have Sex With Men in Ningbo, China: Prospective Cohort Study Using a WeChat-Based Platform
Bibliographic record
Abstract
Background: Sexual transmission among men who have sex with men (MSM) has become the major HIV transmission route. However, limited research has been conducted to investigate the association between transactional sex (TS) and HIV incidence in China. Objective: This study aims to investigate HIV incidence and distinguish sociodemographic and sexual behavioral risk factors associated with HIV incidence among MSM who engage in TS (MSM-TS) in China. Methods: We conducted a prospective cohort study using a WeChat-based platform to evaluate HIV incidence among Chinese MSM, including MSM-TS in Ningbo, recruited from July 2019 until June 2022. At each visit, participants completed a questionnaire and scheduled an appointment for HIV counseling and testing on the WeChat-based platform before undergoing offline HIV tests. HIV incidence density was calculated as the number of HIV seroconversions divided by person-years (PYs) of follow-up, and univariate and multivariate Cox proportional hazards regression was conducted to identify factors associated with HIV incidence. Results: A total of 932 participants contributed 630.9 PYs of follow-up, and 25 HIV seroconversions were observed during the study period, resulting in an estimated HIV incidence of 4.0 (95% CI 2.7-5.8) per 100 PYs. The HIV incidence among MSM-TS was 18.4 (95% CI 8.7-34.7) per 100 PYs, which was significantly higher than the incidence of 3.2 (95% CI 2.1-5.0) per 100 PYs among MSM who do not engage in TS. After adjusting for sociodemographic characteristics, factors associated with HIV acquisition were MSM-TS (adjusted hazard ratio [aHR] 3.93, 95% CI 1.29-11.93), having unprotected sex with men (aHR 10.35, 95% CI 2.25-47.69), and having multiple male sex partners (aHR 3.43, 95% CI 1.22-9.64) in the past 6 months. Conclusions: This study found a high incidence of HIV among MSM-TS in Ningbo, China. The risk factors associated with HIV incidence include TS, having unprotected sex with men, and having multiple male sex partners. These findings emphasize the need for developing targeted interventions and providing comprehensive medical care, HIV testing, and preexposure prophylaxis for MSM, particularly those who engage in TS.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".