Antiretroviral Therapy Reduces HIV Transmission in Discordant Couples in Rural Yunnan, China
Bibliographic record
Abstract
BACKGROUND: Although HIV treatment as prevention (TasP) via early antiretroviral therapy (ART) has proven to reduce transmissions among HIV-serodiscordant couples, its full implementation in developing countries remains a challenge. In this study, we determine whether China's current HIV treatment program prevents new HIV infections among discordant couples in rural China. METHODS: A prospective, longitudinal cohort study was conducted from June 2009 to March 2011, in rural Yunnan. A total of 1,618 HIV-discordant couples were eligible, 1,101 were enrolled, and 813 were followed for an average of 1.4 person-years (PY). Routine ART was prescribed to HIV-positive spouses according to eligibility (CD4<350 cells/µl). Seroconversion was used to determine HIV incidence. RESULTS: A total of 17 seroconversions were documented within 1,127 PY of follow-up, for an overall incidence of 1.5 per 100 PY. Epidemiological and genetic evidence confirmed that all 17 seroconverters were infected via marital secondary sexual transmission. Having an ART-experienced HIV-positive partner was associated with a lower rate of seroconvertion compared with having an ART-naïve HIV-positive partner (0.8 per 100 PY vs. 2.4 per 100 PY, HR = 0.34, 95%CI = 0.12-0.97, p = 0.0436). While we found that ART successfully suppressed plasma viral load to <400 copies/ml in the majority of cases (85.0% vs. 19.5%, p<0.0001 at baseline), we did document five seroconversions among ART-experienced subgroup. CONCLUSIONS: ART is associated with a 66% reduction in HIV incidence among discordant couples in our sample, demonstrating the effectiveness of China's HIV treatment program at preventing new infections, and providing support for earlier ART initiation and TasP implementation in this region.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".