A14 Estimating time since HIV infection using next-generation sequencing data: A unique tool to help understand HIV prevention among high-risk young women in Ukraine
Bibliographic record
Abstract
Abstract The transitions study examines HIV risk among adolescent girls and young women through their sexual life course from first sex, to past and current engagement in casual sex, transactional sex, and, for some, formal sex work (FSW). Understanding the timing of HIV infection and the circumstances around early infection in young females is critical to HIV prevention interventions. We inferred time since HIV infection using next-generation sequencing (NGS) of the HIV pol gene isolated from cross-sectional samples among high-risk young women in Dnipro, Ukraine. Dried blood spots were collected on Whatman 903 cards from young women aged 14–24 engaged in casual sex (n = 894), transactional sex (n = 464), and FSW (n = 452). The HIV pol gene was sequenced using an in-house NGS HIV drug resistance mutation genotyping assay. Time since HIV infection was inferred using an online tool as described by Puller et al. (2017) freely available at https://hiv.biozentrum.unibas.ch/ETI/. The mean estimated time since HIV infection (ETI) for participants engaged in casual sex, transactional sex, and FSW is 1.98, 1.84, and 3.01 years, respectively. ETI was used to determine the duration of HIV infection for each participant and compared to the number of sexually active years prior to FSW. Among FSW, 61 per cent of participants were infected with HIV prior to entry into sex work. In general, ETI from NGS data suggests that FSWs were infected with HIV before entry into FSW. Expansion of targeted prevention programs beyond FSW could play an important role in mitigating HIV transmission at the population level.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".