Consensus statement: Supporting Safer Conception and Pregnancy For Men And Women Living with and Affected by HIV
Bibliographic record
Abstract
Safer conception interventions reduce HIV incidence while supporting the reproductive goals of people living with or affected by HIV. We developed a consensus statement to address demand, summarize science, identify information gaps, outline research and policy priorities, and advocate for safer conception services. This statement emerged from a process incorporating consultation from meetings, literature, and key stakeholders. Three co-authors developed an outline which was discussed and modified with co-authors, working group members, and additional clinical, policy, and community experts in safer conception, HIV, and fertility. Co-authors and working group members developed and approved the final manuscript. Consensus across themes of demand, safer conception strategies, and implementation were identified. There is demand for safer conception services. Access is limited by stigma towards PLWH having children and limits to provider knowledge. Efficacy, effectiveness, safety, and acceptability data support a range of safer conception strategies including ART, PrEP, limiting condomless sex to peak fertility, home insemination, male circumcision, STI treatment, couples-based HIV testing, semen processing, and fertility care. Lack of guidelines and training limit implementation. Key outstanding questions within each theme are identified. Consumer demand, scientific data, and global goals to reduce HIV incidence support safer conception service implementation. We recommend that providers offer services to HIV-affected men and women, and program administrators integrate safer conception care into HIV and reproductive health programs. Answers to outstanding questions will refine services but should not hinder steps to empower people to adopt safer conception strategies to meet reproductive goals.
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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 | 0.118 | 0.211 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.010 | 0.013 |
| Research integrity | 0.028 | 0.033 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".