Perspective: Infant Feeding Policies among Women Living with HIV in Latin America and the Caribbean: Should They Be Updated?
Bibliographic record
Abstract
Among women living with HIV (WLHIV), adherence to highly active antiretroviral treatment (HAART) combined with undetectable maternal viral loads and exclusive breastfeeding during the first 6 mo of life dramatically reduces the risk of mother-to-child transmission of HIV. This knowledge has led to updated World Health Organization infant feeding guidelines for WLHIV, calling for governments to support safe breastfeeding practices among WLHIV who want to breastfeed their infants by providing universal access to HAART, viral load tracking, and high-quality breastfeeding counseling and other needed support across settings. These guidelines eventually led several high-income countries, including the United States and Canada, to revise their infant feeding guidelines that previously contraindicated breastfeeding among WLHIV to incorporate safe, evidence-based breastfeeding recommendations for WLHIV. However, in most of the rest of the Americas, breastfeeding contraindication remains in place. We strongly recommend that all countries in Latin America and the Caribbean consider updating their breastfeeding guidance for WLHIV to allow for safe breastfeeding. Implementing the updated evidence-based recommendations poses major implementation challenges as there is no room for error. Systems-driven implementation science research will be needed to understand how best to codesign, implement, scale up, and sustain intersectoral and equitable person and family-centered policies and programs to empower WLHIV to breastfeed safely if they have the choice to do so.
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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".