Prevention of mother-to-child transmission of HIV in a refugee camp setting in Tanzania
Bibliographic record
Abstract
The objective of this article is to describe the results of a 2-year pilot programme implementing prevention of mother to child HIV transmission (PMTCT) in a refugee camp setting. Interventions used were: community sensitization, trainings of healthcare workers, voluntary counselling and HIV testing (VCT), infant feeding, counselling, and administration of Nevirapine. Main outcome measures include: HIV testing acceptance rates, percentage of women receiving post test counselling, Nevirapine uptake, and HIV prevalence among pregnant women and their infants. Ninety-two percent of women (n=9,346) attending antenatal clinics accepted VCT. All women who were tested for HIV received their results and posttest counselling. The HIV prevalence rate among the population was 3.2%. The overall Nevirapine uptake in the camp was 97%. Over a third of women were repatriated before receiving Nevirapine. Only 14% of male counterparts accepted VCT. Due to repatriation, parent's refusal, and deaths, HIV results were available for only 15% of infants born to HIV-infected mothers. The PMTCT programme was successfully integrated into existing antenatal care services and was acceptable to the majority of pregnant women. The major challenges encountered during the implementation of this programme were repatriation of refugees before administration of Nevirapine, which made it difficult to measure the impact of the PMTCT programme.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".