Long-Term Reductions in Mortality Among Children Under Age 5 in Rural Haiti: Effects of a Comprehensive Health System in an Impoverished Setting
Bibliographic record
Abstract
OBJECTIVES: Evidence regarding the long-term impact of health and other community development programs on under-5 mortality (the risk of death from birth until the fifth birthday) is limited. We compared mortality in a population served by health and other community development programs at the Hôpital Albert Schweitzer (HAS) with national mortality rates among children younger than 5 years for Haiti between 1958 and 1999. METHODS: We collected information on births and deaths in the HAS service area between 1995 and 1999 and assembled previously published under-5 mortality rates at HAS. Published national rates for Haiti served as a comparison. RESULTS: In the early 1970s, the under-5 mortality rate at HAS declined to a level three fourths lower than that in Haiti nationwide. More recently, HAS rates have remained at one half those for Haiti nationwide. Child survival interventions in the HAS service area were substantially higher than in Haiti nationwide although socioeconomic characteristics and levels of childhood malnutrition were similar in both areas. CONCLUSIONS: HAS's programs have been responsible for long-term sustained reduction in mortality among children aged less than 5 years. Integrated systems for health and other community development programs could be an effective strategy for achieving the United Nations Millennium Goal to reduce under-5 mortality two thirds by 2015.
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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 | 0.000 |
| 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".