Progress towards the UN Commission on Life Saving Commodities recommendations after five years: a longitudinal assessment
Bibliographic record
Abstract
Background In 2012, the UN Commission on Life Saving Commodities (UNCoLSC) articulated a series of recommendations to expand access to 13 life-saving reproductive, maternal, newborn and child health (RMNCH) commodities with the greatest potential to reduce preventable deaths. We conducted a five-year longitudinal assessment of progress towards achieving these recommendations among countries in sub-Saharan Africa and Southeast Asia. Methods Between 2013 and 2017, national reviews were undertaken at two time points among 14 countries with a high burden of preventable maternal-child deaths who were receiving support from a multi-UN agency RMNCH technical support and financing mechanism. Data were drawn from national health documentation (e.g. strategic plans, policies, guidelines); logistics management information systems; national household and health facility surveys; and interviews with governments and development partners. Results Over time, the percent of health facilities with stock availability showed a statistically significant increase of five percentage points from 69% to 74% (median). Recent training at health facility also displayed a significant increase of eight percentage points from 38% to 46% (median). National RMNCH coordination mechanisms, treatment guidelines, and national training curricula and job-aids were near fully redressed. However, countries continue to face persistent supply chain challenges including national stock-outs, tracking commodities throughout the supply chain, and strengthening medicine control laboratories. Conclusions While substantial progress has been made in improving access to life-saving commodities, including stock availability and workforce training at health facilities, additional efforts are required to improve regulatory efficiency, enhance commodity quality and safety, and reduce supply chain fragmentation.
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 | 0.026 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".