Emulating value-chains of fast-moving consumer goods to improve uptake of co-packaged ORS and zinc for childhood diarrhoea: evaluation of the ColaLife trial
Bibliographic record
Abstract
Introduction Oral rehydration salts (ORS) and zinc comprise the globally recommended treatment for diarrhoea in children aged <5 years. However, limited access contributes to low uptake of this treatment and subsequently high rates of morbidity and mortality among this age group in low-income and middle-income countries. We adopted approaches used for private-sector value-chains of fast-moving consumer-goods, involving the simultaneous stimulation of supply and demand. These approaches were applied to the introduction of an innovative co-packaged diarrhoea-treatment kit (ORSZ co-pack) to increase ORS and zinc coverage at the community level in Zambia. Methods We tested our approach using an observational pre–post test study design in two intervention districts in rural Zambia (Kalomo and Katete), each with a matched comparator (Monze and Petauke, respectively). We assessed the effect on coverage, of ORS and zinc as well as ORS alone, by conducting household surveys of a total of 2458 and 2477 caregivers of children aged <5 years at baseline and endline, respectively, across the four districts. We also assessed whether the source of ORS (public or private sector) changed following the intervention. Results Both intervention districts experienced significant increases in coverage of ORS and zinc from <1% at baseline to 46.9% and 46.3% in Kalomo and Katete, respectively. Uptake in the comparator districts remained low at 1.7% and 0.6% in Monze and Petauke, respectively. For the secondary outcome examining ORS coverage (with or without zinc), the intervention was associated with a significant increase in Kalomo versus Monze, but not in Katete versus Petauke. There was a clear shift from the public to the private sector, and specifically to the use of the ORSZ co-pack. Conclusion Implementation of a value-chain creation approach for an innovative, over-the-counter, co-packaged diarrhoea-treatment kit can significantly improve the coverage of ORS and zinc.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".