Cost‐effectiveness of sunflower oil fortification with vitamin A in Tanzania by scale
Bibliographic record
Abstract
In 2011, Tanzania mandated the fortification of edible oil with vitamin A to help address its vitamin A deficiency (VAD) public health problem. By 2015, only 16% of edible oil met the standards for adequate fortification. There is no evidence on the cost-effectiveness of the fortification of edible oil by small- and medium-scale (SMS) producers in preventing VAD. The MASAVA project initiated the production of sunflower oil fortified with vitamin A by SMS producers in the Manyara and Shinyanga regions of Tanzania. A quasi-experimental nonequivalent control-group research trial and an economic evaluation were conducted. The household survey included mother and child pairs from a sample of 568 households before the intervention and 18 months later. From the social perspective, the incremental cost of fortification of sunflower oil could be as low as $0.13, $0.06, and $0.02 per litre for small-, medium-, and large-scale producers, respectively, compared with unfortified sunflower oil. The SMS intervention increased access to fortified oil for some vulnerable groups but did not have a significant effect on the prevention of VAD due to insufficient coverage. Fortification of vegetable oil by large-scale producers was associated with a significant reduction of VAD in children from Shinyanga. The estimated cost per disability-adjusted life year averted for fortified sunflower oil was $281 for large-scale and could be as low as $626 for medium-scale and $1,507 for small-scale producers under ideal conditions. According to the World Health Organization thresholds, this intervention is very cost-effective for large- and medium-scale producers and cost-effective for small-scale producers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".