How much to pay for a track and trace system: a simulation model for South Africa
Bibliographic record
Abstract
BACKGROUND: The illicit trade in tobacco reduces the effectiveness of tobacco-control policies. Independent track and trace (T&T) systems are considered one of the most effective measures available to reduce the illicit tobacco trade. South Africa, with an illicit trade estimated at over 35% of the total market, is yet to implement a T&T system. METHODS: An Excel-based simulation model is used to determine the break-even T&T marker cost per pack. At the break-even cost per pack, the government would recover all costs associated with implementing T&T by collecting additional revenues. We conduct a scenario analysis to provide a range of break-even marker costs. FINDINGS: A marker cost of between R2.68 (US$0.17) and R5.24 (US$0.34) per pack allows the South African government to collect enough additional revenue to recover all costs associated with T&T. Implementing such a system would reduce cigarette consumption by between 5% and 11.5%. Given that comparable systems cost significantly less than this range (roughly US$0.02 per pack), the government would in all likelihood be able to implement a system at a cost below the break-even rate, thus generating additional revenue. CONCLUSION: The break-even simulation model provides a practical tool for the government to plan the implementation of T&T and to set up an evaluation criteria for the T&T tender process. The simulations illustrate that implementing T&T in South Africa would both reduce consumption (licit and illicit) and generate additional revenue. With some modifications, the model can be applied to other countries as well.
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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".