Inducing optimal substitution between antibiotics under open access to the resource of antibiotic susceptibility
Bibliographic record
Abstract
This paper designs a bio-economic model to examine the use of substitute antibiotic drugs (analogs) sold by an industry that has open access to the resource of the antibiotic class's susceptibility (treatment effectiveness). Antibiotics are characterized by different expected recovery rates and production costs, which in conjunction with the class's treatment susceptibility determines their relative effectiveness. Our analysis reveals that the high-quality antibiotic drug loses its comparative advantage over time making the low-quality drug the treatment of last resort in the market equilibrium and the social optimum when antibiotic susceptibility cannot replenish. However, when antibiotic susceptibility is renewable, both antibiotics may be used in the long run, and the comparative advantage of the high-quality drug may be restored in the social optimum that allows lowering infection in the long run. We develop the optimal tax/subsidy scheme that would induce antibiotic producers under open access to behave optimally and account for the social cost of infection and value of antibiotic susceptibility. We show that the welfare loss associated with the uncorrected open-access allocation is highest; when the resource of antibiotic susceptibility is non-renewable, high morbidity costs are incurred by individuals, and low social discount rates apply. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".