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248. Balancing Cost and Profit in the Public Sector Vaccine Market
Invited abstract in session MA-15: Machine learning and game theory in healthcare, stream OR in Health Services (ORAHS).
Monday, 8:30-10:00Room: 18 (building: 116)
Authors (first author is the speaker)
| 1. | Banafsheh Behzad
|
| California State University, Long Beach |
Abstract
This study addresses how the government can ensure the cost-effective
procurement of vaccines from private manufacturers. We combine optimization and game theoretic techniques to address cost-effective immunization in the United States. Our optimization model from the government’s perspective minimizes negotiated government costs, while ensuring adequate national vaccination levels, linking dynamics in public and private sectors and incorporating competitive manufacturer behavior. The optimization
model embeds an extant game theoretic price model to capture competitive interactions among manufacturers in the private sector. The model is applied to two different case studies of the US pediatric vaccine market and the COVID-19 vaccine market. The results indicate that markets are at lower risk when high capacity manufacturers have moderate target profits, especially in cases of high demand and asymmetry. Our model can help restabilize a market that experiences a vaccine shortage We also underline scenarios in which the government may be able to prevent monopolies through financial incentives to manufacturers. The results support a paradigm shift from annual contracts to ongoing negotiations, which would enable the government to exercise control over high-risk markets. Our study demonstrates an analytical approach for managerial government officials to influence vaccine prices via the procurement of public-sector goods.
Keywords
- Health Care
- Game Theory
Status: accepted
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