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Pricing the COVID-19 vaccine: A mathematical approach

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  • Martonosi, Susan E.
  • Behzad, Banafsheh
  • Cummings, Kayla

Abstract

According to the World Health Organization, development of the COVID-19 vaccine is occurring in record time. Administration of the vaccine has started the same year as the declaration of the COVID-19 pandemic. The United Nations emphasized the importance of providing COVID-19 vaccines as a global public good, which is accessible and affordable world-wide. Pricing the COVID-19 vaccines is a controversial topic. We use optimization and game theoretic approaches to model the COVID-19 U.S. vaccine market as a duopoly with two manufacturers Pfizer-BioNTech and Moderna. The results suggest that even in the context of very high production and distribution costs, the government can negotiate prices with the manufacturers to keep public sector prices as low as possible while meeting demand and ensuring each manufacturer earns a target profit. Furthermore, these prices are consistent with those currently predicted in the media.

Suggested Citation

  • Martonosi, Susan E. & Behzad, Banafsheh & Cummings, Kayla, 2021. "Pricing the COVID-19 vaccine: A mathematical approach," Omega, Elsevier, vol. 103(C).
    • Handle: RePEc:eee:jomega:v:103:y:2021:i:c:s0305048321000608
    DOI: 10.1016/j.omega.2021.102451
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    Cited by:

    1. Batabyal, Amitrajeet & Beladi, Hamid, 2022. "City and Regional Demand for Vaccines Whose Supply Arises from Competition in a Bertrand Duopoly," MPRA Paper 113758, University Library of Munich, Germany, revised 28 Jun 2022.
    2. Emanuele Blasioli & Bahareh Mansouri & Srinivas Subramanya Tamvada & Elkafi Hassini, 2023. "Vaccine Allocation and Distribution: A Review with a Focus on Quantitative Methodologies and Application to Equity, Hesitancy, and COVID-19 Pandemic," SN Operations Research Forum, Springer, vol. 4(2), pages 1-32, June.
    3. Bruno Alves-Maciel & Ruben A. Proano, 2024. "Enhancing affordability and profit in a non-cooperative, coordinated, hypothetical pediatric vaccine market via sequential optimization," Health Care Management Science, Springer, vol. 27(3), pages 436-457, September.
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    8. Gilani, Hani & Sahebi, Hadi, 2022. "A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain," Omega, Elsevier, vol. 110(C).
    9. Wang, Fan & Xu, Danni & Zhuo, Xiaopo & Zhang, Chao & Liu, Yaoqi, 2022. "Improving consumer welfare in vaccine market: Pricing, government subsidies and consumer awareness," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    10. Ekinci, Esra & Mangla, Sachin Kumar & Kazancoglu, Yigit & Sarma, P.R.S. & Sezer, Muruvvet Deniz & Ozbiltekin-Pala, Melisa, 2022. "Resilience and complexity measurement for energy efficient global supply chains in disruptive events," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
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