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When Should Fractional-Dose Vaccines Be Used?

Author

Listed:
  • Francis de Véricourt

    (European School of Management and Technology, 10178 Berlin, Germany)

  • Jérémie Gallien

    (London Business School, London NW1 4SA, United Kingdom)

  • Naireet Ghosh

    (Naveen Jindal School of Management, The University of Texas at Dallas, Richardson, Texas 75080)

Abstract

Problem definition : Vaccination campaigns often face significant operational challenges such as limited stockpiles, vaccine delivery delays, and constrained administration capacity. In such contexts, fractional-dose vaccines have been described in the medical literature as a possible strategy because their efficacy reduction is typically not commensurate with the level of fractionation, allowing greater population coverage. We seek to determine the optimal use and potential benefits of a fractionated vaccine dose with lower and more uncertain efficacy, given the specific supply constraints faced by a country. Methodology/results : We employ a susceptible-infected-recovered (SIR) epidemic model integrating vaccination with full and fractional doses over time. We embed it within a deterministic optimal control model aimed at identifying vaccination policies that minimize total infections during an epidemic, given operational constraints restricting the stockpile, delivery rate, and administration of vaccines. Using a statistical approach described in the clinical literature for estimating the uncertainty around fractional-dose efficacy, we conduct two application case studies grounded in real-world scenarios. Our theoretical analysis provides an intuitive characterization of the optimal vaccination policy that, depending on the epidemic and operational parameters, may utilize a combination of full- and fractional-dose vaccines, either simultaneously or sequentially. We also examine simpler policies that employ a single vaccine dosage throughout the epidemic. We conclude that, although these single-dose policies can often be almost as effective as the optimal policy in averting infections, they are not as robust to the uncertainty affecting fractional-dose vaccine efficacy. Managerial implications : Fractional-dose vaccines, used either alone or in conjunction with full-dose vaccines, present an opportunity to significantly reduce infections during an epidemic in resource-constrained settings. The proportion of fractional-dose vaccines relative to full-dose vaccines in a campaign should generally increase with the maximum vaccine administration rate and decrease with the total antigen stockpile available.

Suggested Citation

  • Francis de Véricourt & Jérémie Gallien & Naireet Ghosh, 2026. "When Should Fractional-Dose Vaccines Be Used?," Manufacturing & Service Operations Management, INFORMS, vol. 28(2), pages 594-609, March.
  • Handle: RePEc:inm:ormsom:v:28:y:2026:i:2:p:594-609
    DOI: 10.1287/msom.2024.1332
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    References listed on IDEAS

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    1. Kenan Arifoglu & Sarang Deo & Seyed M. R. Iravani, 2012. "Consumption Externality and Yield Uncertainty in the Influenza Vaccine Supply Chain: Interventions in Demand and Supply Sides," Management Science, INFORMS, vol. 58(6), pages 1072-1091, June.
    2. Fernando Alvarez & David Argente & Francesco Lippi, 2021. "A Simple Planning Problem for COVID-19 Lock-down, Testing, and Tracing," American Economic Review: Insights, American Economic Association, vol. 3(3), pages 367-382, September.
    3. repec:plo:pone00:0001993 is not listed on IDEAS
    4. Yanhan (Savannah) Tang & Alan Scheller-Wolf & Sridhar Tayur & Emily R. Perito & John P. Roberts, 2025. "Split Liver Transplantation: An Analytical Decision Support Model," Operations Research, INFORMS, vol. 73(4), pages 1785-1804, July.
    5. Tinglong Dai & Soo-Haeng Cho & Fuqiang Zhang, 2016. "Contracting for On-Time Delivery in the U.S. Influenza Vaccine Supply Chain," Manufacturing & Service Operations Management, INFORMS, vol. 18(3), pages 332-346, July.
    6. Laura J. Kornish & Ralph L. Keeney, 2008. "Repeated Commit-or-Defer Decisions with a Deadline: The Influenza Vaccine Composition," Operations Research, INFORMS, vol. 56(3), pages 527-541, June.
    7. Joseph T. Wu & Lawrence M. Wein & Alan S. Perelson, 2005. "Optimization of Influenza Vaccine Selection," Operations Research, INFORMS, vol. 53(3), pages 456-476, June.
    8. Soo-Haeng Cho, 2010. "The Optimal Composition of Influenza Vaccines Subject to Random Production Yields," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 256-277, November.
    9. Kremer, Michael & Więcek, Witold & Ahuja, Amrita & Simoes Gomes Junior, Alexandre & Snyder, Christopher & Tabarrok, Alex & Tan, Brandon, 2021. "Could Vaccine Dose Stretching Reduce COVID-19 Deaths?," CEPR Discussion Papers 16324, Centre for Economic Policy Research.
    10. Stephen E. Chick & Hamed Mamani & David Simchi-Levi, 2008. "Supply Chain Coordination and Influenza Vaccination," Operations Research, INFORMS, vol. 56(6), pages 1493-1506, December.
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