The Centers for Disease Control and Prevention’s (CDC) significant patronage of U.S. vaccines affords them leverage in negotiating public-sector prices that prevent the formation of monopolies. This work is the first in the literature to incorporate the CDC as a strategic agent in the vaccine pricing market.​ Our optimization model from the CDC’s perspective captures US goals, links dynamics in public and private sectors, and incorporates competitive manufacturer behavior via an embedded Bertrand-Edgeworth-Chamberlin game. The model is validated in an extended case study of the diphtheria, tetanus, and acellular pertussis (DTaP) vaccine and is extended to the U.S. COVID-19 vaccine duopoly that was initially defined by Pfizer-BioNTech and Moderna through February 2021. The study indicates that our model can help re-stabilize a market that experiences a vaccine shortage and that the CDC might mitigate the same shortage using strategies that depend on which manufacturer is limited. These results support a paradigm shift from annual pricing contracts to ongoing negotiations in pediatric vaccine markets, which would enable the CDC to exercise more granular control over high-risk markets. Furthermore, the results suggest that even in the context of very high production and distribution costs, the CDC can negotiate COVID-19 vaccine prices with manufacturers to keep public sector prices as low as possible while meeting CDC goals. We have predicted optimal COVID-19 vaccine prices that were consistent with those that were anticipated by the media at the time of writing.

This work is joint with Susan Martonosi and Banafsheh Behzad.

Bio:
Kayla Cummings is a PhD candidate in Operations Research at the Massachusetts Institute of Technology, advised by Alexandre Jacquillat and Vikrant Vaze. In her graduate work, she develops decomposition methods for large-scale optimization models toward integrated and optimal design of urban transportation systems. She has conducted research in cybersecurity, computational mathematics, operations research, graph theory, and algorithmic algebraic geometry at Oak Ridge National Laboratory, DIMACS at Rutgers University, Harvey Mudd College, Pomona College, and Texas A&M University. Kayla is a recipient of the MIT Teaching + Learning Lab's Teaching Development Fellowship, the NSF Graduate Research Fellowship, and the 2018 INFORMS Undergraduate Research Prize. She graduated magna cum laude with a B.A. in Mathematics from Pomona College. In her spare time, Kayla loves indoor rock climbing, distance running, classical piano, reading, petting every dog she encounters, and consuming expensive coffee.