Optimizing the Societal Benefits of the Annual Influenza Vaccine: A Stochastic Programming Approach

Authors:
Osman Y. Özaltın;Oleg A. Prokopyev;Andrew J. Schaefer;Mark S. Roberts
Affiliations:
Department of Management Sciences, Faculty of Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261;Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261;Department of Health Policy and Management, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
Venue:
Operations Research
Year:
2011

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Abstract

Seasonal influenza is a major public health concern, and the first line of defense is the flu shot. Antigenic drifts and the high rate of influenza transmission require annual updates to the flu shot composition. The World Health Organization recommends which flu strains to include in the annual vaccine, based on surveillance and epidemiological analysis. There are two critical decisions regarding the flu shot design. One is its composition; currently, three strains constitute the flu shot, and they influence vaccine effectiveness. Another critical decision is the timing of the composition decisions, which affects the flu shot production. Both of these decisions have to be made under uncertainty many months before the flu season starts. We quantify the trade-offs involved through a multistage stochastic mixed-integer program that determines the optimal flu shot composition and its timing in a stochastic and dynamic environment.We incorporate risk sensitivity through mean-risk models. Our results provide valuable insights for pressing policy issues.