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Improving Selection Process For Seasonal Flu Vaccines

The H1N1 influenza virus (Swine Flu) appeared after the 2009-10 flu vaccine was approved. Now the vaccine for this specific strain of the flu must be rush-manufactured and delivered to consumers separately from the seasonal flu vaccine. Soo-Haeng Cho, Assistant Professor of Operations Management, has a solution to this dilemma.

“At least once a year the Vaccine and Related Biologic Products Advisory Committee meets to decide the composition of seasonal influenza vaccine for the United States,” says Cho. “Because the virus strains constantly mutate, and because manufacture of the vaccine, needed in October of that year, takes a long time, the Committee must make their decision early in the year before they have optimal data on the strains to be feared. If the Committee decides to retain the current vaccine composition instead of updating it to a new one—as they did in 2009—there is lower uncertainty in production yields, but the current vaccine could be less effective if a new virus strain spread later in the spring, as it has in the case of H1N1.”

Cho derived a model to improve this decision making, showing that the optimal timing of selecting a new strain is a few weeks later than that of retaining the current vaccine strain. “The model suggests that the Committee should delay its decision by three to four weeks to collect more information,” says Cho. “This delay allows for better decision regarding the virus strains that are likely to threaten consumer health.”

Cho’s dynamic model analyzes the effect of cross-efficacy of vaccines, capacity expansion of incumbent manufacturers, entry of new manufacturers, and the severity and progress of virus activities. He also examines consumer behavior, as consumers place increasing value on obtaining a vaccination rather than suffering the risk of expensive illness or even death. “By incorporating these key components, the model allows the Committee to perform a what-if analysis under various scenarios. The value of this approach is potentially huge,” Cho adds. “This is an example of Tepper applying mathematical principles to a practical and important business—and social—problem.”

Soo-Haeng Cho’s award-winning paper, “The Optimal Composition of Influenza Vaccines Subject to Random Production Yields,” will be published shortly in Manufacturing & Service Operations Management, a leading journal in the field. “This is an example of a dynamic decision-making situation prevalent in other industries,” says Cho. “An optimized delay in making the choice can lead to a better social outcome.”

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