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

• 成果类型: Article
• 署名作者: Oezaltin, Osman Y.; Prokopyev, Oleg A.; Schaefer, Andrew J.; Roberts, Mark S.
• 署名单位: University of Waterloo; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.1110.0988
• 发表日期: 2011
• 页码: 1131-1143
• 关键词: Optimization

摘要

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.