IE-BIO-OPIM Joint Grad Seminar
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  • IE-BIO-OPIM Joint Grad Seminar

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IE-BIO-OPIM Joint Seminar
Prof. Andrew Schaefer
University of Pittsburgh
Nov 28, 2012, Wednesday
@ 13:40pm @ FENS G029

“Optimizing the Societal Benefits of the
Annual Influenza Vaccine: A Stochastic
Programming Approach”
Influenza (flu) is a highly contagious, acute, respiratory viral disease. Seasonal epidemics
annually impact 5-15% of the world's population, resulting in 3-5 million cases of severe illness
and up to 500,000 deaths. Seasonal flu epidemics caused by antigenic drifts and the high rate of
influenza transmission require annual updates in the flu shot composition. The World Health
Organization recommends which strains of influenza to include in each year’s vaccine based on
surveillance data and epidemiological analysis.
There are two critical decisions regarding the flu shot. The first is its composition; currently
three strains comprise the flu shot, and this decision affects its effectiveness against the
upcoming flu epidemic. The second decision is the timing of the composition decision. If the
strains are selected too early, there is a greater likelihood that there will be a mismatch.
However, delaying the decision may leave a short time for manufacturing, resulting in delays or
shortages in the flu shot supply.
Optimization models have not yet made a large impact on public health. Thus far, the design
and timing of the flu shot have been made in an ad hoc manner. We propose a multi-stage
stochastic mixed-integer program to address the optimal design of the annual flu shot design
and calibrate our model with real-life data. Risk evaluation is taken into account by
incorporating risk measures in the objective function. Multi-stage stochastic mixed-integer
programs are very difficult optimization problems, but have many potential applications. The
techniques we have developed are likely to lead to algorithmic enhancements that can be
broadly applied.
This is joint work with Osman Ozaltin of the University of Waterloo, and Oleg Prokopyev and
Mark Roberts of the University of Pittsburgh.
Andrew Schaefer
Andrew Schaefer is W. K. Whiteford Professor of Industrial
Engineering at the University of Pittsburgh. He received his PhD in
Industrial and Systems Engineering from Georgia Tech in 2000. His
research interests include the application of stochastic optimization
methods to health care problems, as well as stochastic optimization
methodology, in particular stochastic integer programming. He is an
Associate Editor for INFORMS Journal on Computing and IIE
Transactions.