Finding optimal vaccination strategies under parameter uncertainty using stochastic programming.

Math Biosci

Department of Industrial and Systems Engineering, Texas A&M University, 241 Zachry, 3131 TAMU, College Station, TX 77843-3131, USA.

Published: October 2008

We present a stochastic programming framework for finding the optimal vaccination policy for controlling infectious disease epidemics under parameter uncertainty. Stochastic programming is a popular framework for including the effects of parameter uncertainty in a mathematical optimization model. The problem is initially formulated to find the minimum cost vaccination policy under a chance-constraint. The chance-constraint requires that the probability that R(*)

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http://dx.doi.org/10.1016/j.mbs.2008.07.006DOI Listing

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