Finding optimal vaccination strategies under parameter uncertainty using stochastic programming. Academic Article

abstract

• 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(*)

authors

• Ntaimo, Lewis

published proceedings

• Math Biosci

altmetric score

• 6

author list (cited authors)

• Tanner, M. W., Sattenspiel, L., & Ntaimo, L.

citation count

• 54
• 67

complete list of authors

• Tanner, Matthew W||Sattenspiel, Lisa||Ntaimo, Lewis

publication date

• October 2008
• January 2008

publisher

• Elsevier  Publisher

published in

• Mathematical Biosciences  Journal

keywords

• Algorithms
• Basic Reproduction Number
• Communicable Disease Control
• Communicable Diseases
• Cost-benefit Analysis
• Disease Outbreaks
• Humans
• Models, Biological
• Stochastic Processes
• Vaccination
• Vaccines

PubMed Central ID

• 18700149

Digital Object Identifier (DOI)

• 10.1016/j.mbs.2008.07.006

start page

• 144

end page

• 151

volume

• 215

issue

• 2

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.mbs.2008.07.006
• http://dx.doi.org/10.1016/j.mbs.2008.07.006

user-defined tag

• 3 Good Health and Well-Being