Mathematical Optimization in Vaccine Allocation Defended on Friday, 15 September 2017
Vaccination is one of the most effective ways to prevent an outbreak of an infectious disease. It results in immunity for the vaccinated individuals, but also reduces the infection pressure for unvaccinated people. In the past years, the Operations Research/Operations Management community has shown a growing interest in the logistical aspects of vaccination.
In this dissertation, we structure the literature on vaccine logics. Using a supply chain perspective, we describe the decision problems and identify future research directions. In the remainder of the dissertation, we analyze three decision problems in the field of vaccine allocation: the allocation of a limited vaccine stockpile to fight a sudden outbreak, the allocation of prepandemic vaccines in an age-structured population and the allocation of a limited budget over multiple vaccine types. We use mathematical optimization to find solutions to these complex allocation problems.
We contribute by providing insights into the structure of the solutions that could not be obtained numerically. Our results show that optimality and equity are often far apart. Policy makers therefore need strategies in which they balance between efficiency and equity. The simple models and analytical insights in this dissertation provide a valuable starting point for analyzing such strategies.
Logistics, Optimization, Mathematical modelling, Infectious diseases, Vaccination, Disease modelling, Resource allocation, Supply chain management