Optimizing Vaccine Allocation Strategies in Pandemic Outbreaks: An Optimal Control Approach
Sander Tonkens, Paul de Klaver, and Mauro Salazar

TL;DR
This paper develops an optimization framework using an age-dependent SEIR model to determine optimal COVID-19 vaccine allocation strategies that balance societal objectives like minimizing infections or fatalities.
Contribution
It introduces a novel dynamic vaccine allocation model incorporating age-specific immunity and infectiousness, solved via nonlinear programming for real-world application.
Findings
Minimizing infections favors delaying second doses.
Prioritizing elderly reduces fatalities.
Different objectives lead to distinct vaccination strategies.
Abstract
Since early 2020, the world has been dealing with a raging pandemic outbreak: COVID-19. A year later, vaccines have become accessible, but in limited quantities, so that governments needed to devise a strategy to decide which part of the population to prioritize when assigning the available doses, and how to manage the interval between doses for multi-dose vaccines. In this paper, we present an optimization framework to address the dynamic double-dose vaccine allocation problem whereby the available vaccine doses must be administered to different age-groups to minimize specific societal objectives. In particular, we first identify an age-dependent Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model including an extension capturing partially and fully vaccinated people, whereby we account for age-dependent immunity and infectiousness levels together with disease severity.…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Influenza Virus Research Studies · SARS-CoV-2 and COVID-19 Research
