A Net Benefit Approach for the Optimal Allocation of a COVID-19 Vaccine
Abstract
OBJECTIVE
We implement a model-based approach to identify the optimal allocation of a COVID-19 vaccine in the province of Alberta, Canada.
METHODS
We develop an epidemiologic model to evaluate allocation strategies defined by age and risk target groups, coverage, effectiveness, and cost of vaccine. The model simulates hypothetical immunization scenarios within a dynamic context, capturing concurrent public health strategies and population behaviour changes.
RESULTS
In a scenario with 80% vaccine effectiveness, 40% population coverage, and prioritisation of those over the age of 60 at high-risk of poor outcomes, active cases are reduced by 17% and net monetary benefit increased by $263 million dollars, relative to no vaccine. Concurrent implementation of policies such as school closure and senior contact reductions have similar impacts on incremental net monetary benefit ($352 vs. 292 million, respectively) when there is no prioritisation given to any age or risk group. When older age groups are given priority, the relative benefit of school closures is much larger ($214 vs. 118 million). Results demonstrate that the rank ordering of different prioritisation options varies by prioritisation criteria, vaccine effectiveness and coverage, and concurrently implemented policies.
CONCLUSIONS
Our results have three implications: (i) optimal vaccine allocation will depend on the public health policies in place at the time of allocation and the impact of those policies on population behaviour; (ii) outcomes of vaccine allocation policies can be greatly supported with interventions targeting contact reduction in critical sub-populations; and (iii) identification of the optimal strategy depends on which outcomes are prioritised.
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