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Model-informed vaccine prioritization strategies

Abstract

When a vaccine for COVID-19 becomes available, it will undoubtedly be in short supply globally, nationally, and locally, raising the question of how that limited vaccine should be prioritized to subpopulations to minimize future cases or deaths. However, this will be complicated by numerous factors, including the heterogeneity of contact structure, vaccine efficacy and

safety, and seroprevalence. We propose a model-informed approach to age-stratified vaccine prioritization that incorporates these complications through two primary aims:

Aim 1: Derive a generalizable framework to compare the projected impacts of proposed vaccine prioritization strategies. When minimization of cumulative incidence or deaths is set as a goal, this framework will also allow the process to be run in reverse, by choosing a target outcome and then solving for a prioritization strategy to best approach it.

Aim 2: Identify critical vaccine parameters and population heterogeneities whose specifications are important to vaccine prioritization models more broadly. This will allow research by others into identifying these key parameters and their interactions prior to the availability of a vaccine.

The priorities of this work have been set through conversations with the WHO Strategic Advisory Group of Experts (SAGE) for vaccines and immunization. As a consequence, the above Aims will be applied not just to the U.S. but to any countries or regions for which data are available (Aim 1) or for which data could be generated (Aim 2).

This study will directly inform vaccine prioritization while also shedding light on critically needed information for effective prioritization decision-making.