Model-informed COVID-19 vaccine prioritization strategies by age and serostatus

Abstract

AbstractWhen a vaccine for COVID-19 becomes available, limited initial supply will raise the question of how to prioritize the available doses and thus underscores the need for transparent, evidence-based strategies that relate knowledge of, and uncertainty in, disease transmission, risk, vaccine efficacy, and existing population immunity. Here, we employ a model-informed approach to vaccine prioritization that evaluates the impact of prioritization strategies on cumulative incidence and mortality and accounts for population factors such as age, contact structure, and seroprevalence, and vaccine factors including imperfect and age-varying efficacy. This framework can be used to evaluate and compare existing strategies, and it can also be used to derive an optimal prioritization strategy to minimize mortality or incidence. We find that a transmission-blocking vaccine should be prioritized to adults ages 20-49y to minimize cumulative incidence and to adults over 60y to minimize mortality. Direct vaccination of adults over 60y minimizes mortality for vaccines that do not block transmission. We also estimate the potential benefit of using individual-level serological tests to redirect doses to only seronegative individuals, improving the marginal impact of each dose. We argue that this serology-informed vaccination approach may improve the efficiency of vaccination efforts while partially addressing existing inequities in COVID-19 burden and impact.