Evaluation of the United States COVID-19 Vaccine Allocation Strategy

Abstract Background Anticipating an initial shortage of vaccines for COVID-19, the Centers for Disease Control (CDC) in the United States developed priority vaccine allocations for specific demographic groups in the population. This study evaluates the performance of the CDC vaccine allocation strategy with respect to multiple potentially competing vaccination goals (minimizing mortality, cases, infections, and years of life lost (YLL)), under the same framework as the CDC allocation: four priority vaccination groups and population demographics stratified by age, comorbidities, occupation and living condition (congested or non-congested). Methods We developed a compartmental disease model that incorporates key elements of the current pandemic including age-varying susceptibility to infection, age-varying clinical fraction, an active case-count dependent social distancing level, and time-varying infectivity (accounting for the emergence of more infectious virus strains). Under this model, the CDC allocation strategy is compared to all other possibly optimal allocations that stagger vaccine roll-out in up to four phases (17.5 million strategies). Results The CDC allocation strategy performed well in all vaccination goals but never optimally. Under the developed model, the CDC allocation deviated from the optimal allocations by small amounts, with 0.19% more deaths, 4.0% more cases, 4.07% more infections, and 0.97% higher YLL, than the respective optimal strategies. The CDC decision to not prioritize the vaccination of individuals under the age of 16 was optimal, as was the prioritization of health-care workers and other essential workers over non-essential workers. Finally, a higher prioritization of individuals with comorbidities in all age groups improved outcomes compared to the CDC allocation. Interpretation The developed approach can be used to inform the design of future vaccine allocation strategies in the United States, or adapted for use by other countries seeking to optimize the effectiveness of their vaccine allocation strategies. Funding The authors received no funding for this work. Research in context Evidence before this study The Centers for Disease Control and Prevention (CDC) prioritized population groups for vaccination based on available scientific evidence, the feasibility of different implementation strategies, and ethical considerations. We searched PubMed using the query “(((COVID) AND (vaccin*)) AND (model)) AND ((priorit*) OR alloc*)” up to June 15, 2021, with no date or language restrictions. The search identified 190 articles, of which 15 used predictive models to evaluate the efficacy of vaccine allocation strategies in achieving vaccination campaign goals such as reducing mortality or incidence. All studies compared only a small number of specific, expertise-based allocations. Most studies stratified the population by age, while some considered additional characteristics such as occupation or comorbidity status, but none took into account all characteristics included in the CDC vaccine prioritizations. Added value of this study We developed a compartmental disease model that takes into account several important components of the COVID-19 pandemic, and stratifies the U.S. population by all characteristics included in the CDC vaccine prioritization recommendations. In a novel global optimization approach, we compared the CDC recommendations to all potentially optimal strategies (17.5 million strategies) that also stagger the vaccine roll-out in four phases. The CDC allocation strategy performed well in all considered outcome measures, but never optimally; a higher prioritization of individuals with comorbidities in all age groups improved outcomes. The CDC decision to initially not vaccinate children, as well as the prioritization of health-care workers and other essential workers over non-essential workers proved optimal under all outcome measures. Implications of all the available evidence Our study identifies and compares the optimal vaccine allocation strategies for several competing vaccination goals. The developed global optimization approach can be used to inform the design of future vaccine allocation strategies in the United States and elsewhere.

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