Comparison of COVID-19 vaccine prioritization strategies in the United States

Chapman, L. A. C.; Shukla, P.; Rodriguez-Barraquer, I.; Shete, P. B.; Leon, T. M.; Bibbins-Domingo, K.; Rutherford, G. W.; Schechter, R.; Lo, N. C.

A critical question in the COVID-19 pandemic is how to optimally allocate the first available vaccinations to maximize health impact. We used a static simulation model with detailed demographic and risk factor stratification to compare the impact of different vaccine prioritization strategies in the United States on key health outcomes, using California as a case example. We calibrated the model to demographic and location data on 28,175 COVID-19 deaths in California up to December 30, 2020, and incorporated variation in risk by occupation and comorbidity status using published estimates. We predicted the proportion of COVID-19 clinical cases, deaths and disability-adjusted life years (DALYs) averted over 6 months relative to a scenario of no vaccination for five vaccination strategies that prioritized vaccination by a single risk factor: random allocation; targeting special populations (e.g. incarcerated individuals); targeting older individuals; targeting essential workers; and targeting individuals with comorbidities. Targeting older individuals averted the highest proportion of DALYs (40% for 5 million individuals vaccinated) and deaths (65%) but the lowest proportion of cases (12%). Targeting essential workers averted the lowest proportion of DALYs (25%) and deaths (33%). Allocating vaccinations simultaneously by age and location or by age, sex, race/ethnicity, location, occupation, and comorbidity status averted a significantly higher proportion of DALYs (48% and 56%) than any strategy prioritizing by a single risk factor. Our results corroborate findings of other studies that age targeting is the best single-risk-factor prioritization strategy for averting DALYs, and suggest that targeting by multiple risk factors would provide additional benefit.