Retrospective analysis of equity-based optimization for COVID-19 vaccine allocation

Abstract

Marginalized racial and ethnic groups in the United States were disproportionally affected by the COVID-19 pandemic. To study these disparities, we construct an age-and-race-stratified mathematical model of SARS-CoV-2 transmission fitted to age-and-race-stratified data from 2020 in Oregon and analyze counterfactual vaccination strategies in early 2021. We consider two racial groups: non-Hispanic White persons and persons belonging to BIPOC groups (including non-Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American-Indian or Alaska-Native persons, and Hispanic or Latino persons). We allocate a limited amount of vaccine to minimize overall disease burden (deaths or years of life lost), inequity in disease outcomes between racial groups (measured with five different metrics), or both. We find that, when allocating small amounts of vaccine (10% coverage), there is a trade-off between minimizing disease burden and minimizing inequity. Older age groups, who are at a greater risk of severe disease and death, are prioritized when minimizing measures of disease burden, and younger BIPOC groups, who face the most inequities, are prioritized when minimizing measures of inequity. The allocation strategies that minimize combinations of measures can produce middle-ground solutions that similarly improve both disease burden and inequity, but the trade-off can only be mitigated by increasing the vaccine supply. With enough resources to vaccinate 20% of the population the trade-off lessens, and with 30% coverage, we can optimize both equity and mortality. Our goal is to provide a race-conscious framework to quantify and minimize inequity that can be used for future pandemics and other public health interventions.

Covid19Vaxplorer: A free, online, user-friendly COVID-19 vaccine allocation comparison tool

“…There is a vast body of work that was developed to compare COVID-19 vaccination strategies. Most of the previous research has been devoted to analyze within-country or within-region vaccine allocation [ 17 – 19 , 21 , 23 , 24 , 26 , 31 , 33 , 74 – 84 ], some has explored the optimal use of COVID-19 vaccines globally to reduce between- [ 20 , 22 , 85 , 86 ], or within-country inequities [ 84 , 87 , 88 ]. Covid19Vaxplorer adds to previous work with the hope of providing those countries or regions with limited modeling capabilities with a tool for vaccine allocation comparison.…”

Evaluating equity-promoting interventions to prevent race-based inequities in influenza outcomes

“…Researchers and decision makers are increasingly recognizing the need to incorporate equity or fairness considerations into analyses aiming to evaluate public health interventions [55][56][57][58][59], including analysis using mathematical models of infectious diseases. Previous work has focused on reducing racial and ethnic inequities in COVID-19 outcomes [60][61][62] assessing the impact of COVID-19 mitigation strategies on different racial and ethnic groups [63,64], optimizing equitable vaccine distribution for COVID-19 and influenza [60,65,66] studying inequity between subgroups for influenza and other diseases [67,68], and promoting equity in resource allocation between geographic regions for Ebola [69]. We hope that the present work will be a helpful addition to the existing literature and will promote further discussion and use of quantitative methods to evaluate equity-promoting interventions in public health.…”

Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models

“…In Stafford et al (2023), an age-and-race-stratified ODE-based model was used to study the distribution of available vaccines in the United States to two different groups: non-Hispanic White persons and all others. Several objective functions that include mortality, YLLs, measures of inequity and joint disease burden were considered.…”