Use of the Improvement Index to Evaluate Equitable COVID-19 Vaccine Allocation in the San Francisco Bay Area

INTRODUCTION: A social determinants of health index score or Vaccine Equity Metric was used to prioritize resources and address geographic disparities in California's vaccination coverage. We calculated the improvement index or percentage of the vaccination disparity gap closed to evaluate the impacts of this vaccination strategy in the San Francisco Bay Area during the SARS-CoV-2 Delta variant surge. METHODS: We conducted a cross-sectional study on San Francisco Bay Area ZIP codes during the Delta surge (July 6–October 5, 2021). Data came from the California Immunization Registry and the 2019 5-year American Community Survey. We used Spearman correlations to examine the relationships between Vaccine Equity Metric category and vaccine coverage and Kruskal–Wallis tests to compare vaccination improvement index across Vaccine Equity Metric categories. RESULTS: We studied 248 ZIP codes in the San Francisco Bay Area. Those with the lowest resources (Vaccine Equity Metric Level 1) had the highest absolute increase in vaccination coverage (14.3 vs 5.4 percentage points in Vaccine Equity Metric Level 4), although a contribution was higher starting vaccination rates in Level 4 ZIP codes with the greatest resources. The ratio of vaccination coverage between the lowest- and highest-resourced ZIP codes increased from 0.79 to 0.9, suggesting reduced disparity. However, it is difficult to interpret given wide differences in n (Level 1 n=8 vs Level 4 n=151). In contrast, the vaccination improvement index accounts for each Vaccine Equity Metric category's baseline vaccination; all were statistically similar (grand mean=41.5%, p=0.367), implying comparable improvement across all ZIP codes. CONCLUSIONS: Using a Vaccine Equity Metric to identify and prioritize resources to vulnerable communities contributed to equitable vaccine allocation in the San Francisco Bay Area. Our study shows an example of the improvement index's advantages over conventional health equity metrics, such as absolute differences and relative effect measures, which can overestimate an intervention's impact.