Characterizing the Spatiotemporal Heterogeneity of the COVID-19 Vaccination Landscape

Abstract

Abstract As variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged throughout 2021–2022, the need to maximize vaccination coverage across the United States to minimize severe outcomes of coronavirus disease 2019 (COVID-19) has been critical. Maximizing vaccination requires that we track vaccination patterns to measure the progress of the vaccination campaign and target locations that may be undervaccinated. To improve efforts to track and characterize COVID-19 vaccination progress in the United States, we integrated Centers for Disease Control and Prevention and state-provided vaccination data, identifying and rectifying discrepancies between these data sources. We found that COVID-19 vaccination coverage in the United States exhibits significant spatial heterogeneity at the county level, and we statistically identified spatial clusters of undervaccination, all with foci in the southern United States. We also identified vaccination progress at the county level as variable through summer 2021; the progress of vaccination in many counties stalled in June 2021, and few had recovered by July, with transmission of the SARS-CoV-2 delta variant rapidly rising. Using a comparison with a mechanistic growth model fitted to our integrated data, we classified vaccination dynamics across time at the county scale. Our findings underline the importance of curating accurate, fine-scale vaccination data and the continued need for widespread vaccination in the United States, especially with the continued emergence of highly transmissible SARS-CoV-2 variants.