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Identifying Areas with Low Access to the COVID-19 Vaccine: A New Objective Framework Incorporating Mobility Data
Defeng Tao1, Joseph Agor2, Jessina McGregor3
1School of Mechanical, Industrial, and Manufacturing Engineering, Oregon State University, 224 Rogers Hall, Corvallis, OR 97331, USA.
Background:
The disparities observed in COVID-19 vaccine access at the early stages of vaccine distribution highlight the need for vaccine distribution plans that consider equitable access. Strategies to identify areas with low access to vaccines that use a single pre-specified distance or time as a threshold to define accessibility may not represent reality. We propose a novel mobility data-driven (MDD) definition to identify areas that have low access to the COVID-19 vaccine.
Methods:
We collected geospatial mobility data for our MDD approach to determine areas of low access. We identified census tracts in Oregon with low access to the COVID-19 vaccine through two approaches-(1) an adapted United States Department of Agriculture (USDA) food desert definition and (2) our proposed MDD framework. Ten spatial and social measures of access were utilized to compare these two approaches.
Results:
Compered with USDA, low-access census tracts identified by the MDD definition have a lower spatial accessibility; higher rates of poverty, unemployment, uninsured individuals, and a population without high school diplomas; and a low per capita income. Moreover, we found that the proportion of older populations, as well as American Indian and Alaskan Native populations, as identified in the MDD low-access census tracts, is higher than that in the USDA definition.
Conclusions:
We believe that the new proposed framework using mobility data can identify more representative areas that have low access to COVID-19 vaccines. Our proposed framework provides a starting point for achieving the goal of the equitable distribution of resources.
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