A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States

How to Cite

Arling, G., Blaser, M., Cailas, M., Canar, J. R., Cooper, B., Flax-Hatch, J., Geraci, P. J., Osiecki, K. M., & Sambanis, A. (2021). A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States. Online Journal of Public Health Informatics, 13(1). https://doi.org/10.5210/ojphi.v13i1.11621


Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic.

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