Spatial Optimization to Improve COVID-19 Vaccine Allocation

Stephen Scroggins; Justin Goodson; Tasnova Afroze; Enbal Shacham

doi:10.3390/vaccines11010064

Spatial Optimization to Improve COVID-19 Vaccine Allocation

Vaccines (Basel). 2022 Dec 28;11(1):64. doi: 10.3390/vaccines11010064.

Authors

Stephen Scroggins¹, Justin Goodson², Tasnova Afroze², Enbal Shacham¹

Affiliations

¹ Taylor Geospatial Institute, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO 63103, USA.
² Department of Operations and IT Management, Chaifetz School of Business, Saint Louis University, St. Louis, MO 63103, USA.

Abstract

Early distribution of COVID-19 vaccines was largely driven by population size and did not account for COVID-19 prevalence nor location characteristics. In this study, we applied an optimization framework to identify distribution strategies that would have lowered COVID-19 related morbidity and mortality. During the first half of 2021 in the state of Missouri, optimized vaccine allocation would have decreased case incidence by 8% with 5926 fewer COVID-19 cases, 106 fewer deaths, and 4.5 million dollars in healthcare cost saved. As COVID-19 variants continue to be identified, and the likelihood of future pandemics remains high, application of resource optimization should be a priority for policy makers.

Keywords: delivery of health care; ecological and environmental COVID-19; vaccines.

Grants and funding

This research received no external funding.