Work

Spatial Optimization to Improve COVID-19 Vaccine Allocation

Year: 2022

Type: article

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.

Source: Vaccines

DOI: 10.3390/vaccines11010064

Authors: Stephen Scroggins, Justin Goodson, Tasnova Afroze, Enbal Shacham

Institutions: Taylor Geospatial Institute, Saint Louis University

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,303