Cargando…

Spatial Optimization to Improve COVID-19 Vaccine Allocation

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 morta...

Descripción completa

Detalles Bibliográficos
Autores principales: Scroggins, Stephen, Goodson, Justin, Afroze, Tasnova, Shacham, Enbal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866695/
https://www.ncbi.nlm.nih.gov/pubmed/36679909
http://dx.doi.org/10.3390/vaccines11010064
_version_ 1784876155675869184
author Scroggins, Stephen
Goodson, Justin
Afroze, Tasnova
Shacham, Enbal
author_facet Scroggins, Stephen
Goodson, Justin
Afroze, Tasnova
Shacham, Enbal
author_sort Scroggins, Stephen
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9866695
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-98666952023-01-22 Spatial Optimization to Improve COVID-19 Vaccine Allocation Scroggins, Stephen Goodson, Justin Afroze, Tasnova Shacham, Enbal Vaccines (Basel) Article 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. MDPI 2022-12-28 /pmc/articles/PMC9866695/ /pubmed/36679909 http://dx.doi.org/10.3390/vaccines11010064 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Scroggins, Stephen
Goodson, Justin
Afroze, Tasnova
Shacham, Enbal
Spatial Optimization to Improve COVID-19 Vaccine Allocation
title Spatial Optimization to Improve COVID-19 Vaccine Allocation
title_full Spatial Optimization to Improve COVID-19 Vaccine Allocation
title_fullStr Spatial Optimization to Improve COVID-19 Vaccine Allocation
title_full_unstemmed Spatial Optimization to Improve COVID-19 Vaccine Allocation
title_short Spatial Optimization to Improve COVID-19 Vaccine Allocation
title_sort spatial optimization to improve covid-19 vaccine allocation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9866695/
https://www.ncbi.nlm.nih.gov/pubmed/36679909
http://dx.doi.org/10.3390/vaccines11010064
work_keys_str_mv AT scrogginsstephen spatialoptimizationtoimprovecovid19vaccineallocation
AT goodsonjustin spatialoptimizationtoimprovecovid19vaccineallocation
AT afrozetasnova spatialoptimizationtoimprovecovid19vaccineallocation
AT shachamenbal spatialoptimizationtoimprovecovid19vaccineallocation