Spatial Optimization to Improve COVID-19 Vaccine Allocation.

delivery of health care ecological and environmental COVID-19 vaccines

Journal

Vaccines
ISSN: 2076-393X
Titre abrégé: Vaccines (Basel)
Pays: Switzerland
ID NLM: 101629355

Informations de publication

Date de publication:
28 Dec 2022
Historique:
received: 11 11 2022
revised: 16 12 2022
accepted: 21 12 2022
entrez: 21 1 2023
pubmed: 22 1 2023
medline: 22 1 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 36679909
pii: vaccines11010064
doi: 10.3390/vaccines11010064
pmc: PMC9866695
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Stephen Scroggins (S)

Taylor Geospatial Institute, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO 63103, USA.

Justin Goodson (J)

Department of Operations and IT Management, Chaifetz School of Business, Saint Louis University, St. Louis, MO 63103, USA.

Tasnova Afroze (T)

Department of Operations and IT Management, Chaifetz School of Business, Saint Louis University, St. Louis, MO 63103, USA.

Enbal Shacham (E)

Taylor Geospatial Institute, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO 63103, USA.

Classifications MeSH