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Accès ouvert déclaré 2023 article

Efficient and effective large-scale vaccine distribution

11Citations signalées — pas une note de qualité
4Institutions déclarées
2Pays d’affiliation déclarés

Résumé fourni par la source

The goal of pandemic response is to provide the greatest protection, for the most people, in the least amount of time. Short response times minimize both current and future health impacts for evolving pathogens that pose global threats. To achieve this goal, efficient and effective systems are needed for distributing and administering vaccines, a cornerstone of pandemic response. COVID-19 vaccines were developed in record time in the U.S. and abroad, but U.S. data shows that they were not distributed efficiently and effectively once available. In an effort to “put vaccines on every corner”, pharmacies and other small venues were a primary means for vaccinating individuals, but daily throughput rates at these locations were very low. This contributed to extended times from manufacture to administration. An important contributing factor to slow administration rates for COVID-19 was vaccine transport and storage box size. In this paper, we establish a general system objective and provide a computationally tractable approach for allocating vaccines in a rolling horizon manner optimally. We illustrate the consequences of both box size and the number and capacity of dispensing locations on achieving system objectives. Using U.S. CDC data, we demonstrate that if vaccines are allocated and distributed according to our proposed strategy, more people would have been vaccinated sooner in the U.S. Many additional days of protection would have occurred, meaning there would have been fewer infections, less demand for healthcare resources, lower overall mortality, and fewer opportunities for the evolution of vaccine-evading strains of the disease.

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Contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Efficient and effective large-scale vaccine distribution
Date Crossref
01/08/2023
Éditeur
Elsevier BV
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

Institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Sujets associés

COVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 ResearchVaccine Coverage and Hesitancy

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