Modeling efficient and equitable distribution of COVID-19 vaccines Article Swipe
Monear Makvandi
,
Laurie Wallis
,
Celine West
,
Haedi De Angelis
,
Zane VanWinkle
,
Vibeke Halkjær-Knudsen
,
Erin Acquesta
,
Walter Beyeler
,
Katherine A. Klise
,
Patrick D. Finley
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.2172/1718986
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.2172/1718986
Producing and distributing COVID-19 vaccine during the pandemic is a major logistical challenge requiring careful planning and efficient execution. This report presents information on logistical, policy and technical issues relevant to rapidly fielding a COVID-19 vaccination program. For this study we (a) conducted literature review and subject matter expert elicitation to understand current vaccine manufacturing and distribution capabilities and vaccine allocation strategies, (b) designed a baseline vaccine distribution strategy and modeling strategy to provide insight into the potential for targeted distribution of limited initial vaccine supplies, and (c) developed parametric interfaces to enable vaccine distribution scenarios to be analyzed in depth with Sandias Adaptive Recovery Model that will allow us evaluate the additional sub- populations and alternative distribution scenarios from a public health benefit and associated economic disruption Principal issues, challenges, and complexities that complicate COVID-19 vaccine delivery identified in our literature and subject matter expert investigation include these items: The United States has not mounted an urgent nationwide vaccination campaign in recent history. The existing global manufacturing and distribution infrastructure are not able to produce enough vaccine for the population immediately. Vaccines, once available will be scarce resources. Prioritization for vaccine allocation will be built on existing distribution networks. Vaccine distribution may not have a universal impact on disease transmission and morbidity because of scarcity, priority population demographics, and underlying disease transmission rates. Considerations for designing a vaccine distribution strategy are discussed. A baseline distribution strategy is designed and tested using the Adaptive Recovery Model, which couples a deterministic compartmental epidemiological model and a stochastic network model. We show the impact of this vaccine distribution strategy on hospitalizations, mortality, and contact tracing requirements. This model can be used to quantitatively evaluate alternative distribution scenarios, guiding policy decisions as vaccine candidates are narrowed down.
Related Topics
Concepts
Population
Pandemic
Baseline (sea)
Vaccination
Computer science
Distribution (mathematics)
Risk analysis (engineering)
Scarcity
Operations research
Business
Medicine
Environmental health
Engineering
Disease
Coronavirus disease 2019 (COVID-19)
Economics
Infectious disease (medical specialty)
Virology
Political science
Mathematical analysis
Microeconomics
Law
Pathology
Mathematics
Metadata
- Type
- report
- Language
- en
- Landing Page
- https://doi.org/10.2172/1718986
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3109967439
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3109967439Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2172/1718986Digital Object Identifier
- Title
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Modeling efficient and equitable distribution of COVID-19 vaccinesWork title
- Type
-
reportOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-11-19Full publication date if available
- Authors
-
Monear Makvandi, Laurie Wallis, Celine West, Haedi De Angelis, Zane VanWinkle, Vibeke Halkjær-Knudsen, Erin Acquesta, Walter Beyeler, Katherine A. Klise, Patrick D. FinleyList of authors in order
- Landing page
-
https://doi.org/10.2172/1718986Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.osti.gov/biblio/1718986Direct OA link when available
- Concepts
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Population, Pandemic, Baseline (sea), Vaccination, Computer science, Distribution (mathematics), Risk analysis (engineering), Scarcity, Operations research, Business, Medicine, Environmental health, Engineering, Disease, Coronavirus disease 2019 (COVID-19), Economics, Infectious disease (medical specialty), Virology, Political science, Mathematical analysis, Microeconomics, Law, Pathology, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2021: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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