ArticleTransportation research. Part E, Logistics and transportation review2022
Multi-period vaccine allocation model in a pandemic: A case study of COVID-19 in Australia.
Article in Transportation research. Part E, Logistics and transportation review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 56 citations in OpenAlex.
- Optimizing patient flow logistics: strategic challenges, tactical solutions, and future directions.BMC health services research · 2025Pooled it
- Pharmacy-based immunization: a systematic review.Frontiers in public health · 2023Pooled it
- Evaluating the impact of COVID-19 vaccination strategies on infections and hospitalisations in Victoria with non-seasonal epidemic wave patterns: a modelling study.The Medical journal of Australia · 2025Article
- Balancing fairness and efficiency in dynamic vaccine allocation during major infectious disease outbreaks.Scientific reports · 2025Article
- Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities.Naval research logistics · 2024Article
- An integrated blockchain-enabled multi-channel vaccine supply chain network under hybrid uncertainties.Scientific reports · 2024Article
- Cost-effectiveness analysis of COVID-19 intervention policies using a mathematical model: an optimal control approach.Scientific reports · 2024Article
- Equitable and effective vaccine access considering vaccine hesitancy and capacity constraints.Omega · 2023Article
- A robust optimization problem for drone-based equitable pandemic vaccine distribution with uncertain supply.Omega · 2023Article
- A reliable emergency logistics network for COVID-19 considering the uncertain time-varying demands.Transportation research. Part E, Logistics and transportation review · 2023Article
- Optimizing two-dose vaccine resource allocation to combat a pandemic in the context of limited supply: The case of COVID-19.Frontiers in public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While the swift development and production of a COVID-19 vaccine has been a remarkable success, it is equally crucial to ensure that the vaccine is allocated and distributed in a timely and efficient manner. Prior research on pandemic supply chain has not fully incorporated the underlying factors and constraints in designing a vaccine allocation model. This study proposes an innovative vaccine allocation model to contain the spread of infectious diseases incorporating key contributing factors to the risk of uninoculated people including susceptibility rate and exposure risk. Analyses of the data collected from the state of Victoria in Australia show that a vaccine allocation model can deliver a superior performance in minimizing the risk of unvaccinated people when a multi-period approach is employed and augmenting operational mechanisms including transshipment between medical centers, capacity sharing, and mobile units being integrated into the vaccine allocation model.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.