ArticleOmega2022
Bi-objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID-19 pandemic.
Article in Omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Balancing fairness and efficiency in dynamic vaccine allocation during major infectious disease outbreaks.Scientific reports · 2025Article
- An integrated blockchain-enabled multi-channel vaccine supply chain network under hybrid uncertainties.Scientific reports · 2024Article
- Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities.Naval research logistics · 2024Article
- Fair-split distribution of multi-dose vaccines with prioritized age groups and dynamic demand: The case study of COVID-19.European journal of operational research · 2023Article
- Optimizing the COVID-19 cold chain vaccine distribution network with medical waste management: A robust optimization approach.Expert systems with applications · 2023Article
- Article
- 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
- Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy.Omega · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper develops an approach to optimize a vaccine distribution network design through a mixed-integer nonlinear programming model with two objectives: minimizing the total expected number of deaths among the population and minimizing the total distribution cost of the vaccination campaign. Additionally, we assume that a set of input parameters (e.g., death rate, social contacts, vaccine supply, etc.) is uncertain, and the distribution network is exposed to disruptions. We then investigate the resilience of the distribution network through a scenario-based robust-stochastic optimization approach. The proposed model is linearized and finally validated through a real case study of the COVID-19 vaccination campaign in France. We show that the current vaccination strategies are not optimal, and vaccination prioritization among the population and the equity of vaccine distribution depend on other factors than those conceived by health policymakers. Furthermore, we demonstrate that a vaccination strategy mixing the population prioritization and the quarantine restrictions leads to an 8.5% decrease in the total number of deaths.
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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.