ArticleNaval research logistics2020
A model of supply-chain decisions for resource sharing with an application to ventilator allocation to combat COVID-19.
Article in Naval research logistics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.
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Who cites it
48 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Optimal resource allocation model for COVID-19: a systematic review and meta-analysis.BMC infectious diseases · 2024Pooled it
- Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Fair-efficient allocation mechanism with meta-types resources in cloud computing.Scientific reports · 2025Article
- An Optimization-Based Framework to Dynamically Schedule Hospital Beds in a Pandemic.Healthcare (Basel, Switzerland) · 2025Article
- Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review and Future Research Opportunities.Naval research logistics · 2024Article
- An AI-based multiphase framework for improving the mechanical ventilation availability in emergency departments during respiratory disease seasons: a case study.International journal of emergency medicine · 2024Article
- Mitigating the COVID-19 Pandemic through Data-Driven Resource Sharing.Naval research logistics · 2024Article
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- Article
- Variability scaling and capacity planning in Covid-19 pandemic.Fundamental research · 2023Article
- A data-driven optimization model to response to COVID-19 pandemic: a case study.Annals of operations research · 2023Article
- Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak.Socio-economic planning sciences · 2023Article
- Emergency order allocation of e-medical supplies due to the disruptive events of the healthcare crisis.Journal of business research · 2023Article
- Mathematical optimization models for reallocating and sharing health equipment in pandemic situations.Top (Berlin, Germany) · 2023Article
- Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: A case study.European journal of operational research · 2023Article
- Design of control strategies to help prevent the spread of COVID-19 pandemic.European journal of operational research · 2023Article
- COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk.European journal of operational research · 2023Article
- Resource planning strategies for healthcare systems during a pandemic.European journal of operational research · 2023Article
- Impact of the COVID-19 epidemic on medical product imports from china from outbreak to stabilization: Monthly panel data regression and instrumental variable test.Frontiers in public health · 2023Article
- Conversion strategy builds supply chain resilience during the COVID-19 pandemic: A typology and research directions.Progress in disaster science · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk-averse condition. The model is applied to study the allocation of ventilator inventory in the COVID-19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non-COVID-19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non-COVID-19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top-most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst-case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk-aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp-up consideration can be based on a cost-benefit analysis.
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