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This paper presents a stochastic optimization model for allocating andsharing a critical resource in the case of a pandemic. The demand for differententities peaks at different times, and an initial inventory from a centralagency is to be allocated. The entities (states) may share the criticalresource with a different state under a risk-averse condition. The model isapplied to study the allocation of ventilator inventory in the COVID-19pandemic by the Federal Emergency Management Agency of the US Department ofHomeland Security (FEMA) to different states in the US. Findings suggest thatif less than 60% of the ventilator inventory is available for non-COVID-19patients, FEMA's stockpile of 20,000 ventilators (as of 03/23/2020) would benearly adequate to meet the projected needs. However, when more than 75% of theavailable ventilator inventory must be reserved for non-COVID-19 patients,various degrees of shortfall are expected. In an extreme case, where the demandis assumed to be concentrated in the top-most quartile of the forecastconfidence interval, the total shortfall over the planning horizon (till05/31/20) is about 28,500 ventilator days, with a peak shortfall of 2,700ventilators on 04/12/20. The results also suggest that in theworse-than-average to severe demand scenario cases, NY requires between7,600-9,200 additional ventilators for COVID-19 patients during its peakdemand. However, between 400 to 2,000 of these ventilators can be given to adifferent state after the peak demand in NY has subsided.

A Model of Supply-Chain Decisions for Resource Sharing with an Application to Ventilator Allocation to Combat COVID-19