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

Sanjay Mehrotra; Hamed Rahimian; Masoud Barah; Fengqiao Luo; Karolina Schantz

We have presented a model for procuring and sharing life-saving resources whose demand is stochastic. The demand arising from different entities (states) peaks at different times, and it is important to meet as much of this demand as possible to save lives. Each participating state is risk averse to sharing their excess inventory at any given time, and this risk-aversion is captured by using a safety threshold parameter. Specifically, the developed model is applicable to the current COVID-19 pandemic, where many US states are in dire need of mechanical ventilators to provide life-support to severely-and critically-ill patients. Computations were performed using realistic ventilator need forecasts and availability under a wide combination of parameter settings.