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

A medical resource allocation problem in a disaster is considered in [29] . Victims' deteriorating health conditions are modeled as a Markov chain, and the resources are allocated to optimize the total expected health recovery rate and reduce the total waiting time. Certain illustrative examples in a queuing network setting are also given in [29] . The problem of scarce medical resource allocation after a natural disaster using a discrete event simulation approach is investigated in [14] . Specifically, the authors in [14] investigate four resource-rationing principles: first come-first served, random, most serious first, and least serious first. It is found that without ethical constraints, the least serious first principle exhibits the highest efficiency. However, a random selection provides a relatively fairer allocation of services and a better trade-off with ethical considerations. Resource allocation in an emergency department in a multi-objective and simulation-optimization framework is studied in [16] . Simulation and queuing models for bed allocation are studied in [27, 18] .