Decision Intelligence for Nationwide Ventilator Allocation

Many states in the U.S. have faced shortages of medical resources because of the surge in the number of patients suffering from COVID-19. As many projections indicate, the situation will be far worse in coming months. The upcoming challenge is not only due to the exponential growth in cases but also because of inherent uncertainty and lags associated with disease progression. In this paper, we present a collection of models for decision intelligence which provide decision-support for ventilator allocation based on predictions from well-accepted oracles of disease progression. It is clear from our study that without coordination among states, there is a very high risk of ventilator shortages in certain states. However, such shortages can be reduced, provided neighboring states agree to share ventilators as suggested by our models. We show that despite the explosive growth in cases and associated uncertainty in ventilator demand, our simulation results hold the promise of reducing unmet demand, even in the face of significant uncertainty. This paper also provides the first evidence that coordination between neighboring states can lead to a significant reduction in ventilator shortages across the U.S.


University of Southern California, Submitted in Feb. 2021



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