Efficient Mask Allocation during a Pandemic

We analyse the allocation of face masks with the goal of minimizing mortality during a pandemic through airborne transmission. When the initial distribution of masks is private information, the optimal allocation achieved by a sophisticated mechanism in most cases maximizes the coverage rate by incentivizing individuals who initially own a mask to reveal this information in exchange for a better chance to receive masks in the future. We propose a novel and simple mechanism, which reduces death by a sizable number compared with simple random assignment. Our simulation shows that, for small to medium early coverage rates, the new mechanism approximately attains the minimum mortality