Optimal allocation of face masks during the COVID-19 pandemic: a case study of the first epidemic wave in the United States

TL;DR

This study uses a two-group SIR model and optimal control to determine the best distribution of face masks during COVID-19's first wave in the US, revealing that mask sharing with the public can significantly reduce deaths when supplies are adequate.

Contribution

It introduces an optimal control framework for face mask allocation during a pandemic, highlighting the importance of supply levels in policy recommendations.

Findings

Sharing masks with the public reduces deaths when supplies are sufficient.

Prioritizing healthcare workers is optimal when supplies are limited.

Guidelines should adapt to changing mask supply levels.

Abstract

In this paper, we propose a two-group SIR epidemic model to simulate the outcome of stay-at-home policy and wearing face masks during the first COVID-19 epidemic wave in the United States. Based on our proposed model, we further use the optimal control approach (with the objective of minimizing total deaths) to find the optimal dynamical distribution of face masks between the healthcare workers and the general public. It is not surprising that all the face masks should be solely reserved for the healthcare workers if the supply is short. However, when the supply is indeed sufficient, our numerical study indicates that the general public should share a large portion of face masks at the beginning of an epidemic wave to dramatically reduce the death toll. This interesting result partially contradicts with the guideline advised by the US Surgeon General and the Centers for Disease Control and Prevention (CDC) in March 2020. The optimality of this sounding CDC guideline highly depends on the supply level of face masks that changes frequently, and hence it should be adjusted according to the supply of face masks.