A Data-Driven Approach to Allocating Personal Protective Equipment During the COVID-19 Pandemic in King County, Washington.

The COVID-19 pandemic created an extraordinarily high demand for personal protective equipment (PPE). Acute need and supply chain disruptions made hospitals, emergency medical services, and other critical care agencies particularly vulnerable to PPE shortages. In March 2020, King County, Washington, developed computational tools, operating procedures, and data visualizations to fulfill its responsibilities to prioritize, allocate, and distribute scarce PPE equitably and efficiently during a public health emergency. King County distributed over 1.6 million gowns, 22 million gloves, 3.9 million surgical masks, and 1.5 million N95 respirators (among other items) during its PPE distribution mission. An algorithm processed resource requests from the community, with respect to available inventory, emergency allocation policies, prioritization constraints, estimated PPE use rates, agency-specific needs, and other parameters. With these inputs and constraints, the requests were translated into instructions for fulfillment and delivery and several tabular and graphical data visualizations were produced for quality assurance and transparency. Access to timely, relevant, and stable data was a constant challenge, and constraints invariably changed as the emergency response unfolded. King County's PPE distribution mission provides a useful case study in how to develop a scalable and data-driven approach to resource allocation and distribution under emergency response conditions.