Spatiotemporal Analysis of Medical Resource Deficiencies in the U.S. under COVID-19 Pandemic

ABSTRACT

A data-driven approach is developed to estimate medical resource deficiencies or medical burden at county level during the COVID-19 pandemic from February 15, 2020 to May 1, 2020 in the U.S. Multiple data sources were used to extract local population, hospital beds, critical care staff, COVID-19 confirmed case numbers, and hospitalization data at county level. We estimate the average length of stay from hospitalization data at state level, and calculate the hospitalized rate at both state and county level. Then we develop two medical resource deficiency indices that measure the local medical burden based on the number of accumulated active confirmed cases normalized by local maximum potential medical resources, and the number of hospitalized patients that can be supported per ICU beds per critical care staff, respectively. The medical resources data, and the two medical resource deficiency indices are illustrated in a dynamic spatiotemporal visualization platform based on ArcGIS Pro Dashboards. Our results provide new insights into the U.S. pandemic preparedness and local dynamics relating to medical burdens in response to the COVID-19 pandemic.