A Spatiotemporal Tool to Project Hospital Critical Care Capacity and Mortality From COVID-19 in US Counties

Abstract

Objectives. To create a tool to rapidly determine where pandemic demand for critical care overwhelms county-level surge capacity and to compare public health and medical responses.Methods. In March 2020, COVID-19 cases requiring critical care were estimated using an adaptive metapopulation SEIR (susceptible‒exposed‒infectious‒recovered) model for all 3142 US counties for future 21-day and 42-day periods from April 2, 2020, to May 13, 2020, in 4 reactive patterns of contact reduction-0%, 20%, 30%, and 40%-and 4 surge response scenarios-very low, low, medium, and high.Results. In areas with increased demand, surge response measures could avert 104 120 additional deaths-55% through high clearance of critical care beds and 45% through measures such as greater ventilator access. The percentages of lives saved from high levels of contact reduction were 1.9 to 4.2 times greater than high levels of hospital surge response. Differences in projected versus actual COVID-19 demands were reasonably small over time.Conclusions. Nonpharmaceutical public health interventions had greater impact in minimizing preventable deaths during the pandemic than did hospital critical care surge response. Ready-to-go spatiotemporal supply and demand data visualization and analytics tools should be advanced for future preparedness and all-hazards disaster response.

FIGURE 1—

US Counties Exceeding Hospital Critical Care Surge Limits Within a 21-Day Time Period Under Different Surge Response and Contact Reduction Scenarios, Shown in Black: April 2, 2020–April 23, 2020

FIGURE 2—

US Counties Exceeding Hospital Critical Care Surge Limits Within a 42-Day Time Period Under Different Surge Response and Contact Reduction Scenarios, Shown in Black: April 2, 2020–May 13, 2020

FIGURE 3—

Percentage Errors of Projected Versus Actual Differentials in COVID-19 Cases Requiring Critical Care: United States, April 5, 2020–June 10, 2020