Hospital-flux simulator aims to signal surges 30 days in advance
In December 2020, the U.S. Department of Health and Human Services (HHS) began sharing detailed data on Coronavirus Disease 2019 (COVID-19) hospitalizations and hospital capacity, including the average number of patients in hospital and intensive care units (ICU) beds each week. As the past year has shown, a high proportion of reported COVID-19 cases are characterized as severe, requiring hospitalization in acute treatment units or ICUs. While our understanding about why some individuals progress towards severe disease and others do not is still evolving, it is clear that risk factors for severe disease include age and underlying health conditions. Based on the U.S. Centers for Disease Control and Prevention (CDC) COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) data, that describes trends in clinical outcomes, “15.9%, or about 1 in 6 hospitalized COVID-19 patients, were admitted to the ICU.”
Since the pandemic began, the proportion of severe cases has remained consistent; a growing concern focuses on the threat of new variants – whether they are more transmissible and pathogenic, resulting in increased transmission, greater incidence of severe disease, and possibly death. While the promise of enough vaccines to reach herd immunity in the United States is heartening, the weeks and months until this stage is achieved will—especially with increasing COVID-19 pandemic fatigue—continue to challenge health systems and hospitals.
Combating COVID-19 with Computing
The COVID-19 pandemic has been an accelerator for the automation of data modeling and computing. Recently, Dr. Donal Bisanzio and Dr. Rainer Hilscher led a team of data scientists and epidemiologists to develop an innovative, high-resolution hospital-flux simulator (at the facility level) to describe COVID-19 case flow across the United States and identify those locations with a higher risk of increased hospital and ICU admissions. The simulator was added to RTI’s COVID-19 Data Insights Tool. Figure 1 overlays the average of ICU bed occupancy rates projected by the model for a series of select states, displaying these averages over the projected national average for the past month and 30-days into the future.