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Above: Caleb Willard, an engineer with the U.S. Army Corps of Engineers Walla Walla District, uses augmented-reality tools developed at the U.S. Army Engineer Research and Development Center to assess a potential site for a COVID-19 alternate care facility (ACF) while working from home in April 2020. Above right: Kelly Irvin of the U.S. Army Engineer Research and Development Center uses augmented-reality technology developed in the Information Technology Laboratory to inspect a mock boiler room. The software is being used across the nation to assess potential sites for COVID-19 ACFs, while limiting the number of people who have to physically examine the facilities.
“Facility assessments are critical to the success of the ACF mission,” said Jonathan Boone, a research civil engineer on the augmented-reality project. “Having reachback, live-stream capabilities allows engineers and architects who are leading efforts from a ‘boots on the ground’ team perspective to get virtual support from other USACE subject-matter experts.” But augmented reality wasn’t the only computational solution to come from ERDC-ITL in response to COVID-19. Managed by ERDC, the Department of Defense High Performance Computing Modernization Program (HPCMP) also brought a powerful weapon to the fight against COVID-19: supercomputers. One major HPCMP study worked to determine how to safely airlift COVID-19-positive passengers to treatment. Researchers studied computational fluid dynamics of airflow, as well as the droplets within that airflow, to decide on the safest ways to transport infected patients, all while posing a minimal risk to aircrews and medical attendants. When it came time to investigate potential COVID-19 vaccines, supercomputers once again proved to be a useful tool. In conjunction with the U.S. Army Medical Command and the Walter Reed Army Research Institute, the HPCMP used high-performance computers located at ERDC and Aberdeen Proving Ground, Maryland, to more quickly examine target proteins and their chemistry. Before HPCMP supercomputing
power, only 2 million vaccine options could be considered over a threeweek period, but with the help of the program, researchers were able to examine close to 40 million target compounds. Yet another modeling effort ensued when more than 40 ERDC researchers from multiple laboratories worked 16 hours a day as members of the COVID-19 Model and Analysis Team (C-MAT) to develop, operationalize, and deliver the most accurate and timely projections of COVID-19 spread possible, grounding the predictive modeling solidly on the best available data. The ERDC-Susceptible Exposed Infected Recovered, or ERDC-SEIR, model was developed over the course of several weeks, providing the foundation for the ERDC approach to several modeling efforts. The model forecasts are provided to the USACE Geospatial Task Force, which then summarizes outputs in order for the broader USACE team to advise federal, state, and local partners on decisions related to COVID-19 courses of action. “It’s the most comprehensive modeling platform we’ve worked on,” said Brandon Lafferty, Ph.D., an ERDC Environmental Laboratory (EL) researcher leading the team’s day-to-day operations. “It’s been used as a planning tool for building ACFs, and it has provided estimates as to how many infected patients states and counties [may] have.” ERDC-SEIR predictions have also been used in an effort to support Federal Emergency Management Agency (FEMA) Region 1. Three researchers from ERDC-EL are on an interagency detail to FEMA’s Region 1 Data Analytics Team. The team supplements the ERDC-SEIR model with information relevant to hospital resource needs to help FEMA request the resources necessary for response and recovery in the New England states. In such complex situations as a pandemic, researchers use a “model ensemble” approach, or a collection of models, to develop predicted outcomes. The idea behind this approach is that if several independently developed models point to a similar answer, the conclusion inspires greater confidence. The ERDC-SEIR was one of 16 models consulted to make national forecasts for total deaths, and one of four used in the national forecast ensemble for hospitalization rates. The ERDC-SEIR was also featured on the Centers for Disease Control and Prevention’s (CDC) COVID-19 model ensemble website, the first instance a model developed and maintained by the Department of Defense was included in the CDC ensemble. As of this writing, the ERDC-SEIR is still being used by the USACE Geospatial Task Force and FEMA Region 1 to inform decisions. The model will run autonomously as it receives data and will post results on the CDC website. n 129