Due to the sudden outbreak of COVID-19, college campuses and school systems were shut down globally to slow down the spread of the disease. Despite being largely successful in controlling the spread of COVID-19, school closings caused health problems, including physical and psychological stresses, for students, staff, and faculty in addition to direct economic impacts. This project develops a system to better support school re-openings with specific policies based on scientific data and information. The potential product can simulate the trajectory of COVID-19 cases and provide potential customers with a reliable method to scientifically monitor the status of their campuses. This product has the potential to be used globally and can be used to manage large events with a focused gathering site setting.
This I-Corps project is based on a spatiotemporal simulation/prediction system developed to address the urgent campus reopening questions caused by the COVID-19 pandemic. The system integrates investigation on spatiotemporal infrastructure including big data, cloud computing, analytics, and community outreach. Human behavior simulation, campus spatiotemporal dynamics, and public health data are combined to predicate possible viral case trajectories. The novel spatiotemporal simulation integrates agent-based people movement and public health risks as well as control policies (such as mask mandates, classroom size restrictions, test and tracking, and vaccination status) to derive accurate predictions. The system has been validated using data from several college campuses.The project includes four key participants with support from the center members, faculty, staff and interns: Zifu Wang (EL), zwang31@gmu.edu, Hai Lan (TL), hlan5@gmu.edu, Qyana Stewart (IM), and Phil Yang (PI)