SDSC researcher leads e-Decision Tree efforts used for classrooms and school buses
Since the start of the pandemic, a group of UC San Diego researchers have been meeting weekly with epidemiologists at the County of San Diego Health and Human Services Agency (HHSA) to discuss COVID-19 dynamics, analyze populations at higher risk and explore the county’s pandemic response and new ways to mitigate the infection. This early collaboration resulted in several interesting projects, including one led by San Diego Supercomputer Center (SDSC) researcher Ilya Zaslavsky and a team of UC San Diego undergraduate data science students, who developed an agent-based simulation system to assist in COVID-safe school re-openings within San Diego County.
SDSC Researcher Ilya Zaslavsky led the team of undergraduate data science students who developed an agent-based simulation system to assist in COVID-safe school re-openings. Photo courtesy of SDSC External Relations.
While a variety of high-level policies were considered to make school re-openings as safe as possible, little was known about potential infection spread in a school setting and the efficacy of mitigation measures. At the same time, both teachers and parents were anxious to learn what might happen with children in specific schools, given each site’s variation in design, resources and mitigation plans.
Using an early online version of a site simulator, school officials simulated interactions between agents—students and teachers in different grades—as they participated in different types of activities throughout 15 school days: learning at individual desks during class time, group activities, recess time and having lunch in the school cafeteria or classroom. To assess infection risks due to aerosol and droplet transmission, the model used real school floor plans, layouts and capacities of classrooms, cafeterias and recess areas.
Schools were mostly closed for on-campus instruction at the time of these initial simulations, so the modeling team had to rely on data from other countries, from literature and from other fluid dynamics models to generate these initial simulations.
“The simulations allowed us to pinpoint areas in schools that would present higher COVID-19 transmission risks, and to evaluate relative importance of non-pharmaceutical interventions such as wearing masks, reducing class sizes or canceling lunch in the cafeteria and moving it to classrooms,” said Zaslavsky, who is director of the SDSC Spatial Information Systems Laboratory.
According to Zaslavsky, the spatially explicit, agent-based modeling of COVID-19 transmission at schools allowed individual sites and districts to test their plans and match them with their specific spaces, resources and population.
Within several days after the team demonstrated the model in September 2020 to nearly 400 San Diego educators, on a call organized by the …….