COVID Modelers Expand their Missions

COVID Modelers Expand their Missions, By Gregory Goth

Commissioned by CACM Staff,March 9, 2023

Last August, the University of Texas COVID-19 Model Consortium posted its model of the expected number of COVID-19 cases that would be arriving at school in September in the form of an interactive map.

In the initial days of the COVID-19 pandemic, a new kind of computational modeling theory began to emerge: instead of relying on traditional public health data as used in "tried and true" SIR (Susceptible, Infected, Recovered) models, new types of data, such as aggregated mobility data gleaned from smartphone GPS signals, helped policymakers and scientists alike begin to make sense of the dangerous and deadly effects of the novel virus.

The fast spread of the virus and the drastic effects it had on daily life were, it turned out, a tailor-made field of possibility for academic computer scientists and public health researchers, who ramped up complex models very quickly.

"In the beginning of the pandemic, there were a lot of national-level data models, and in our virtual water cooler talks we said that was ridiculous," David Rubin, M.D., director of the Children's Hospital of Philadelphia (CHOP) PolicyLab, which undertook localized data modeling on a national scale during the pandemic. "The fact that New York City was surging didn't mean that Montgomery, AL, was surging, so we developed a model that grew to about 800 counties. With lots of local variables incorporated every week, we started to calibrate a model that was more like a weather forecast for a local area, and I think that was the real value of the approach we took."

Other leading-edge modeling efforts also emerged, such as the University of Texas (UT) COVID-19 Modeling Consortium, and the University of Virginia (UVA) Biocomplexity Institute. Among the results of the UT consortium was a staged alert system that treaded a careful line between restrictive measures and keeping society open, forecasting hospital demand on that fine line. At UVA, Biocomplexity Institute researchers began modeling the spread of the disease in January 2020 and had already produced predictions of the effects of social distancing mandates within weeks of the near-national shutdown that March.  .. '