Raphael Stern: Viral spread and containment via transportation networks
An expert, by definition, excels in one area. Real-life problems, however, rarely fall into just one area. For this reason, Raphael Stern values collaboration.
When the COVID-19 pandemic arose, Stern saw a connection between the transportation network theory he researches and the spread of the novel corona virus. Stern’s reasoning proceeded like this: people are sick; people move along a transportation network; people spread the virus. He saw a need to apply network theory to the new-to-him problem of virus spread. So Stern sought out a colleague with expertise in viral spread.
Collaboration: Transportation Networks and Viral Spread
Now, Stern and Philip Paré, a colleague at Purdue University with expertise in viral spread, are exploring how recent changes in the transportation network, such as canceled flights and travel restrictions, help control the spread of COVID-19. “We’re trying to understand how transportation networks act to propagate the virus using virus spread models, and to understand how limiting travel can help contain viral spread.”
Network science methods are based on linear algebra, and the method can be applied to many systems. Transportation networks apply that science to how people move. Viral spread theories can be applied to information spreading through the internet or to a virus spreading through a population.
Viral spread science relies on what is called a SIR or SEIR model. Elements (people) in the model are labeled in terms of potential to be infected: S = susceptible, E = exposed, I = infected, or R = removed (not—or no longer—likely to be infected). Once the elements in the model have been labeled, the researchers can examine the number of each element within an area and track patterns of infection.
Stern, Paré, and Mingfeng Shang, a Ph.D. student advised by Stern, plan to study how the virus spread via airports in three geographic areas: California, a province in China, and a multi-state area on the east coast (including New York, New Jersey, Rhode Island, and Massachusetts). This research is being supported by the National Science Foundation.
Stern has begun a similar study with fellow CEGE professor Michael Levin focused on viral movement within Minnesota. They will study changes in the volume of road traffic (vs air traffic) within and across two or three regions in the state and plan to have results this fall. Lessons learned could guide transportation policy in the instance of a second wave of COVID-19 or even another viral outbreak sometime in the future.
Stern is also advising Shang and another student as they explore how traffic changed during the quarantine. Data shows that traffic volumes in the Twin Cities were down 40% overall at the peak of the quarantine, but just what does that dip mean? Does it, for example, compare to a large snowstorm? This project seeks to understand just how anomalous that dip was compared to other traffic interruptions.
Stern’s research is primarily computer based. Computations and modeling can be conducted anywhere, so he is unlimited in that sense. Yet he says, “It is more difficult to have interactive conversations, to brainstorm ideas, or to share sketches when we are not together in person. I have felt more constrained in those activities.” This constraint has led Stern to learn and apply new online collaboration tools. He has discovered one great advantage of using an online whiteboard: having an electronic record of the board at the end of a collaborative session.
In the face of new challenges, Stern is finding new ways to apply his engineering expertise for the benefit of his students and our society.