A University of Lethbridge team won first place in the STEM Fellowship's Inter-University Big Data Challenge 2022 in the Research Solutions category. (Photo: U of L)

By David Opinko

U of L team wins “big data challenge” by predicting pandemic paths

Aug 15, 2022 | 12:50 PM

LETHBRIDGE, AB – A team of students and researchers at the University of Lethbridge’s (U of L’s) Canadian Centre for Behavioural Neuroscience hope to make it easier for societies to respond to future pandemics.

The team, consisting of Ph.D. candidate HaoRan Change, Ph.D. student Lukas Grasse, and master’s students Yagika Kaushik and Sally Sade, claimed first place at the STEM Fellowship Inter-University Big Data Challenge 2022 in the Research Solutions category.

They analyzed a data set from Johns Hopkins University that tracked the daily number of new COVID-19 cases, mostly from locations in the U.S., from March 2020 to June 2022.

According to a media release from the U of L, the COVID-19 pandemic revealed flaws in the world’s ability to respond to unexpected health disasters. Medical supplies like ventilators and PPE were in short supply and could not be sent to the areas that needed them the most.

Sade says, if the next geographical location in a pandemic’s path could be predicted, governments and other organizations could potentially be able to stop the virus from spreading further.

What's Happening in Lethbridge this week: November 12-17, 2024

Nov 12, 2024

What's Happening in Lethbridge this week: November 4-10, 2024

Nov 04, 2024

What's Happening in Lethbridge this week: October 28-November 3, 2024

Oct 28, 2024

“What we could do with that data is allocate scarce resources to those regions pre-emptively before you see spikes occurring, so you’re not wasting resources in one region when they could be allocated to another,” says Sade.

Grasse adds that they reduced the number of locations into 10 clusters representing geographically similar locations in the same time period.

“We could see how each cluster influenced other clusters,” says Grasse. “A cool thing we found is that certain clusters, if they could have been eliminated, would have prevented the spread of COVID to later clusters. The idea is that if you could stop the spread of COVID at this one time and place, it would actually prevent all this later infection.”

In the U.S., the data shows COVID cases started along the east and west coasts and then spread to the Midwest, before spreading back again to the coasts.

“If some of that infection could have been prevented in the Midwest, or resources actually allocated there even though there isn’t quite the same population density as the coast, you could have hopefully prevented a lot of the later cases in the high population areas on the coasts,” says Grasse.

Using their model, the team was able to predict a spike in COVID cases for July 2022, which Sade says turned out to be the case with the surge in the BA.5 subvariant.

213 teams from 69 universities competed virtually in the STEM Fellowship Inter-University Big Data Challenge 2022. The U of L team won a $1,000 cash prize and will have their manuscript published in the STEM Fellowship Journal.