Since the beginning of the pandemic, top researchers worldwide have been putting in long hours to try to understand the coronavirus as it spreads across the globe.
Not every scientist spearheading that research is a veteran in the field. One is a rising junior at the University of Vermont.
Jayce Slesar, who is studying data science at UVM, is currently leading an effort to aggregate research from scientists around the world on Covid-19. The project will boil down all the information into one dashboard that can sort out which studies and policies are most effective at helping to understand and contain the virus.
Slesar is working in conjunction with John Hanley, a professor at UVM, on the project, as well as postdoctoral student Vitor Mori and Jason Bates, a lung expert at UVM.
Hanley said gathering data on the studies of Covid-19 around the world will give researchers a better sense of where the virus is, and how ideas about its rates of transmission are shifting and evolving.
Despite being just a junior in college, Slesar has worked with Bates for several years, starting when he was in high school. He helped with Bates’ work on lung and respiratory disease as part of his senior project.
While Bates is an expert in the world of lung disease, he didn’t have the coding skills to scrape the web for the information they needed for the project.
That’s where Slesar came in.
For five or six hours each morning, Slesar has been using Python, a programming language, to scrape the internet for all the research on the web that might be applicable to his work.
Then, he goes through each study, and enters the date and location it was conducted into a computer program, along with all the numbers that he’s interested in tracking, including infection rate, hospitalization rate, death rate, asymptomatic case rate and others.
Slesar said the date and location of each study is especially important, because the information he’s looking for has become much better over time, and not everywhere is producing equally good data. His work, Slesar said, will help identify mistakes some researchers are making so others don’t follow suit, and help identify patterns of what makes a good study.
Many studies are specific to certain areas. Because public health policies that are in place in each part of the world vary so much it makes any comparisons difficult, Slesar said.
“The infection rate in Vermont, for example, is different than it is anywhere else in the world, honestly,” he said.
The aim for the research, he said, is that it can eventually help lawmakers and public health leaders better make decisions about public policy during the pandemic.
“It feels good to know I’m doing my best to help everyone do their best right now,” Slesar said.
Slesar said he doesn’t have the statistics skills to do the “really cool” parts of the work, but he does have the coding know-how to help get the project off the ground quickly and efficiently.
Hanley is helping to guide Slesar in this initial part of the process, and will help with the analysis of the data. He said Slesar is “very skilled” at the data work he is doing.
“Science doesn’t typically work this fast,” Hanley said. “We usually have a lot more time to see a problem and analyze it. Right now, there’s just a flood of publications out there, both peer-reviewed and hoping to be peer-reviewed.”
So having someone with the skills Slesar has, he said, is essential to gathering and analyzing this data in real time.
“This is our first big global pandemic where the world has been so connected,” Slesar said. “If we can figure out what we’re learning and how accurate that learning is, over time we can conglomerate all that information and figure out how to learn from each other a lot faster.”
In the first few weeks of the pandemic, Slesar and Hanley were working on modeling of the virus in Vermont, but quickly decided there were enough adequate models for the state already. Instead they shifted their focus to do a “meta analysis” that went much broader than the state.
“In the early days of this pandemic, no one really knew who was doing what,” Hanley said. “Once we settled down, we wanted to focus on an area that didn’t seem to be as crowded so we could really be helping out the scientific community.”
There’s a much smaller group of scientists doing the kind of work they’re doing now, Hanley said.
“At some point, the scientific community is going to be looking back and reflecting on the work that we put into modeling this epidemic, and also reflecting on the best practices for determining these parameter values and modeling the severity of this pandemic,” Hanley said. “I think this will be a useful tool in helping analyze how good a job we did.”
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