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Math + Computer Science

A Crystal Ball?

How Mathematical Modeling Can Predict the Future of Covid And Other Infectious Diseases

In our inaugural edition of Foundations, you learned about the important COVID-19 research conducted by Drs. Matthew Johnston and Bruce Pell . As the pandemic lingers, ebbing and flowing in severity, introducing the nation and the world to new variants, and continuing to disrupt lives, Mathematics Professors Johnston and Pell published new research on the impact of vaccinations using mathematical modeling.

"COVID has affected different groups of people in vastly different ways," Johnston said. "The probabilities of severe outcomes are different for old and young people, vaccinated and unvaccinated, for instance." Pell explained that “since our study, we now have people who are vaccinated and unvaccinated, and people who received the first and second booster shots and those who did not. This would also be interesting to study but the data was not available to us at the time.”

Johnston's interest was piqued when a colleague living in Alberta, Canada, posted a time-course chart documenting hospitalizations and ICU (Intensive Care United) patients from the start of 2021 through the end of the year by vaccination status.

“We wanted to use qualitative data to truly tease out how effective the vaccine is using mathematics and the appropriate data sets and being very scientific in our conclusions.”

– DR. BRUCE PELL

From the start of 2021, when vaccines started to become available, to the end of 2021, when vaccines were available to everyone who wanted one, he was charting hospitalizations and the vaccine status of the patients.

“I became interested in the narrative,” Johnston said. “You could read the 140-character diatribes on Twitter: ‘Look, there are way more people who are vaccinated and still getting COVID.’” 

Pell agreed. “We wanted to use qualitative data to truly tease out how effective the vaccine is using mathematics and the appropriate data sets and being very scientific in our conclusions.”

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Simulations of the two-stage vaccination model.

The scientists gathered publicly available reports from the state of Virginia and stratified the numbers of unvaccinated, partially vaccinated, and fully vaccinated people. They built a comprehensive mathematical model that tracked and can predict the spread of a disease. Could we mitigate the spread by having more people vaccinated? And what if they also got the booster shot?

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New cases by vaccination status are shown next to the the observed and model predicted cases.

The study suggested that the main culprit of the Summer 2021 spike in COVID cases was the significantly increased transmissibility of the Delta variant, not a failure of vaccines. “If you actually look at the data, people who had the vaccine were less likely to get the disease during the Delta wave. It was still preventing infection, serious infection, “Johnston said. “Delta was twice as contagious as the original COVID strain.”

By the time “A Mathematical Study of COVID-19 Spread by Vaccination Status in Virginia” was published on February 8, 2022, in the peer-reviewed journal Applied Sciences, Special Issues, however, a new strain called Omicron had taken over. In a month and a half, Omicron has pushed the Delta variant off the COVID map, Johnston said, demonstrating the importance of timely mathematics research.

To that end, Pell spearheaded an inquiry into the optimal length of time between booster shots to keep the population vaccinated to fight against COVID infection. The research, which is currently undergoing peer review, “used publicly available data from our own state of Michigan and applied a mathematical model that incorporated waning immunity from infection and vaccination," he said.

“The grant will help us build impactful models which assist the healthcare community in predicting and managing the impact of variants.”

– DR. MATTHEW JOHNSTON

Meanwhile, Johnston was recently awarded a prestigious two-year $242,192 LEAPS-MPS grant funded by the National Science Foundation (NSF) . He looks forward to begin working this fall with Pell and a team of undergraduate research assistants to develop urgently needed mathematical frameworks for modeling the spread of COVID-19 and other infectious diseases in heterogeneous populations. He concluded, "The grant will help us build impactful models which assist the healthcare community in predicting and managing the impact of variants. Using scientific data, we have the power as a society to keep COVID-19 at a manageable level through targeted interventions rather than disruptive population-wide lockdowns."

The power of the type of modeling used by Johnston and Pell is that it’s predictive and teases out the important treatments and behaviors that can moderate the spread of the disease. Mathematics allows researchers to test different scenarios quickly and eventually create an effective public policy. “That’s also why we publish and why we present our results at conferences,” explained Johnston. “So other people can read…and learn!”

by Renée Ahee