Kean University Research Maps COVID-19 Impact by ZIP Code

UNION, N.J. — A Kean University mathematics associate professor has developed data analytics research on the impact of COVID-19 that is helping guide authorities as they respond to the pandemic and roll out vaccines.

George Avirappattu, Ph.D., and his team use data analytics of ZIP Code-level demographic data combined with COVID-19 outcome data to identify how different communities are impacted by the coronavirus. Working with five Kean students, the researcher uses Geographic Information Systems (GIS) statistical analysis and machine learning to analyze data.

“Our work helps identify what factors make certain communities more vulnerable to COVID-19 than others,” said Avirappattu, who teaches in the Dorothy and George Hennings College of Science, Mathematics and Technology (CSMT). Examples of social vulnerability factors include median household income, occupation, housing and average educational attainment.

“That, in turn, helps identify communities to target for intervention strategies,” he added. “Our work can help develop an equitable vaccination policy for the general population based on data.”

Click here for an interactive map of Florida data.

The project won praise from public health officials in states such as South Carolina, who recommended Avirappattu’s research to the federal Centers for Disease Control (CDC) during a conference call on vaccine roll-out.

“His work has been extremely helpful for us as we were planning and continue to refine the plan for our vaccine distribution efforts,” said Dr. Abdoulaye Diedhiou, director of the Division of Acute Disease Epidemiology in that state’s Department of Health and Environmental Control.

Kean President Lamont O. Repollet, Ed.D., said the project exemplifies Kean’s research possibilities.

“Dr. Avirappattu’s research and public service engagement with health officials are making a difference while also providing our students with a valuable learning experience,” Repollet said. “This project and others like it are helping to move Kean closer to becoming the next great research university in the state of New Jersey.”

Avirappattu began working with “big data” and machine learning at Kean in 2014. He was part of a team under the guidance of CSMT Dean George Chang, Ph.D., that developed a data analytics option in mathematics at Kean.

The researcher was doing a different statistical analysis project at New York University when COVID-19 arose. “As a population research group, our attention naturally turned to that,” Avirappattu said.

When the pandemic began, experts quickly saw the illness hit harder among minority communities. But as it continued, Avirappattu said studies increasingly showed socioeconomic and environmental factors play an outsized role in causing that disparity. “Our research supports this with data-based evidence,” he said.

Kean senior Andres Alvarez of Elizabeth, who is majoring in mathematical sciences, is part of Avirappattu’s student research team. His duties are to design and develop a website to display the data.

“Working with the research group is exciting and vigorous. The best part is getting to meet new people and sharing ideas to accomplish our goals,” he said. “The extensive work and experience we are gaining will help me for a future career.”

The project also requires balancing privacy concerns with data use. Avirappattu said the CDC does not release COVID-19 data below the county level, so the more detailed data had to be gathered state by state.

The project received a 2021 Kean Faculty Seed Grant from the Office of Research and Sponsored Programs.

“This helps students see that mathematics and statistics, when combined with programming, is an emerging potent combination that can solve real-world problems in ways never tried before,” CSMT Dean Chang said.

Avirappattu said the research will continue to be relevant after the pandemic.

“Our findings shine light on issues that need to be addressed to better tackle the next pandemic or natural disaster,” he said. “Our goals are to develop statistical and machine learning tools to educate the public through facts and empower decision-makers to develop policies and guidelines to serve their communities more effectively and equitably.”