Smith Researcher Leading NSF-Funded, Data-Driven Fight Against Pandemics

Dean’s Professor of Information Systems Louiqa Raschid at the University of Maryland’s Robert H. Smith School of Business is principal investigator for a new, $1 million predictive analytics project to develop sophisticated predictive models and best communication practices to combat future pandemics.

This UMD-led effort is funded by the National Science Foundation as part of its new Predictive Intelligence for Pandemic Prevention Program.

Raschid and her team will crunch voluminous data from the current pandemic and analyze social media content, epidemiological statistics and public statements from officials.

The project aims to develop a digital platform, called PandEval (pandemic evaluation), that can zero-in on specific locales, offering a level of detail not widely available during the current pandemic.

“An effective response to pathogen spread requires a seamless, end-to-end network that takes into account complex and interdependent biological, environmental and human factors,” said Raschid.

Raschid, who has an appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS), is joined by a multi-institutional team of computational social scientists and data scientists, public health experts, biostatisticians and epidemiologists.

It includes Vanessa Frias-Martinez, an associate professor in the College of Information Studies; Xiaoli Nan, a professor of communication in the College of Arts and Humanities; Kristina Lerman, a professor of computer science at the University of Southern California; Eili Klein, M.D., an associate professor of emergency medicine at Johns Hopkins University; and Neil Sehgal, an assistant professor of health policy and management in the School of Public Health.

“What we’ve seen is a need to improve messaging and policymaking at the local scale,” said Sehgal. “Public acceptance for health-related mandates—things like a statewide shutdown of non-essential businesses—could look very different in Montgomery County than on the Lower Eastern Shore.”

To develop robust algorithms for the PandEval platform, the researchers are curating data that includes almost two billion Twitter posts since January 2020, social media captures from Facebook, GPS digital footprints from location intelligence companies, face masking statistics from a New York Times database and inoculation data from the Centers for Disease Control and Prevention.

The team will use Twitter and Facebook posts to develop social media-based models of community beliefs and attitudes, offering a window into areas like science skepticism, concern about vaccine safety, a lack of trust in public officials or an unwillingness to contribute to the public good.

“We think the benefits of PandEval will be twofold: increasing trust and confidence in our public health infrastructure and giving decision makers epidemiological models that are customized to specific population segments,” said Raschid. “This can be invaluable for things like vaccine rollouts and health-related mandates.”

Source: University of Maryland Institute for Advanced Computer Studies, via Maryland Today.