Every Monday morning, thousands of parents ask themselves a difficult question: Is my child too sick to go to school?
When searching for an answer, studies indicate that parents weigh many factors, including their child’s symptoms, the likelihood of making others sick, the school’s attendance policies and looming tests or assignments. The clock is ticking, and choices must be urgently made.
A kid with the sniffles or the stomach flu might just be a family having a bad week. But when illness spreads through a population in patterns that suggest large-scale transmission and escalation, that is called an epidemic.
Public health officials shift into high gear. They must make the same kinds of decisions as America’s parents, but on a massive scale, weighing plans designed to help large groups of people avoid contracting a disease while minimizing disruptions to society. To get it right, these officials need reliable information.
That’s where data scientists like K. Selçuk Candan come in.
Candan is a professor of computer science and engineering in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University. He is leading a new research initiative that could dramatically change how experts respond to emerging disease threats.
Backed by a grant from the National Science Foundation Accelerating Computing for Epidemic Discovery program, Candan and his team are building a system called PanAX, a powerful new approach to epidemic modeling and decision support.
PanAX is a new data modeling tool that uses data science and artificial intelligence, or AI, to learn from past epidemics and apply that knowledge to new or potential ones. Instead of starting from scratch each time a new epidemic emerges, PanAX combines past data and existing models and then uses machine learning to quickly assess how a disease might spread under various conditions.
“An epidemic is shaped by how people behave, where they live, how mobile they are and what decisions are made,” Candan says. “PanAX helps account for all of that, even when we have limited data.”
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