Presented by Barbara A. Han, Disease Ecologist at Cary Institute of Ecosystem Studies. Hosted by ASU Biodesign Institute as part of The Arntzen Grand Challenges Lecture Series
How can we prepare for infectious diseases we've never encountered, emerging in unexpected places and carried by animals we barely understand?
In recent years, scientists have begun addressing this daunting challenge: predicting the “unknown unknowns” of disease emergence in human populations. These efforts are increasingly critical in a rapidly changing world, where human activities are transforming ecosystems, increasing contact between people and wildlife and creating new opportunities for pathogens to spill over.
In this Arntzen Grand Challenges lecture, Barbara Han examined how researchers are working to make sense of this complexity by integrating ecology, virology and artificial intelligence. She highlighted recent efforts that combine machine learning with biological data to identify bat species that may carry dangerous viruses such as Ebola—and how these approaches can help pinpoint where and when future threats might emerge. While these methods do not yet offer perfect foresight, they represent some of the most advanced tools available for guiding disease surveillance, management and prevention. By working across disciplines and viewing nature through new scientific lenses, researchers are beginning to shift the paradigm: from reacting to pandemics to anticipating them.
Han’s research is at the intersection of ecology, computing and global health. She has pioneered the use of machine learning and artificial intelligence tools to understand when and where new zoonotic diseases are likely to emerge and why.
