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Using AI to Predict & Preempt Epidemics

Millions of lives are lost each year to illnesses caused by pathogens that spread from wildlife and domesticated animals to people. Too often, outbreaks of Ebola, Nipah, Zika, and other zoonotic diseases force communities into reactive mode: scrambling to contain their spread and minimize suffering.

What if we could forecast pathogen spillovers and diffuse them before they made people sick? This question is at the heart of Cary Institute disease ecologist Dr. Barbara Han’s research program. Working at the intersection of ecology, computing, and global public health, she is developing tools to predict and preempt disease outbreaks.

Dr. Han will discuss how she is harnessing the power of big data and machine learning to create maps of regions that are hotspots for disease spillover. By identifying animal species that are likely to harbor pathogens and pinpointing where their populations intersect with people, her work can guide disease surveillance and protect public health.

Learn how climate change and urbanization influence zoonotic disease transmission, what traits make animals risky neighbors, Han’s projects with IBM and DARPA, and the critical role of basic science in making accurate predictions to safeguard public health.

Disease forecasting has the potential to prevent the next pandemic. Come join the conversation.

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