Using AI to Predict and Preempt Epidemics
Cary Institute/Pamela Freeman©
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.
Tonight join Dr. Han as she discusses how she is harnessing the power of big data and machine learning to create maps of regions that are hotspots for disease spillover. Learn how climate change affects zoonotic disease transmission, what traits make animals risky neighbors and the critical role of basic science in making accurate predictions to safeguard public health.
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