Johns Hopkins The new tool is the first to use large language modeling to predict infectious disease risk. A new AI tool to predict the spread of infectious disease outperforms existing state-of-the-art forecasting methods.
The tool, created with federal support by researchers at Johns Hopkins and Duke universities, could revolutionize how public health officials predict, track, and manage outbreaks of infectious diseases including flu and COVID-19.
“COVID-19 elucidated the challenge of predicting disease spread due to the interplay of complex factors that were constantly changing,” said author Lauren Gardner of Johns Hopkins, a modeling expert who created the COVID-19 dashboard that was relied upon by people worldwide during the pandemic. “When conditions were stable the models were fine. However, when new variants emerged or policies changed, we were terrible at predicting the outcomes because we didn’t have the modeling capabilities to include critical types of information. The new tool fills this gap.”
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