What if scientists could anticipate the likelihood of an outbreak before it starts? What if, instead of scrambling to contain an emerging threat, we could prevent it?
In the last year, waves of illnesses such as Marburg virus, Mpox and avian influenza (H5N1) have underscored the need for enhanced preparedness to prevent future outbreaks. While the world continues to grapple with the long-term effects of COVID-19, scientists are working to harness the full potential of artificial intelligence in global health security through AI-driven modeling and predictive analytics — hoping to foresee potential outbreaks, assess risk factors and create early warning systems that can save lives.
Researchers at the University of Florida’s Emerging Pathogens Institute , for example, published an algorithm capable of predicting which COVID-19 variant in circulation today is most likely to become dominant in the next three months. This algorithm was used to spot new variants of concern, and it correctly identified 11 out of 11 variants a full 10 weeks before they were officially labeled by the Centers for Disease Control and Prevention .
By training these algorithms on publicly available genetic sequences of SARS-CoV-2, scientists can continue to predict which mutations will pose the greatest threat to public health.
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