Event

How predictable is evolution? This question has inspired biological research for decades, but it remains challenging to address quantitatively. In this talk, I will describe how we adapted methods from statistical physics to study viral evolution. Viruses offer an extraordinary opportunity for studying evolutionary dynamics because of their high rates of mutation, small genomes, and abundant data. Applied to SARS-CoV-2, our approach identified key mutations that enhance viral transmission, highlighting major variants before they became widespread. I’ll also describe how we’ve extended these methods to predict influenza evolution, forecasting the fate of individual mutations and which viral strains are likely to become dominant in future seasons. Our results show how theoretical techniques from physics can provide insights into viral evolution. In the future, similar models could be used to inform vaccine design. Beyond viruses, our framework also provides a general approach for studying stochastic dynamics that could be applied to other complex systems.