Predicting the evolution of influenza
Michael Lässig (Institut für Theoretische Physik, Universität zu Köln)
The human flu virus undergoes rapid evolution, which is driven by interactions with its host immune system. We describe the evolutionary dynamics by a fitness model based on two molecular properties of the virus: protein folding stability and binding affinity to human antibodies. This model successfully predicts the evolution of influenza one year into the future. Thus, evolutionary analysis transcends its traditional role of reconstructing past history. This has important consequences for public health: evolutionary predictions can inform the selection of influenza vaccine strains. We discuss the conditions of predictability and highlight the role of physics in making evolutionary biology a predictive science.