A predictive fitness model for influenza

By M. Łuksza, Michael Lässig. 2014

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Predicting evolution from the shape of genealogical trees (2014, methodology): “Figure 5 shows bootstrap distributions of d for our methods and compares it to Łuksza and Lässig (2014) as well as two naive prediction methods: (i) a growth rate estimate of individual clades obtained by fitting an exponential curve to the fraction of the total sequences that are part of this clade”
The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin (2014, background): “It also may be possible to utilize high-throughput experimental data on mutational effects to better estimate the fitness of naturally occurring strains in a way that aids in prediction of the yearto-year strain dynamics of influenza (Łuksza and Lässig, 2014).”
Predicting evolution (2017, methodology): “This problem is difficult in general, but at least the response of pathogen population size to immune or vaccination pressure can be computed using fitness models of immune interactions 13,120,121 .”
Modeling infectious disease dynamics in the complex landscape of global health (2015, positive): “Recent models of influenza fitness have also been developed to predict viral evolution from one year to the next, providing a principled and more precise method for the vaccine selection required every year (90).”