SATURDAY, OCTOBER 1, 2016

New predictive model could clarify flu evolution

A new model used to predict the evolution of the influenza virus could help to scientists to better understand and select flu vaccine strains, according to a study published on Wednesday in Nature.

Researchers at Columbia University and the University of Cologne developed the model to predict the evolution of the flu virus from one year to the next. The new model could lead to a new, systematic way to select flu vaccine strains.

Because influenza is a fast-evolving pathogen, it is a challenging global health issue to select the optimal vaccines for a given flu season. Different flu strains compete with each other in a race to determine which will successfully infect humans. The researchers asked whether or not scientists could predict which competitor would win the race.

"This was a challenge for an evolutionary biologist because there are very few systems in the wild for which quantitative predictions of their evolution are at all feasible," Marta Łuksza, a co-author on the study, said. "It was also a computational and theoretical challenge. While traditional evolutionary thinking is about reconstruction of the past, we had to develop ideas on how to reach into the future."

Łuksza and Michael Lässig used the Darwinian principle of survival of the fittest, considering innovation and conservation to determine which virus strains had the optimal combination of the two. In the study, the researchers touched on the question of how predictable biological evolution is.

"There is clearly no general answer to this question," Łuksza said. "But our analysis shows under what auspices limited predictions may be successful."

The researchers said that further extensive tests using global influenza data could help determine if their method would result in improved vaccines.