Fitness flux in SARS-CoV-2 and influenza H3N2

Abstract

The tempo of viral adaptation is usually read indirectly from the composition of mutations, through measures such as dN/dS. Here we measure it directly from the dynamics of variant frequencies, where we use multinomial logistic regression to estimate a fitness for each co-circulating variant. We aggregate these estimates to derive the rate of change of mean population fitness, referred to as fitness flux. Tracing SARS-CoV-2 from its emergence, we find that it initially adapted rapidly, doubling in fitness every 6 months from Jan 2021 to Jun 2022, but slowing to every 2.4 years from Jul 2022 to Dec 2025. Seasonal influenza H3N2 sustained a slower, steadier pace doubling in fitness every 10.0 years. In both, the rate of fitness gain closely tracks the variance in fitness, matching the 1:1 expectation of Fishers fundamental theorem. Phylogenetic contrasts between parent and child lineages localize most fitness gain to spike, and within spike to the receptor-binding domain, where a simple count of spike S1 substitutions predicts lineage fitness about as well as deep-learning escape and protein-language-model scores. Measuring fitness directly thus offers a transparent, frequency-based alternative to mutational proxies for tracking and anticipating viral adaptation. The website blab.github.io/fitness-flux/ is the intended reading experience of this paper, providing responsive layout and interactive figures.