Dynamical correlations in the escape strategy of Influenza A virus

TL;DR

This paper introduces a model linking genetic and antigenic distances in Influenza A virus, revealing how spatial correlations influence viral evolution and immune escape, mirroring real-world staggered evolutionary patterns.

Contribution

The paper presents a novel model based on spatial correlations among mutations that explains the dynamic structure of immunity space and its impact on influenza evolution.

Findings

Reveals a staggered time evolution pattern in the model matching real influenza dynamics.

Shows how spatial correlations among mutations shape the immunity landscape.

Demonstrates the influence of immunity space structure on virus-host interactions.

Abstract

The evolutionary dynamics of human Influenza A virus presents a challenging theoretical problem. An extremely high mutation rate allows the virus to escape, at each epidemic season, the host immune protection elicited by previous infections. At the same time, at each given epidemic season a single quasi-species, that is a set of closely related strains, is observed. A non-trivial relation between the genetic (i.e., at the sequence level) and the antigenic (i.e., related to the host immune response) distances can shed light into this puzzle. In this paper we introduce a model in which, in accordance with experimental observations, a simple interaction rule based on spatial correlations among point mutations dynamically defines an immunity space in the space of sequences. We investigate the static and dynamic structure of this space and we discuss how it affects the dynamics of the virus-host interaction. Interestingly we observe a staggered time structure in the virus evolution as in the real Influenza evolutionary dynamics.