2013/03/01 by Lorenzo Taggi, Francesca Colaiori, Vittorio Loreto +1
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Physics and Astronomy · #Biology #COVID-19 epidemiological studies #Epistasis #Gene #Genetics #Influenza A virus #Influenza Virus Research Studies #Mathematical and Theoretical Epidemiology and Ecology Models #Mathematics #Physics #Statistical physics #Virology #Virus #physics.bio-ph #q-bio.PE
paper · pdf · doi:10.1209/0295-5075/101/68003
published as EPL 101 (2013) 68003 · 14 pages, 5 figures; main paper for the supplementary info in arXiv:1303.5953
openalex publication_date 2013/03/01 · arxiv created 2013/05/15 · arxiv updated 2016/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.