Influenza A gradual and epochal evolution: insights from simple models.
The recurrence of influenza A epidemics has originally been explained by a "continuous antigenic drift" scenario. Recently, it has been shown that if genetic drift is gradual, the evolution of influenza A main antigen, the haemagglutinin, is punctuated. As a consequence, it has been suggested that influenza A dynamics at the population level should be approximated by a serial model. Here, simple models are used to test whether a serial model requires gradual antigenic drift within groups of strains with the same antigenic properties (antigenic clusters). We compare the effect of status based and history based frameworks and the influence of reduced susceptibility and infectivity assumptions on the transient dynamics of antigenic clusters. Our results reveal that the replacement of a resident antigenic cluster by a mutant cluster, as observed in data, is reproduced only by the status based model integrating the reduced infectivity assumption. This combination of assumptions is useful to overcome the otherwise extremely high model dimensionality of models incorporating many strains, but relies on a biological hypothesis not obviously satisfied. Our findings finally suggest the dynamical importance of gradual antigenic drift even in the presence of punctuated immune escape. A more regular renewal of susceptible pool than the one implemented in a serial model should be part of a minimal theory for influenza at the population level.
UMR 7625 (UPMC, ENS, AgroParisTech, CNRS), Ecole Normale Supérieure, Unit of Eco-Evolutionary Mathematics, Paris, France.
Sébastien
S
Ballesteros
Elisabeta
E
Vergu
Bernard
B
Cazelles
D000941:Antigens / Q000235:genetics; D019143:Evolution, Molecular; D040961:Genetic Drift; D006801:Humans; D007107:Immune System; D009980:Influenza A virus / Q000235:genetics*; D007251:Influenza, Human / Q000276:immunology* / Q000821:virology*; D018448:Models, Immunological; D008962:Models, Theoretical; D005810:Multigene Family; D009154:Mutation; D013269:Stochastic Processes
D000941:Antigens