6533b7d5fe1ef96bd1263c68
RESEARCH PRODUCT
Host–virus evolutionary dynamics with specialist and generalist infection strategies: Bifurcations, bistability, and chaos
Josep SardanyésLluís AlsedàAnel NurtaySantiago F. ElenaMatthew G. Hennessysubject
BistabilityPopulationGeneral Physics and AstronomyDynamical Systems (math.DS)Fixed pointParameter spaceBiologyGeneralist and specialist speciesModels Biological01 natural sciencesStability (probability)010305 fluids & plasmas0103 physical sciencesFOS: MathematicsHumansQuantitative Biology::Populations and EvolutionComputer SimulationMathematics - Dynamical SystemsQuantitative Biology - Populations and Evolution010306 general physicsEvolutionary dynamicseducationMathematical Physicseducation.field_of_studyApplied MathematicsDegenerate energy levelsPopulations and Evolution (q-bio.PE)Statistical and Nonlinear Physics3. Good healthNonlinear DynamicsEvolutionary biologyFOS: Biological sciencesHost-Pathogen InteractionsVirusesVirus Physiological Phenomenadescription
In this work, we have investigated the evolutionary dynamics of a generalist pathogen, e.g., a virus population, that evolves toward specialization in an environment with multiple host types. We have particularly explored under which conditions generalist viral strains may rise in frequency and coexist with specialist strains or even dominate the population. By means of a nonlinear mathematical model and bifurcation analysis, we have determined the theoretical conditions for stability of nine identified equilibria and provided biological interpretation in terms of the infection rates for the viral specialist and generalist strains. By means of a stability diagram, we identified stable fixed points and stable periodic orbits, as well as regions of bistability. For arbitrary biologically feasible initial population sizes, the probability of evolving toward stable solutions is obtained for each point of the analyzed parameter space. This probability map shows combinations of infection rates of the generalist and specialist strains that might lead to equal chances for each type becoming the dominant strategy. Furthermore, we have identified infection rates for which the model predicts the onset of chaotic dynamics. Several degenerate Bogdanov–Takens and zero-Hopf bifurcations are detected along with generalized Hopf and zero-Hopf bifurcations. This manuscript provides additional insights into the dynamical complexity of host–pathogen evolution toward different infection strategies.
year | journal | country | edition | language |
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2019-11-14 |