Key Factors and Parameter Ranges for Immune Control of Equine Infectious Anemia Virus Infection

Dylan Hull-Nye

Washington State University

"Key Factors and Parameter Ranges for Immune Control of Equine Infectious Anemia Virus Infection"

Equine Infectious Anemia Virus (EIAV) is an important infection in equids, and its similarity to HIV creates hope for a potential vaccine. We analyze a within-host model of EIAV infection with antibody and cytotoxic T lymphocyte (CTL) responses. In this model, the stability of the biologically relevant endemic equilibrium, characterized by the coexistence of long-term antibody and CTL levels, relies upon a balance between CTL and antibody growth rates, which is needed to ensure persistent CTL levels. We determine the model parameter ranges at which CTL and antibody proliferation rates are simultaneously most influential in leading the system towards coexistence and can be used to derive a mathematical relationship between CTL and antibody production rates to explore the bifurcation curve that leads to coexistence. We employ Latin hypercube sampling and least squares to find the parameter ranges that equally divide the endemic and boundary equilibria. We then examine this relationship numerically via a local sensitivity analysis of the parameters. Our analysis is consistent with previous results showing that an intervention (such as a vaccine) intended to control a persistent viral infection with both immune responses should moderate the antibody response to allow for stimulation of the CTL response. Finally, we show that the CTL production rate can entirely determine the long-term outcome, regardless of the effect of other parameters, and we provide the conditions for this result in terms of the identified ranges for all model parameters.
Additional authors: Tyler Meadows, Department of Mathematics and Statistics, Queen's University; Stacey R. Smith?, Department of Mathematics and Faculty of Medicine, The University of Ottawa; Elissa J. Schwartz, Department of Mathematics and Statistics, School of Biological Sciences, Washington State University

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