Viral dynamics with immune responses: effects of distributed delays and Filippov antiretroviral therapy

J Math Biol. 2023 Jan 25;86(3):37. doi: 10.1007/s00285-023-01869-w.

Abstract

In this paper, we propose a general viral infection model to incorporate two infection modes (virus-to-cell mode and cell-to-cell mode), the CTL immune response, and the distributed intracellular delays during the processes of viral infection, viral production, and CTLs recruitment. We investigate the existence, the uniqueness, and the global stability of three equilibria: infection-free equilibrium [Formula: see text], immune-inactivated equilibrium [Formula: see text] and immune-activated equilibrium [Formula: see text], respectively. We prove that the viral dynamics are determined by two threshold parameters: the basic reproduction number for infection [Formula: see text] and the basic reproduction number for immune response [Formula: see text]. We also numerically explore the viral dynamics beyond stability. We use bifurcation diagrams to show that increasing the delay in CTL immune cell recruitment can induce a switch in viral load from a stable constant level to sustained oscillations, and then back to a stable equilibrium. We also compare the contributions of the two infection modes to the total infection level and identify the key parameters that would affect the percentages of virus-to-cell infection and cell-to-cell infection. Finally, we explore how Filippov control can be applied in antiretroviral therapy to reduce the viral loads.

Keywords: Cell-to-cell infection; Distributed delays; Filippov antiretroviral therapy; Viral dynamics with immune responses; Virus-to-cell infection.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Basic Reproduction Number
  • Computer Simulation
  • HIV Infections* / drug therapy
  • Humans
  • Immunity
  • Models, Biological
  • T-Lymphocytes, Cytotoxic
  • Virus Diseases*