Viral dynamics of an HIV stochastic model with cell-to-cell infection, CTL immune response and distributed delays

Yan Wang1, Ting Ting Zhao2, Jun Liu1

  • 1College of Science, China University of Petroleum (East China), Qingdao, Shandong 266580, P.R. China.

Insights

Stochastic modeling of HIV infection reveals noise can influence viral dynamics. High noise intensity may lead to virus extinction, while low noise can sustain virions and immune responses.

Area of Science:

  • Mathematical Biology
  • Epidemiology
  • Immunology

Background:

  • HIV infection involves both virus-to-cell and cell-to-cell transmission.
  • CTL immune response is crucial in controlling HIV replication.

Purpose of the Study:

  • To analyze a stochastic HIV infection model with distributed delays.
  • To investigate the impact of noise intensity on viral dynamics and immune response.

Main Methods:

  • Stochastic integro-delay differential equations were transformed into degenerate stochastic differential equations.
  • Lyapunov functions were used to establish the existence of a stationary Markov process.
  • Numerical simulations explored the effects of noise intensity and delays.

Main Results:

  • The model solution was proven to be unique, positive, and global.
  • A stationary Markov process exists when a critical condition is met.
  • Small noise sustained virions and CTL response; large noise promoted virus extinction.

Conclusions:

  • Stochastic fluctuations can significantly impact HIV model dynamics, potentially more than delays.
  • Noise intensity is a critical factor in determining viral persistence or extinction.
  • The findings offer insights into managing HIV infection through understanding stochastic effects.

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