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Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach

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  • González, Ramón E.R.
  • Coutinho, Sérgio
  • Zorzenon dos Santos, Rita Maria
  • de Figueirêdo, Pedro Hugo

Abstract

The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.

Suggested Citation

  • González, Ramón E.R. & Coutinho, Sérgio & Zorzenon dos Santos, Rita Maria & de Figueirêdo, Pedro Hugo, 2013. "Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4701-4716.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:19:p:4701-4716
    DOI: 10.1016/j.physa.2013.05.056
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    References listed on IDEAS

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    Cited by:

    1. M., Pitchaimani & M., Brasanna Devi, 2020. "Random effects in HIV infection model at Eclipse stage," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    2. Hillmann, Andreas & Crane, Martin & Ruskin, Heather J., 2017. "HIV models for treatment interruption: Adaptation and comparison," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 44-56.
    3. González, Ramón E.R. & Figueirêdo, P.H. & Coutinho, S., 2020. "Dynamics of HIV Infection: An entropic–energetic view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    4. Burkhead, Emily & Hawkins, Jane, 2015. "A cellular automata model of Ebola virus dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 424-435.
    5. Akdim, Khadija & Ez-zetouni, Adil & Danane, Jaouad & Allali, Karam, 2020. "Stochastic viral infection model with lytic and nonlytic immune responses driven by Lévy noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).

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