We use a cellular automata model to study the evolution of human immunodeficiency virus (HIV)
infection and the onset of acquired innumodeficiency syndrome (AIDS). The model takes into account
the global features of the immune response to any pathogen, the fast mutation rate of the HIV, and a fair
amount of spatial localization, which may occur in the lymph nodes. Our results reproduce the three-
phase pattern observed in T cell and virus counts of infected patients, namely, the primary response, the
clinical latency period, and the onset of AIDS. The dynamics of real experimental data is related to the
transient behavior of our model and not to its steady state. We have also found that the infected cells
organize themselves into spatial structures, which are responsible for the decrease on the concentration
of uninfected cells, leading to AIDS.
%0 Journal Article
%1 zorzenondossantos2001dynamics
%A Zorzenon dos Santos, Rita Maria
%A Coutinho, Sérgio
%D 2001
%I American Physical Society
%J Phys. Rev. Lett.
%K HIV cellular_automata modeling
%N 16
%P 168102
%R 10.1103/PhysRevLett.87.168102
%T Dynamics of HIV Infection: A Cellular Automata Approach
%U http://link.aps.org/doi/10.1103/PhysRevLett.87.168102
%V 87
%X We use a cellular automata model to study the evolution of human immunodeficiency virus (HIV)
infection and the onset of acquired innumodeficiency syndrome (AIDS). The model takes into account
the global features of the immune response to any pathogen, the fast mutation rate of the HIV, and a fair
amount of spatial localization, which may occur in the lymph nodes. Our results reproduce the three-
phase pattern observed in T cell and virus counts of infected patients, namely, the primary response, the
clinical latency period, and the onset of AIDS. The dynamics of real experimental data is related to the
transient behavior of our model and not to its steady state. We have also found that the infected cells
organize themselves into spatial structures, which are responsible for the decrease on the concentration
of uninfected cells, leading to AIDS.
@article{zorzenondossantos2001dynamics,
abstract = {We use a cellular automata model to study the evolution of human immunodeficiency virus (HIV)
infection and the onset of acquired innumodeficiency syndrome (AIDS). The model takes into account
the global features of the immune response to any pathogen, the fast mutation rate of the HIV, and a fair
amount of spatial localization, which may occur in the lymph nodes. Our results reproduce the three-
phase pattern observed in T cell and virus counts of infected patients, namely, the primary response, the
clinical latency period, and the onset of AIDS. The dynamics of real experimental data is related to the
transient behavior of our model and not to its steady state. We have also found that the infected cells
organize themselves into spatial structures, which are responsible for the decrease on the concentration
of uninfected cells, leading to AIDS.},
added-at = {2014-05-28T14:45:44.000+0200},
author = {Zorzenon dos Santos, Rita Maria and Coutinho, S\'ergio},
biburl = {https://www.bibsonomy.org/bibtex/2d932de400251b9f37aaff381b8f1a98b/peter.ralph},
doi = {10.1103/PhysRevLett.87.168102},
interhash = {e1cb223f3e45b40d2713d6dc9b7d23c6},
intrahash = {d932de400251b9f37aaff381b8f1a98b},
journal = {Phys. Rev. Lett.},
keywords = {HIV cellular_automata modeling},
month = sep,
number = 16,
numpages = {4},
pages = 168102,
publisher = {American Physical Society},
timestamp = {2014-05-28T14:45:44.000+0200},
title = {Dynamics of {HIV} Infection: A Cellular Automata Approach},
url = {http://link.aps.org/doi/10.1103/PhysRevLett.87.168102},
volume = 87,
year = 2001
}