Publication: Cellular automata simulation modeling of HIV infection in Lymph Node and peripheral blood compartments
Issued Date
2010-12-01
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ISSN
19980159
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2-s2.0-78650816379
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Mahidol University
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SCOPUS
Bibliographic Citation
International Journal of Mathematics and Computers in Simulation. Vol.4, No.4 (2010), 124-134
Suggested Citation
Sompop Moonchai, Yongwimon Lenbury, Wannapong Triampo Cellular automata simulation modeling of HIV infection in Lymph Node and peripheral blood compartments. International Journal of Mathematics and Computers in Simulation. Vol.4, No.4 (2010), 124-134. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/28992
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Title
Cellular automata simulation modeling of HIV infection in Lymph Node and peripheral blood compartments
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Abstract
Acquired immune deficiency syndrome (AIDS) has been widely considered as the most devastating epidemic. To discover effective therapy for HIV infection, the dynamics of the virus-immune system in the human body have been the subject of intense studies. Since the development of the disease typically exhibits a three phase evolution, that is, an acute phase (measured in days), a chronic phase (measured in weeks) and AIDS (measured in years), the use of ordinary or partial differential equations are inadequate in our attempt to describe the three different time scales in order to simulate the entire course of the HIV infection. Cellular automata simulation approach has become well known as a useful technique to investigate complex biomedical systems in situations where traditional methodologies are difficult or too costly to employ. So far, relatively simple cellular automata models have been proposed to simulate the dynamics of HIV infection in human. Most cellular automata models only considered viral proliferation in the lymph node. However, most clinical indications of AIDS progression are based on blood data, because these data are most easily obtained. Since viral population circulates between lymph node and plasma, viral load in the two compartments are important for the description of HIV infection dynamics. We present here cellular automata simulations of a two-compartment model of HIV proliferation with delay.