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dc.creatorMbogo, Rachel Waema
dc.creatorLuboobi, Livingstone S.
dc.creatorOdhiambo, John W.
dc.date04/26/2013
dc.dateFri, 26 Apr 2013
dc.dateThu, 9 May 2013 11:01:24
dc.dateMonth: 4 Day: 2 Year: 2013
dc.dateThu, 9 May 2013 11:01:24
dc.date.accessioned2015-03-18T11:28:56Z
dc.date.available2015-03-18T11:28:56Z
dc.identifier1314-0744
dc.identifier
dc.identifier.urihttp://hdl.handle.net/11071/3525
dc.descriptionPublished by International Electronic Journal of Pure and Applied Mathematics Volume 6 No. 2 2013, 83-103
dc.descriptionMathematical models are used to provide insights into the mechanisms and dynamics of the progression of viral infection in vivo. Untangling the dynamics between HIV and CD4+ cellular populations and molecular interactions can be used to investigate the effective points of interventions in the HIV life cycle. With that in mind, we develop and analyze a stochastic model for In-Host HIV dynamics that includes combined therapeutic treatment and intracellular delay between the infection of a cell and the emission of viral particles. The unique feature is that both therapy and the intracellular delay are incorporated into the model. We show the usefulness of our stochastic approach towards modeling combined HIV treatment by obtaining probability generating function, the moment structures of the healthy CD4+ cell, and the virus particles at any time t and the probability of virus clearance. Our analysis show that, when it is assumed that the drug is not completely effective, as is the case of HIV in vivo, the predicted rate of decline in plasma HIV virus concentration depends on three factors: the initial viral load before therapeutic intervention, the efficacy of therapy and the length of the intracellular delay.
dc.description.abstractMathematical models are used to provide insights into the mechanisms and dynamics of the progression of viral infection in vivo. Untangling the dynamics between HIV and CD4+ cellular populations and molecular interactions can be used to investigate the effective points of interventions in the HIV life cycle. With that in mind, we develop and analyze a stochastic model for In-Host HIV dynamics that includes combined therapeutic treatment and intracellular delay between the infection of a cell and the emission of viral particles. The unique feature is that both therapy and the intracellular delay are incorporated into the model. We show the usefulness of our stochastic approach towards modeling combined HIV treatment by obtaining probability generating function, the moment structures of the healthy CD4+ cell, and the virus particles at any time t and the probability of virus clearance. Our analysis show that, when it is assumed that the drug is not completely effective, as is the case of HIV in vivo, the predicted rate of decline in plasma HIV virus concentration depends on three factors: the initial viral load before therapeutic intervention, the efficacy of therapy and the length of the intracellular delay.
dc.formatVolumes:2
dc.formatNumber of Pages:23p.
dc.languageeng
dc.publisherIJAPM
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dc.subjectintracellular delay
dc.subjecttherapeutic intervention
dc.subjectCD4+ T-cells
dc.subjectHIV dynamics
dc.subjectstochastic model
dc.titleMathematical model for HIV and CD4+ cells dynamics in vivo
dc.typeArticle


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