mathematical analysis of the hiv-1 infection : parameter estimation, therapies effectiveness and therapeutical failures

Ouattara, Djomangan Adama

doi:10.1109/iembs.2005.1616541

Cited by 22 publications

(23 citation statements)

References 9 publications

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“…Days -1 . This range is consistent with previous studies on HAART [14]. The mean life a of infected CD4 + T cells was 0.44 days -1 ( t 1/2 = 1.6 days), in good agreement with previous evaluations [1][2][3][14][15][16].…”

Section: Resultssupporting

confidence: 91%

“…For instance, in a study on HAART treated patients, d was quantified in the range 10 -3 -10 -2 days -1 [14]. The parameter , that represents the rate of infection of CD4 + T cells, was 2.03 .…”

Section: Resultsmentioning

confidence: 99%

“…Parameters of the first class were initialized at the established values =0.01 μl 1 days -1 [13] and d =0.01 days -1 , so that /d =1 μl 1 and a =0.5 days -1 [1,2]. The parameter u was fixed to 3 days -1 , due the general agreement on this value [1][2][3][14][15][16]. As for treatmentspecific parameters, we determined suitable ranges for and k by heuristic reconstruction of the profile of 2 as a function of these variables (see Fig.…”

Section: Methodsmentioning

confidence: 99%

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Evaluation of HIV-1 and CD4+ T Cell Dynamic Parameters in Patients Treated with Genotypic Resistance Testing-Guided HAART

Cappuccio¹,

Castiglione²,

Piccoli³

et al. 2008

CHR

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The extent of immune restoration in HIV-1 patients on antiretroviral therapy is an important marker of disease progression. In this work, we investigate the dynamics of immune reconstitution and address the question of whether the early response to antiretroviral treatments allows to predict the late immune restoration. We select a cohort of twelve patients on GRT-HAART who achieve virological suppression, but show variable recovery of immune competence. HIV-RNA and CD4+ T cell assessments are used for estimation of the dynamic parameters of an established mathematical model of the viral-immune system interactions. We find that failure in immune reconstitution is associated with an abnormal increase of the death rate of uninfected CD4+ T cells. In contrast, their production rate is up to three times higher than in healthy seronegative individuals. This finding is in line with the view of chronic activation as a major cause of immune depletion. According to non parametric statistics, CD4+ T cell responders and non responders do not show significantly different dynamic parameters. Such result suggests that the employed model does not allow to predict the long term immune reconstitution.

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Section: Resultssupporting

confidence: 91%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of HIV-1 and CD4+ T Cell Dynamic Parameters in Patients Treated with Genotypic Resistance Testing-Guided HAART

Cappuccio¹,

Castiglione²,

Piccoli³

et al. 2008

CHR

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“…A new estimation method was introduced in ref. [21]. It is based on a Monte-Carlo approach which is heuristic and relies also on the simplex optimization algorithm.…”

Section: Parameter Identificationmentioning

confidence: 99%

Control of the HIV infection and drug dosage

Mhawej

Moog

Biafore

et al. 2010

Biomedical Signal Processing and Control

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“…In that study, demonstrated was the CD4 + T cells measurement and viral load count, using reverse transcriptase inhibitor (RTI) as single treatment. Other notable models involving discretization methods for parameter estimations could be found in [6] [9] [10]. The deployment of highly antiretroviral therapy (HAART) regimen in the treatment and suppression of viral replication and immune system recovery were studied by [5] [11] [12].…”

Section: Introductionmentioning

confidence: 99%

On Analysis of Parameter Estimation Model for the Treatment of Pathogen-Induced HIV Infectivity

Bassey¹,

Andreyevich²

2016

OALib

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Multiplicity of new cases of HIV/AIDS and its allied infectious diseases daunted by lack of proper parametric estimation necessitated this present work. Formulated using ordinary differential equation was a five-dimensional (5D) differential mathematical model with which compatibility of optimal control strategy for dual (viral load and parasitoid-pathogen) infectivity in the blood plasma was investigated. Discretization method indicated the incompatibility of the model due to large error derivatives. The study using numerical method established treatment set point with which we explored the variation of predominant model parameters and thereof investigated the maximization of uninfected healthy CD4 + T cell count as well as the de-replication of viruses following the consistent administration of reverse transcriptase inhibitor from set point. Presented was a series of numerical calculations obtained using well-known Runge-Kutter of order of precision 4, in Mathcad platform. Analysis of simulated parameters showed that distortion of replication viruses and de-transmutation of susceptible CD4 + T cells by viruses via chemotherapy led to restoration and gradual increase of healthy blood plasma, with near zero declination of both viral load and parasitoid-pathogen within chemotherapy validity time frame. The model was worthy in the study of treatment analysis of dual HIV-pathogen infection and thereof recommended for other related dual infectious diseases.

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mathematical analysis of the hiv-1 infection : parameter estimation, therapies effectiveness and therapeutical failures

Abstract: This paper presents a method to estimate accurately the parameters involved in the HIV-1 infection. An application to the evaluation of the drugs effectiveness and therapeutical failures is presented.

Cited by 22 publications

References 9 publications

Evaluation of HIV-1 and CD4+ T Cell Dynamic Parameters in Patients Treated with Genotypic Resistance Testing-Guided HAART

Evaluation of HIV-1 and CD4+ T Cell Dynamic Parameters in Patients Treated with Genotypic Resistance Testing-Guided HAART

Control of the HIV infection and drug dosage

On Analysis of Parameter Estimation Model for the Treatment of Pathogen-Induced HIV Infectivity

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