Short-Term Antiretroviral Treatment Recommendations Based on Sensitivity Analysis of a Mathematical Model for HIV Infection of CD4+T Cells

[1]  Abba B. Gumel,et al.  Mathematical assessment of the role of pre-exposure prophylaxis on HIV transmission dynamics , 2017, Appl. Math. Comput..

[2]  Vivek A. Kumar,et al.  Development of peptide inhibitors of HIV transmission , 2016, Bioactive materials.

[3]  P. Cahn,et al.  Clinical challenges in HIV/AIDS: Hints for advancing prevention and patient management strategies. , 2016, Advanced drug delivery reviews.

[4]  J. Levy.  Dispelling myths and focusing on notable concepts in HIV pathogenesis. , 2015, Trends in molecular medicine.

[5]  Jianhong Wu,et al.  An optimal strategy for HIV multitherapy , 2014, J. Comput. Appl. Math..

[6]  Ş. Yüzbaşı.  A numerical approach to solve the model for HIV infection of CD4+T cells , 2012 .

[7]  Jeehyun Lee,et al.  Optimal control of an age-structured model of HIV infection , 2012, Appl. Math. Comput..

[8]  José Marie Orellana,et al.  Optimal drug scheduling for HIV therapy efficiency improvement , 2011, Biomed. Signal Process. Control..

[9]  Ahmet Yildirim,et al.  On the numerical solution of the model for HIV infection of CD4+ T cells , 2011, Comput. Math. Appl..

[10]  Nilay Shah,et al.  The identification of model effective dimensions using global sensitivity analysis , 2011, Reliab. Eng. Syst. Saf..

[11]  Jeehyun Lee,et al.  Free Terminal Time Optimal Control Problem of an HIV Model Based on a Conjugate Gradient Method , 2011, Bulletin of mathematical biology.

[12]  Christopher J. Roy,et al.  Verification and Validation in Scientific Computing , 2010 .

[13]  D. Ian Wilson,et al.  Planning of patient-specific drug-specific optimal HIV treatment strategies , 2009 .

[14]  To Oluyo,et al.  Mathematical analysis of the global dynamics of a model for HIV infection of CD4 + T cells , 2008 .

[15]  Robert F Stengel,et al.  Mutation and Control of the Human Immunodeficiency Virus , 2022 .

[16]  Dominik Wodarz,et al.  Infection dynamics in HIV-specific CD4 T cells: does a CD4 T cell boost benefit the host or the virus? , 2007, Mathematical biosciences.

[17]  D M Bortz,et al.  Model Selection and Mixed-Effects Modeling of HIV Infection Dynamics , 2006, Bulletin of mathematical biology.

[18]  Mostafa Rachik,et al.  Optimal control and infectiology: Application to an HIV/AIDS model , 2006, Appl. Math. Comput..

[19]  A. Owen,et al.  Estimating Mean Dimensionality of Analysis of Variance Decompositions , 2006 .

[20]  B. Adams,et al.  HIV dynamics: Modeling, data analysis, and optimal treatment protocols , 2005 .

[21]  V. Guinot,et al.  Treatment of precipitation uncertainty in rainfall-runoff modelling: a fuzzy set approach , 2004 .

[22]  Ruy M Ribeiro,et al.  Modeling the long-term control of viremia in HIV-1 infected patients treated with antiretroviral therapy. , 2004, Mathematical biosciences.

[23]  Niranjala C Perera,et al.  Deterministic and stochastic models of virus dynamics , 2003 .

[24]  Christine Hogan,et al.  Determining the antiviral activity of tenofovir disoproxil fumarate in treatment-naive chronically HIV-1-infected individuals , 2003, AIDS.

[25]  Hem Raj Joshi,et al.  Optimal control of an HIV immunology model , 2002 .

[26]  A. Saltelli,et al.  Making best use of model evaluations to compute sensitivity indices , 2002 .

[27]  C. Mahé,et al.  HIV-1 infection in rural Africa: is there a difference in median time to AIDS and survival compared with that in industrialized countries? , 2002, AIDS.

[28]  I. Sobola,et al.  Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates , 2001 .

[29]  Ivan Kramer,et al.  Modeling the dynamical impact of HIV on the immune system: Viral clearance, infection, and AIDS , 1999 .

[30]  Alan S. Perelson,et al.  Mathematical Analysis of HIV-1 Dynamics in Vivo , 1999, SIAM Rev..

[31]  V. Gruttola,et al.  Why are the decay rates in plasma HIV-1 different for different treatments and in different patient populations? , 1999, AIDS.

[32]  J. Montaner,et al.  A randomized, double-blind trial comparing combinations of nevirapine, didanosine, and zidovudine for HIV-infected patients: the INCAS Trial. Italy, The Netherlands, Canada and Australia Study. , 1998, JAMA.

[33]  A. Saltelli,et al.  An alternative way to compute Fourier amplitude sensitivity test (FAST) , 1998 .

[34]  E A Emini,et al.  Treatment with indinavir, zidovudine, and lamivudine in adults with human immunodeficiency virus infection and prior antiretroviral therapy. , 1997, The New England journal of medicine.

[35]  D. Kirschner,et al.  Optimal control of the chemotherapy of HIV , 1997, Journal of mathematical biology.

[36]  K. Kim.  CD4+T Cells , 1993 .

[37]  A. Perelson,et al.  Dynamics of HIV infection of CD4+ T cells. , 1993, Mathematical biosciences.

[38]  C. Fortuin,et al.  Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory , 1973 .

[39]  A. Croicu.  Short- and Long-Term Optimal Control of a Mathematical Model for HIV Infection of C D 4 + T Cells , 2015 .

[40]  Jennifer F Hoy,et al.  Antiretroviral treatment of adult HIV infection: 2014 recommendations of the International Antiviral Society-USA Panel. , 2014, JAMA.

[41]  Yaning Liu,et al.  Non-intrusive methods for probabilistic uncertainty quantification and global sensitivity analysis in nonlinear stochastic phenomena , 2013 .

[42]  Shigui Ruan,et al.  Mathematical Biology Digital Object Identifier (DOI): , 2000 .