References for HIV Dynamics and AIDS Modeling

HIV Dynamics: Classified Major References

Important clinical results on HIV dynamics:

Wei X, Ghosh SK, Taylor ME, et al. Viral dynamics in human immunodeficiency virus type 1 infection. Nature 1995; 373:117-22.

Ho DD, Neumann AU, Perelson AS, et al. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 1995; 373:123-26.

Perelson AS, Neumann AU, Markowitz M, et al. HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science 1996; 271:1582-86.

Perelson AS, Essunger P, Cao Y, et al. Decay characteristics of HIV-1-infected compartments during combination therapy. Nature 1997; 387:188-91.

Notermans DW, Goudsmit J, Danner SA, et al. Rate of HIV-1 decline following antiretroviral therapy is related to viral load at baseline and drug regimen. AIDS 1998 ; 12:1483-90.

Wu, H., Kuritzkes, D.R., and McClernon, D.R. et al. (1999), Characterization of Viral Dynamics in Human Immunodeficiency Virus Type 1-Infected Patients Treated with Combination Antiretroviral Therapy: Relationships to Host Factors, Cellular Restoration and Virological Endpoints, Journal of Infectious Diseases, 179(4):799-807.

Wu, H., Mellors, J., Ruan, P. et al. (2003), Viral Dynamics and Their Relations to Baseline Factors and Longer-Term Virologic Responses in Treatment-Naive HIV-1 Infected Patients Receiving Abacavir in Combination with HIV-1 Protease Inhibitors, JAIDS, 32, 557-564.

Pediatric viral dynamics:

Mueller BU, Zeichner SL Kuznetsov VA et al. Individual prognoses of long-term responses to antiretroviral treatment based on virological, immunological and pharmacological parameters measured during the first week under therapy. AIDS 1998 ; 12:F191-F196.

Luzuriaga, K., Wu, H., and McManus, M. et al. (1999), Dynamics of HIV-1 Replication in Vertically-Infected Infants, Journal of Virology, 73, 362-367.

Wu, H., Lathey, J., Ruan, P., et al. (2004), Relationship of Plasma HIV-1 RNA Dynamics to
Baseline Factors and Virological Responses to Highly Active Antiretroviral Therapy in Adolescents (Aged 12-22 Years) Infected through High-Risk Behavior, Journal of Infectious Diseases, 189, 593-601.

Review of Mathematical Models:

Perelson AS and Nelson PW. Mathematical Analysis of HIV-1 dynamics in vivo. SIAM Review, 1999, 41 (1):3-44.

Tan, W.Y. (2000), Stochastic Modeling of AIDS Epidemiology and HIV Pathogenesis, World Press.

Nowak MA and May RM, Virus Dynamics: Mathematical Principles of Immunology and Virology, Oxford University Press, 2000.

Callaway DS, Perelson AS. HIV-1 infection and low steady state viral loads. Bulletin of mathematical Biology 2002; 64 :29-64.

New viral dynamic models and interpretations:

Wu, H., Ding, A. and DeGruttola, V. (1999), Why are the decay rates in plasma HIV-1 different for different treatments and in different patient populations? AIDS, 13 (3): 429-430.

Ding, A.A. and Wu, H. (1999), Relationships between Antiviral Treatment Effects and Biphasic Viral Decay Rates in Modeling HIV Dynamics, Mathematical Biosciences, 160. 63-82.

Huang, Y., Rosenkranz, S., Wu, H. (2003), Modeling HIV Dynamics and Antiviral Responses with Consideration of Time-Varying Drug Exposures, Sensitivities and Adherence, Mathematical Biosciences, 184, 165-186.

Design of viral dynamic studies:

Marschner IC (1998), Design of HIV Viral Dynamics Studies, Statistics in Medicine, 17, 2421-2434.

Wu, H. (1999), How Frequently Should Viral Load be Monitored to Evaluate Antiretroviral Therapies in AIDS Clinical Trials? Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology, 20, 97-99.

Wu, H. and Ding, A.A. (2000), Design of Viral Dynamic Studies for Efficiently Assessing Anti-HIV Therapies in AIDS Clinical Trials, Biometrical Journal, 2, 175-196.

Han C. Optimal Designs for Nonlinear Regression Models with Applications to HIV Dynamic Studies . PhD Dissertation in Biostatistics, University of Minnesota, Minneapolis, 2002.

Han C, and Chaloner K. D - and c -optimal designs for exponential regression models used in viral dynamics and other applications. Journal of Statistical Planning and Inference 2003; 115 : 585-601.

Han C, and Chaloner K. Bayesian experimental design for nonlinear mixed-effects models with application to HIV dynamics. Biometrics 2004; 60 : 25-33.

Statistical estimation methods of viral dynamic parameters:

Wu, H., Ding, A. and DeGruttola. V. (1998), Estimation of HIV Dynamic Parameters, Statistics in Medicine, 17, 2463-2485.

Wu, H. and Ding, A. (1999),  Population HIV-1 Dynamics in Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials, Biometrics, 55, 410-418.

Wu, H., Ruan, P., Ding, A.A., Sullivan, J.L. and Luzuriaga, K. (1999), Inappropriate Model-Fitting Methods May Lead To Significant Underestimates of Viral Decay Rates in HIV Dynamic Studies, Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology, 21, 426-428.

Ding, A.A. and Wu, H. (2000), A Comparison Study of Models and Fitting Procedures for Biphasic
Viral Dynamics in HIV-1 Infected Patients Treated with Antiviral Therapies, Biometrics, 56, 293-300.

Wu, H. (2004), Statistical Methods for HIV Dynamic Studies in AIDS Clinical Trials, Statistical Methods in Medical Research, in press.

Bayesian approach for parameter estimation:

Frost SDW (2001). Bayesian modeling of viral dynamics and evolution. AIDS Cyber J. (Online), 4(2).
Putter H, Heisterkamp SH, Lange JMA and Wolf F. (2002). A Bayesian approach to parameter estimation in HIV dynamic models. Statistics in Medicine, 21, 2199-2214.

Han C, Chaloner K, Perelson AS. Bayesian analysis of a population HIV dynamic model. Case Studies in Bayesian Statistics, Vol. 6 . Springer-Verlag: New York, 2002.

Huang, Y. and Wu, H. (2004), A Bayesian Approach for Estimating Antiviral Efficacy in HIV Dynamic Models, submitted.

Statistical inference approaches for Viral dynamic parameters:

Ding, A.A. and Wu, H. (2001), Assessing Antiviral Potency of Anti-HIV Therapies in Vivo
by Comparing Viral Decay Rates in Viral Dynamic Models, Biostatistics, 2, 13-29.

Sun, Y. and Wu, H. (2003), AUC-Based Tests for Nonparametric Functions with Longitudinal
Data, Statistica Sinica, 13, 593-612.

Modeling Long-term viral dynamics and cell kinetics:

Wu, H., Zhang, B., and Spritzler, J. (1999), Modeling and Analyzing Cellular Kinetics for HIV-infected Patients Treated with Potent Antiviral Therapies in AIDS Clinical Trials, ASA 1999 Proceedings of the Biometrics Section, 123-128.

Wu, H., Connick E., Kuritzkes, D.R. et al. (2001), Multiple CD4+ Cell Kinetic Patterns and Their Relationships with Baseline Factors and Virologic Responses in HIV-1 Patients Receiving HAART, AIDS Research and Human Retroviruses, 17(13), 1237-1246.

Wu, H. and Zhang, J.T. (2002), The Study of Long-Term HIV Dynamics Using Semiparametric Nonlinear Mixed-Effects Models, Statistics in Medicine, 21, 3655-3675.

Liang, H., Wu, H., and Carroll, R.J. (2003), The Relationship Between Virologic and Immunologic Responses in AIDS Clinical Research Using Mixed-Effects Varying-Coefficient Semiparametric Models with Measurement Error, Biostatistics, 4, 297-312.

Huang, Y., Rosenkranz, S., Wu, H. (2003), Modeling HIV Dynamics and Antiviral Responses with Consideration of Time-Varying Drug Exposures, Sensitivities and Adherence, Mathematical Biosciences, 184, 165-186.

Wu, H. and Liang, H. (2003), Random Varying-Coefficient Models with Smoothing Covariates, Applications to an AIDS Clinical Study, Scan. J. Statist., in press.

Wu, H., Zhao, C. and Liang, H. (2004), Comparison of Linear, Nonlinear and Semiparametric Models for Estimating HIV Dynamic Parameters, Biometrical Journal, in press.

Control theory and HIV/AIDS research:

Adams BM, Banks HT, Davidian M et al. HIV dynamics: Modeling, data analysis, and optimal treatment protocols. preprint.

Alvarez-Ramirez J, Meraz M and Velasco-Hermandez JX. Feedback control of the chemotherapy of HIV. International Journal of Bifurcation and Chaos, 2000, 10:2207-2219.

Brandt ME and Chen B. Feedback Control of biodynamical model of  HIV-1. IEEE Trans. on Biom. Engr. 2001, 48: 754-759

Butler S, Kirschner D and Lenhart S. Optimal control of the  chemotherapy affecting the infectivity of HIV. Advances in Mathematical Population Dynamics---Molecules, Cells and Man, Editors: O. Arino, D. Axelrod and M. Kimmel, World Scientific Press, Singapore, 1997, 557-569.

de Souza JAMF, Caetano MAL and Yoneyama T. Optimal control theory applied to the anti-viral treatment of AIDS. Proc. IEEE Conference on Decision and Control, Sydney, Australia, 2000.

Fister KR, Lenhart S and McNally JS. Optimizing chemotherapy in an HIV model, Electr. J. of Diff. Eq. 1998, 32:1-12.

Jeffrey M, Xia X and Craig IK. Controllability analysis of the chemotherapy of HIV. 15th IFAC World Congress, Barcelona, Spain, July 21-26, 2002.

Jeffrey M, Xia X and Craig IK. When to initiate HIV therapy: A control theoretic approach. IEEE Trans. BME 2003a, 50:1213-1220.

Jeffrey M, Xia X and Craig IK. On attaining maximal and durable suppression of the viral load. 1st African Control Conference AFCON 2003b, Cape Town, South Africa.

Joshi HR. Optimal control of an HIV immunology model. Optim. Contr. Appl. Math 2002, 23:199-213.
Kirschner D, Lenhart S and Serbin S. Optimal control of the chemotherapy of HIV. J. Math. Biol. 1997, 35:775-792.

Wein LM, Zenios SA and Nowak MA. Dynamic multidrug therapies for HIV: A control theoretic approach. J. Theor. Biol. 1997, 185: 15-29.

Xia X. Estimation of HIV/AIDS parameters. Automatica 2003, 39:1983-1988.

Xia X and Moog CH. Identifiability of nonlinear systems with application to HIV/AIDS modes. IEEE Tran. Auto. Cont. 2003, 48: 330-336.

Identification of host factors and covariates for viral dynamic parameters:

Wu, H. and Wu, L. (2000), Identification of Significant Host Factors for HIV Dynamics Modeled by Nonlinear Mixed-Effect Models, Statistics in Medicine, 21, 753-771.

Wu, H. and Wu, L. (2001), A Multiple Imputation Method for Missing Covariates in Nonlinear
Mixed-effect Models, with Application to HIV Dynamics, Statistics in Medicine, 20 (12), 1755-1769.

Wu, H. and Wu, L. (2000), Identification of Significant Host Factors for HIV Dynamics Modeled by Nonlinear Mixed-Effect Models, Statistics in Medicine, 21, 753-771.

Wu, L. and Wu, H. (2002), Nonlinear Mixed-Effect Models with Missing Time-Dependent Covariates, with Application to HIV Viral Dynamics, Journal of the Royal Statistical Society, Series C (Applied Statistics), 51, 297-318.

Relationship between viral dynamics and long-term response:

Mueller B.U., Zeichner S.L. Kuznetsov V.A. et al. (1998), Individual prognoses of long-term responses to antiretroviral treatment based on virological, immunological and pharmacological parameters measured during the first week under therapy, AIDS, 12: F191-F196.

Mittler, J. Essunger, P., Yuen, G.J. et al. (2001), Short-term measures of relative efficacy predict longer-term reductions in Human Immunodeficiency Virus Type 1 RNA levels following nelfinavir monotherapy, Antimicrobial Agents and Chemotherapy, 45: 1438-1443.

Polis MA, Sidorov IA, Yoder C et al. Correlation between reduction in plasma HIV-1 RNA concentration 1 week after start of antiretroviral treatment and longer-term efficacy. The Lancet, 2001 ; 358:1760-65.

HIV Dynamics: Introductory References for Students and New Researchers

Important clinical results on HIV dynamics:

Ho DD, Neumann AU, Perelson AS, et al. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 1995; 373:123-26.

Perelson AS, Neumann AU, Markowitz M, et al. HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science 1996; 271:1582-86.

Perelson AS, Essunger P, Cao Y, et al., Decay characteristics of HIV-1-infected compartments during combination therapy. Nature 1997; 387:188-91.

Wu, H., Kuritzkes, D.R., and McClernon, D.R. et al. (1999), Characterization of Viral Dynamics in Human Immunodeficiency Virus Type 1-Infected Patients Treated with Combination Antiretroviral Therapy: Relationships to Host Factors, Cellular Restoration and Virological Endpoints, Journal of Infectious Diseases, 179(4):799-807.

Review Paper and Book of Mathematical Models:

Perelson AS and Nelson PW. Mathematical Analysis of HIV-1 dynamics in vivo. SIAM Review, 1999, 41 (1):3-44.

Callaway DS, Perelson AS. HIV-1 infection and low steady state viral loads. Bulletin of mathematical Biology 2002; 64 :29-64.

Nowak MA and May RM, Virus Dynamics: Mathematical Principles of Immunology and Virology, Oxford University Press, 2000.

Statistical estimation methods of viral dynamic parameters:

Wu, H., Ding, A. and DeGruttola. V. (1998), Estimation of HIV Dynamic Parameters, Statistics in Medicine, 17, 2463-2485.

Wu, H. and Ding, A. (1999),  Population HIV-1 Dynamics in Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials, Biometrics, 55, 410-418.

Putter H, Heisterkamp SH, Lange JMA and Wolf F. (2002). A Bayesian approach to parameter estimation in HIV dynamic models. Statistics in Medicine, 21, 2199-2214.

Han C, Chaloner K, Perelson AS. Bayesian analysis of a population HIV dynamic model. Case Studies in Bayesian Statistics, Vol. 6 . Springer-Verlag: New York, 2002.

Wu, H. (2004), Statistical Methods for HIV Dynamic Studies in AIDS Clinical Trials, Statistical Methods in Medical Research, in press.