IJMSC Vol. 6, No. 2, 8 Apr. 2020
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HIV-HBV-infectivity, time-delay-lag, triple-dual-control-functions, double-lymphocyte, systemic-cost, monolytic-infection, lentivirus, triphasic-maximization
It has been of concern for the most appropriate control mechanism associated with the growing complexity of dual HIV-HBV infectivity. Moreso, the scientific ineptitude towards an articulated mathematical model for co-infection dynamics and accompanying methodological application of desired chemotherapies inform this present investigation. Therefore, the uniqueness of this present study is not only ascribed by the quantitative maximization of susceptible state components but opined to an insight into the epidemiological identifiability of dual HIV-HBV infection transmission routes and the methodological application of triple-dual control functions. Using ODEs, the model was formulated as a penultimate 7-Dimensional mathematical dynamic HIV-HBV model, which was then transformed to an optimal control problem, following the introduction of multi-therapies in the presence of dual adaptive immune system and time delay lags. Applying classical Pontryagin’s maximum principle, the system was analyzed, leading to the derivation of the model optimality system and uniqueness of the system. Specifically, following the dual role of the adaptive immune system, which culminated into triple-dual application of multi-therapies, the investigation was characterized by dual delayed HIV-HBV virions decays from infected double-lymphocytes in a biphasic manner, accompanied by more complex decay profiles of infectious dual HIV-HBV virions. The result further led to significant triphasic maximization of susceptible double-lymphocytes and dual adaptive immune system (cytotoxic T-lymphocytes and humeral immune response) achieved under minimal systemic cost. Therefore, the model is comparatively a monumental and intellectual accomplishment, worthy of emulation for related and future dual infectivity.
Bassey, B. Echeng, " Optimal Control Dynamics: Multi-therapies with Dual Immune Response for Treatment of Dual Delayed HIV-HBV Infections", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.6, No.2, pp.18-60, 2020. DOI: 10.5815/ijmsc.2020.02.02
[1]Bassey E. B. (2018) Dynamic optimal control model for dual-pair treatment functions of dual delayed HIV-pathogen infections. Journal of Mathematical Sciences: Advances and Applications, 51(1): 1-50.
[2]Allali K., Meskaf A. and Tridane A. (2018) Mathematical modeling of the adaptive immune responses in the early stage of the HBV infection. International Journal of Differential Equations, 2018(1): 1-13.
[3]Hattaf K. and Yousfi N. (2018) Modeling the adaptive immunity and both modes of transmission in HIV infection. Computation, 6(37): 1-18.
[4]Kirschner, D. (1999) Dynamics of Co-infection with M. Tuberculosis and HIV-1. Theoretical Population Biology, 55, 94-109.
[5]Bassey, B. E. and Lebedev, K. A. (2015) On Mathematical Modeling of the Effect of Bi-Therapeutical Treatment of Tuberculosis Epidemic. Journal of Mathematics and Statistics, 9(1-4), 1-7.
[6]Ferrari C. (2015) HBV and the immune response. Liver International, 35(1): 121–128.
[7]Rehermann B. and Nascimbeni M. (2005) Immunology of hepatitis B virus and hepatitis C virus infection. Nature Reviews Immunology, 5(3): 215–229.
[8]Waters J., Pignatelli M., Galpin S., Ishihara K., and Thomas H. C. (1986) Virus-neutralizing antibodies to hepatitis B virus: The nature of an immunogenic epitope on the S gene peptide. Journal of General Virology, 67(11): 2467–2473.
[9]Hagiwara S., Nishida N., and Kudo M. (2015) Antiviral therapy for chronic hepatitis B: Combination of nucleoside analogs and interferon. World Journal of Hepatolog y, 7(23): 2427–2431.
[10]Atteena P. K. Bultery M., Hu D. J. nad Jamieson D. J. (2012) HIV-HBV co-infection – A global challenge. N. Engl J. Med., 366(19): 1749-1752.
[11]Hoffman C. J. and Thio C. L. (2007) Clinical implications of HIV and Hepatitis B co-infection in Asia and Africa. Lancet Infect Dis., 7, 402-409. [PubMed:17521593]
[12]Nasal M. (2015) HBV cccDNA: Viral persistence reservoir and key obstacle for a cure of chronic hepatitis B. Gut, 64, 1972-1984.
[13]WHO (2017) HIV/AIDS, Facts sheet, July, 2017. Retrieved date: [26, November, 2018], online available at http://www.who.int/mediacentre/factsheets/fs360/en/
[14]Alavian S. M. (2010) Hepatitis B virus infection in Iran: Changing the epidemiology. Iran J clin infect Dis., 5, 51-61.
[15]Zhu H. and Zou X. (2009) Dynamics of a HIV-1 infection model with cell-mediated immune response and intracellular delay. Discrete and continuous dynamical systems, series B, 12(2): 511–524.
[16]Culshaw, R., Ruan, S. and Spiteri, R. J. (2004) Optimal HIV Treatment by Maximizing Immune Response. Journal of Mathematical Biology, 48, 5, 545-562.
[17]Webster G. J. M., Reignat S., Miani M. K., etal. (2000) Incubation phase of acute hepatitis B in man: Dynamics of cellular immune mechanisms. Hepatology, 32(5): 1117-1124.
[18]World Health Organization (2018) Progress towards access to hepatitis B treatment worldwide. WHO Website. Retrieved date: [27, November, 2018], online available at http://www.who.int/hepatitis/news-events/cdc-hepatitis-b-article/en/
[19]Lavanchy D. (2004) Hepatitis B virus epidemiology, disease burden, treatment and current emerging prevention and control measures. J. Viral Hepat., 11, 97-107. [CrossRef][PubMed]
[20]Dontwi I. K., Frempong N. K. nad Wiah E. N. (2010) Using mathematical model to depict the immune respovse to Hepatitis B virus infection. American Journal of Sc. & Ind. Res., 1(3): 516-528.
[21]Van Steenbergen J. E., Niesters H.G., Op de Coul E.L., Van Doornum G. J., Osterhaus A. D., Leentvaar-Kuijpers A., Coutinho R. A., Van den Hoek J. A.(2002) Molecular epidemiology of hepatitis B virus in Amsterdam 1992-1997. J Med Virol., 66, 159-65.
[22]Fisker N., Pedersen C., Lange M., Nguyen N.T., Nguyen K.T., Georgsen J.and Christensen P. B. (2004) Molecular epidemiology of hepatitis B virus infections in Denmark. J Clin Virol., 31, 46-52.
[23]Hauri A.M., Armstrong G. L, Hutin Y.J. (2004) The global burden of disease attributable to contaminated injections given in health care settings. Int J STD AIDS, 15, 7-16.
[24]Ataei B., Tayeri K., Kassaeian N., Farajzadegan Z., Babak A. (2010) Hepatitis B and C among Patients Infected with Human Immunodeficiency Virus in Isfahan, Iran: Sero-prevalence and Associated Factors. Hepat Mon, 10, 188-92.
[25]WHO. (2015) Hepatitis B. Fact sheet no. 204, Updated March, 2015. Retrieved date: [26, November, 2018], online available at https://www.who.int/news-room/fact-sheets/detail/hepatitis-b
[26]Tsui J. I., French A. L., etal. (2007) Prevalence and long-trem effects of occult hepatitis B virus infection in HIV-infected women. Clin Infect Dis, 45, 736-40.
[27]Yousfi N., Hattaf K. and Tridane, A. (2011) Modeling the adaptive immune response in HBV infection. J. Math. Biol., 63, 933–957. [CrossRef] [PubMed]
[28]Manna K. and Chakrabarty S. P. (2018) Combination therapy of pegylated interferon and lamivudine and optimal controls for chronic hepatitis B infection. Int. J. Dynam. Control, 354-368. [CrossRef]
[29]Bassey E. (2017) On Optimal Control Pair Treatment: Clinical Management of Viremia Levels In Pathogenic-Induced HIV-1 Infections. Biomed J Sci & Tech Res., 1(2) BJSTR. MS.ID.000204, 1-9. http://biomedres.us/pdfs/BJSTR.MS.ID.000204.pdf
[30]Sherman M. (2009) Strategies for managing co-infection with hepatitis B virus and HIV. Cleve Clin J Med, 76, S30-3. [19465707] [http://dx.doi.org/10.3949/ccjm.76.s3.07]
[31]Iser D. M., Sasadeusz J. J. (2008) Current treatment of HIV/hepatitis B virus co-infection. J Gastroenterol Hepatol, 23:699-706. [18410604] [http://dx.doi.org/10.1111/j.1440-1746.2008.05382.x]
[32]Nowak M. A., Bonhoeffer S., Hill A. M., Boehme R., Thomas H. C. and Mcdade H. (1996) Viral dynamics in hepatitis B virus infection,” Proceedings of the National Acadamy of Sciences of the United States of America, 93(9): 4398–4402.
[33]Wang, K. and Wang, W. (2007) Propagation of HBV with spatial dependence. Math. Biosci. 210, 78–95. [CrossRef] [PubMed]
[34]Zheng Y., Min L., Ji Y., Su Y., Kuang Y. (2010) Global stability of endemic equilibrium point of basic virus infection model with application to HBV infection. J. Syst. Sci. Complex, 23, 1221–1230. [CrossRef]
[35]Li J., Wang K. and Yang Y. (2011) Dynamical behaviors of an HBV infection model with logistic hepatocyte growth. Math. Comput. Model, 54, 704–711. [CrossRef]
[36]Bassey B. E. and Lebedev K. A.(2015) On mathematical model of the impact of verimia levels and condom use: preventive measures for the spread of HIV/AIDS// Materials of the XVIII-th International scientific-practical conference "modern science: Actual problems and ways of their solution" (Russian Federation, Lipetsk, July 20, 2015). – Ed. M. J. Levin. – Lipetsk: "maximum information technology", 2015. – 160с. /47-56 стр. http://elibrary.ru/author_items.asp?authorid=801157
[37]Ouattara D. A. (2005) Mathematical Analysis of the HIV-1 Infection: Parameter Estimation, Therapies Effectiveness and Therapeutical Failures. Proceedings of the 2005 IEEE, Engineering in Medicine and Biology 27th Annual Conference, Shanghai, 1-4 September 2005, 821-824.
[38]Gumel A. B., Zhang X., Shirakumar P. N., Garba M. L. nad Sahai B. M. (2002) A new mathematical model for accessing therapeutic strategies for HIV infection. Journal of Theoretical Medicine, 4(20: 147-155.
[39]Bassey B. E. and Lebedev K. A. (2015) On mathematical modeling of the impact of numerical stability of the treatment of vertical transmitted HIV/AIDS infections//Proceedings of the XVI-th international scientific conference "scientific potential with time-Russia (Russian Federation, Lipetsk, August 10, 2015.)/ Ed. by M. J. Levin. – Lipetsk: "maximum information technology", №5(13): 7-19.
http://elibrary.ru/author_items.asp?authorid=801157
[40]Srivastava V. K., Awasthi M. K. and Kumar S. (2004) Numerical approximation for HIV infection of CD4+ T cells mathematical model. Ain Shams Engineering Journal, 5, 625-629.
[41]Hattaf K., Tridane A. and Yousfi N. (2017) A review of mathematical modeling of Hepatitis B and immune response. 9th Pan African Congress of Mathematicians 2017: Symposium, PACOM2017, 1-1.
[42]Danane J. and Allali K. (2018) Mathematical Analysis and Treatment for a Delayed Hepatitis B Viral Infection Model with the Adaptive Immune Response and DNA-Containing Capsids. High-Throughput, 7(35): 1-16.
[43]Jiang C. and Wang W. (2014) Complete classification of global dynamics of a virus model with immune responses. Discret. Contin. Dyn. Syst., Ser. B 2014, 19, 1087–1103.
[44]Meskaf A. Allali K. and Tabit, Y. (2017) Optimal control of a delayed hepatitis B viral infection model with cytotoxic T-lymphocyte and antibody responses. Int. J. Dyn. Control, 5, 893–902. [CrossRef]
[45]Manna K. and Chakrabarty S. P. (2015) Chronic hepatitis B infection and HBV DNA-containing capsids: Modeling and analysis. Commun. Nonlinear Sci. Numer. Simul., 22, 383–395. [CrossRef]
[46]Hattaf K. and Yousfi, N. (2012) Optimal control of a delayed HIV infection model with immune response using an efficient numerical method. Biomathematics, 2012, 1-7. [CrossRef]
[47]Nowak M. A. and Bangham C. R. (1996) Population dynamics of immune response to persistent viruses. Science, 272, 74-79.
[48]Rosenberg E. S., Altfeld M., Poon S. H., Phillips M. N., Wilkes B.M., Eldridge R. L., Robbins G. K., D’Aquila R. T., Goulder P. J. and Walker B. D. (2000) Immune Control of HIV-1 after Early Treatment of Acute Infection. Nature, 407:523–526.
[49]Eikenberry S., Hews S., Nagy J. D. and Kuang Y. (2009) The dynamics of a delay model of hepatitis B virus infection with logistic hepatocyte growth. Mathematical Biosciences and Engineering, 6(2): 283–299.
[50]Bassey E. B. (2017) Optimal control model for immune effectors response and multiple chemotherapy treatment (MCT) of dual delayed HIV - pathogen infections. SDRP Journal of Infectious Diseases Treatment & Therapy, 1(1) 1-18.
[51]Meskaf A., Allali K. Tabit and Y. (2017) Optimal control of a delayed hepatitis B viral infection model with cytotoxic T-lymphocyte and antibody responses. International Journal of Dynamics and Control, 5(3): 893–902.
[52]Forde J. E., Ciupe S. M., Cintron-Arias A. and Lenhart S. (2016) Optimal control of drug therapy in a hepatitis B model. Applied Sciences, 6(8): articleno, 219, Switzerland.
[53]Mouofo P. T., Tewa J. J., Mewoli B. and Bowong S. (2013) Optimal control of a delayed system subject to mixed control state constraints with application to a within-host model of hepatitis virus B. Annual Reviews in Control, 37(2): 246–259.
[54]Schmitz J. E, et al. (1999) Control of Viremia in Simian Immunodeficiency Virus Infection by CD8 (þ) Lymphocytes. Science, 283, 857–860.
[55]Fister K. R., Lenhart, S. and McNally, J. S. (1998) Optimizing chemotherapy in an HIV Model. Electr. J. Diff. Eq., 32, 1-12.
[56]Velichenko V.V. and Pritykin D. A. (2006) Numerical Methods of Optimal Control of the HIV-Infection Dynamics. Journal of Computer and Systems Sciences International, 45(6): 894–905.
[57]Adams B. M., Banks H. T., Hee-Dae K. and Tran H. T. (2004) Dynamic Multidrug Therapies for HIV: Optimal and STI Control Approaches. Retrieved date: [24, January, 2019], online available at http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.400.9056
[58]Adams B. M., Banks H. T., Davidian M., Kwon Hee-Dae, Tran H. T., Wynne S. N. and Rosenberg E.S. (2005) HIV Dynamics: Modeling, Data Analysis, and Optimal Treatment Protocols. J. Comp. Appl. Math., 184, 10-49. Retrieved date: [24, January, 2019], online available at
http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.8107
[59]Bassey B. E. (2017) Dynamic optimal control model for period multiple chemotherapy (PMC) treatment of dual HIV-pathogen infections. J Anal Pharm Res., 6(3): 00176, 1-22. DOI: 10.15406/japlr.2017.06.00176
[60]Thomsen A. R, Nansen A., Christensen J. P., Andreasen S. O. and Marker O. (1998) CD40 Ligand is Pivotal to Efficient Control of Virus Replication in Mice Infected with Lymphocytic Choriomeningitis Virus. J Immunol, 161, 4583–4590.
[61]Mathew G. V., Bartholomeusz A., Locarnini S., etal. (2006) Characteristics of drug resistant HBV in an international collaborative study of HIV-HBV infected individuals on extended lamivudine therapy. AIDS2006, 20, 863–870.
[62]Shilaih M., Marzel A., Scherrer U. A.,etal. (2016) Dually Active HIV/HBV Antiretroviral as Protection against incident Hepatitis B infections: Potential for Prophylaxis. Journal of Infectious Diseases, 214, 599-606.
[63]Babudieri S., Longo B., Sarmati L, etal. (2005) Correlates of HIV, HBV, and HCV infections in a Prison inmate population: Results from a multicentre study in Italy. Journal of Medical Virology, 76, 311–317.
[64]Fleming W. and Rishel R. (1975) Deterministic and Stochastic Optimal Control. Springer Verlag, New York
[65]Lukes D. L. (1982) Differential Equations: Classical to Controlled, vol. 162 of Mathematics in Science and Engineering, Academic Press, New York, NY, USA.
[66]Perelson S. A., Kirschner E. D. and De Boer R. (1993) Dynamics of HIV-infection of CD4+ T cells. Mathematical Biosciences, 114, 81-125.
[67]Tridane A., Hattaf K., Yafia R., and Rihan F. A. (2016) Mathematical modeling of HBV with the antiviral therapy for the immunocompromised patients. Communications in Mathematical Biology and Neuroscience, 2016, 1-31.