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On the Role of Optimal Counseling and Antiviral Therapy on Controlling HCV among Intravenous Drug Misusers

DOI: 10.1155/2014/347827

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Abstract:

Hepatitis C virus (HCV) remains a major health challenge despite the availability of highly effective antiviral drugs. Prior studies suggest that many physicians are reluctant to treat intravenous drug misusers due to low levels of treatment adherence associated with intravenous drug misusers. HCV treatment guidelines and recommendations stipulate that HCV patients in treatment should abstain from intravenous drug misuse activities in order to reduce the likelihood of treatment failure, drug resistance, reinfection, superinfection, or mixed infection. In this paper, a mathematical model for exploring the transmission dynamics of HCV among intravenous drug misusers is proposed. The model incorporates essential characteristics of intravenous drug misusers such as relapse and nonadherence to treatment guidelines. With the aid of optimal control theory we assess the effects of time dependent HCV screening and treatment. Results from this study provide a framework for designing the appropriate strategies on controlling the long-term dynamics of HCV among intravenous drug users. 1. Introduction Intravenous drug misuse continues to claim a large proportion of new hepatitis C virus (HCV) infections worldwide [1]. Despite advancements in the management of HCV and suggestions that treatment of recently acquired HCV can lead to virological response rate of up to 98%, low rates of treatment among HCV patients continue to be observed [2]. Apart from low treatment rates, nonadherence to HCV treatment guidelines and recommendations has been observed as one of the major challenges on effective HCV control among intravenous drug misusers [2, 3]. Adherence in the context of HCV treatment includes the patient’s adherence to both the medication regimen and the overall medical plan [3]. Nonadherence to HCV treatment may be associated with a number of reasons among the following: higher pill burden and lengthy treatment, limited provider experience, lack of social support, and presence of cirrhosis [4]. This study aims to evaluate the effects of time dependent HCV screening and treatment. The application of optimal control theory on gaining insights into the long-term dynamics of HCV has been an interesting topic for a couple of researchers (e.g., see [5–8] and the references therein). In 2011, Martin et al. [5] developed a mathematical model to assess the impact of time dependent control on HCV antiviral treatment. Their work revealed, among others, that, with a fixed annual budget, greater impact on HCV control (measured by infections averted or prevalence reductions) and

References

[1]  S. Mushayabasa and C. P. Bhunu, “Hepatitis C and intravenous drug misuse: a modeling approach,” International Journal of Biomathematics, vol. 7, no. 1, 2014.
[2]  M. Hellard, R. Sacks-Davis, and J. Gold, “Hepatitis c treatment for injection drug users: a review of the available evidence,” Clinical Infectious Diseases, vol. 49, no. 4, pp. 561–573, 2009.
[3]  P. Higgs, R. Sacks-Davis, J. Gold, and M. Hellard, “Barriers to receiving hepatitis c treatment for people who inject drugs myths and evidence,” Hepatitis Monthly, vol. 11, no. 7, pp. 513–518, 2011.
[4]  Centers for Disease Control and Prevention, Viral Hepatitis Surveillance, Centers for Disease Control and Prevention, Atlanta, Ga, USA, 2009.
[5]  N. K. Martin, A. B. Pitcher, P. Vickerman, A. Vassall, and M. Hickman, “Optimal control of hepatitis C antiviral treatment programme delivery for prevention amongst a population of injecting drug users,” PLoS ONE, vol. 6, no. 8, Article ID e22309, 2011.
[6]  A. Khan, S. Sial, and M. Imran, “Transmission dynamics of hepatitis C with control strategies,” Journal of Computational Medicine, vol. 2014, Article ID 654050, 18 pages, 2014.
[7]  S. Mushayabasa, C. P. Bhunu, G. Magombedze, and A. G. R. Stewart, “On the role of screening and educational campaigns on controlling HCV in correctional institutions,” Journal of Biological Systems, vol. 21, no. 1, Article ID 1350007, 2013.
[8]  S. Mushayabasa, C. P. Bhunu, and R. J. Smith, “Assessing the impact of educational campaigns on controlling HCV among women in prison settings,” Communications in Nonlinear Science and Numerical Simulation, vol. 17, no. 4, pp. 1714–1724, 2012.
[9]  S. Mushayabasa and C. P. Bhunu, “Mathematical analysis of hepatitis C model for intravenous drug misusers: impact of antiviral therapy, abstinence and relapse,” Simulation: Transactions of the Society of Modeling and Simulation International, vol. 90, no. 5, pp. 487–500, 2014.
[10]  W. H. Fleming and R. W. Rishel, Deterministic and Stochastic Optimal Control, Springer, 1975.
[11]  D. L. Lukes, Differential Equations: Classical to Controlled, Mathematics in Science and Engineering, Academic Press, New York, NY, USA, 1982.
[12]  E. Jung, S. Lenhart, and Z. Feng, “Optimal control of treatments in a two-strain tuberculosis model,” Discrete and Continuous Dynamical Systems B, vol. 2, no. 4, pp. 473–482, 2002.

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