The HIV-HCV co-infection dynamics in absence of therapy

Paper presented at the 5th Strathmore International Mathematics Conference (SIMC 2019), 12 - 16 August 2019, Strathmore University, Nairobi, KenyaHIV-HCV co-infection is whereby an individual is infected with both viruses HIV and HCV. Globally, approximately 4 to 5 million people are co-infected with HIV and HCV. HCV infection significantly causes morbidity and mortality among HIV patients. HCV is known to progress faster and cause more liver-related health problems and death among people who are HIV/AIDS positive than those who are negative. Co-infection with HCV complicates the management of HIV/AIDS. Mathematical modeling generally provides an explicit framework by which we can develop and communicate an understanding of transmission dynamics of an infectious disease. In this article, a deterministic model is used in which ordinary differential equations are formulated and analyzed to study the HIV-HCV co-infection dynamics in absence of therapy. The findings reveal that the basic reproduction number for HIV-HCV co infection dynamics is equal to the maximum of single-disease basic reproduction numbers. This implies that the dynamics of the HIV-HCV co-infection will be dominated by the disease with the bigger basic reproduction numberInstitute of Mathematical Sciences, Strathmore University, Nairobi, Kenya. Uganda Virus Research Institute London School of Hygiene and Tropical Medicine, Ugand

Mathematical Modelling of HIV-HCV Coinfection Dynamics in Absence of Therapy

Globally, it is estimated that of the 36.7 million people infected with human immunodeficiency virus (HIV), 6.3% are coinfected with hepatitis C virus (HCV). Coinfection with HIV reduces the chance of HCV spontaneous clearance. In this work, we formulated and analysed a deterministic model to study the HIV and HCV coinfection dynamics in absence of therapy. Due to chronic stage of HCV infection being long, asymptomatic, and infectious, our model formulation was based on the splitting of the chronic stage into the following: before onset of cirrhosis and its complications and after onset of cirrhosis. We computed the basic reproduction numbers using the next generation matrix method. We performed numerical simulations to support the analytical results. We carried out sensitivity analysis to determine the relative importance of the different parameters influencing the HIV-HCV coinfection dynamics. The findings reveal that, in the long run, there is a substantial number of individuals coinfected with HIV and latent HCV. Therefore, HIV and latently HCV-infected individuals need to seek early treatment so as to slow down the progression of HIV to AIDS and latent HCV to advanced HCV