Mathematical modeling of HIV-HCV co-infection model: Impact of parameters on reproduction number [version 1; peer review: 1 approved, 1 approved with reservations]

• Published in: F1000 research Vol. 11; p. 1153
• Main Authors: Abiodun, Oluwakemi E., Adebimpe, Olukayode, Ndako, James A., Oludoun, Olajumoke, Aladeitan, Benedicta, Adeniyi, Michael
• Format: Journal Article
• Language: English
• Published: England F1000 Research Ltd 2022
• Subjects: Acquired Immunodeficiency Syndrome; awareness; Coinfection - epidemiology; eng; HCV; Hepacivirus; Hepatitis C - complications; Hepatitis C - epidemiology; HIV; HIV Infections - complications; HIV Infections - epidemiology; HIV/AIDS; Humans; infection-free equilibrium; Mathematical model; Models, Theoretical; Reproduction; unawareness; HIV/AIDS; endemic equilibrium; awareness; next generation matrix; unawareness; HCV; infection-free equilibrium; Mathematical model; stability; basic reproduction number
• ISSN: 2046-1402; 2046-1402
• DOI: 10.12688/f1000research.124555.1

Background: Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV) are both as classified blood-borne viruses since they are transmitted through contact with contaminated blood. Approximately 1.3 million of the 2.75 million global HIV/HCV carriers inject drugs (PWID). HIV co-infection has a harmful effect on the progression of HCV, resulting in greater rates of HCV persistence after acute infection, higher viral levels, and accelerated progression of liver fibrosis and end-stage liver disease. In this study, we developed and investigated a mathematical model for the dynamical behavior of HIV/AIDS and HCV co-infection, which includes therapy for both diseases, vertical transmission in HIV cases, unawareness and awareness of HIV infection, inefficient HIV treatment follow-up, and efficient condom use.
Methods: Positivity and boundedness of the model under investigation were established using well-known theorems. The equilibria were demonstrated by bringing all differential equations to zero. The associative reproduction numbers for mono-infected and dual-infected models were calculated using the next-generation matrix approach. The local and global stabilities of the models were validated using the linearization and comparison theorem and the negative criterion techniques of bendixson and dulac, respectively.
Results: The growing prevalence of HIV treatment dropout in each compartment of the HIV model led to a reduction in HIV on treatment compartments while other compartments exhibited an increase in populations
. In dually infected patients, treating HCV first reduces co-infection reproduction number
R
ech
, which reduces liver cancer risk.
Conclusions: From the model's results, we infer various steps that policymakers could take to reduce the number of mono-infected and co-infected individuals.