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Mathematical modeling of HIV-HCV co-infection model: Impact of parameters on reproduction number
Oluwakemi E Abiodun1, Olukayode Adebimpe2, James A Ndako1
1Physical Sciences, Landmark University, Omu Aran, State, 251101, Nigeria.
Insights
Mathematical modeling of HIV/HCV co-infection reveals that treating Hepatitis C Virus (HCV) first in co-infected individuals can reduce the co-infection reproduction number and liver cancer risk. Public health interventions are crucial for reducing mono- and co-infections.
Area of Science:
- Epidemiology
- Mathematical Biology
- Public Health
Background:
- Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV) are blood-borne viruses with significant global prevalence, particularly among people who inject drugs (PWID).
- HIV co-infection exacerbates HCV progression, leading to increased viral load, fibrosis, and end-stage liver disease.
- Understanding the dynamics of HIV/HCV co-infection is critical for developing effective control strategies.
Purpose of the Study:
- To develop and analyze a mathematical model simulating the dynamics of HIV/HCV co-infection.
- To incorporate factors such as dual therapy, vertical HIV transmission, HIV awareness status, treatment adherence, and condom use into the model.
- To evaluate the impact of different intervention strategies on disease transmission and progression.
Main Methods:
- The study employed mathematical modeling techniques to analyze the dynamical behavior of HIV/HCV co-infection.
- Positivity, boundedness, and equilibria of the model were established using established mathematical theorems.
- Reproduction numbers were calculated using the next-generation matrix approach, and stability analysis was performed using linearization and Bendixson-Dulac criteria.
Main Results:
- Increased HIV treatment dropout was associated with reduced HIV treatment adherence and increased prevalence in other compartments.
- Prioritizing HCV treatment in dually infected individuals was shown to decrease the co-infection reproduction number (R_c), thereby lowering the risk of liver cancer.
- The model highlighted the impact of various parameters on disease dynamics.
Conclusions:
- Public health policies should focus on comprehensive strategies, including awareness campaigns about risks associated with multiple sexual partners and promoting consistent condom use.
- Continued treatment for chronic HCV and AIDS is essential for managing co-infections.
- Implementing these interventions can effectively reduce the burden of mono- and co-infections in the population.
Abstract:
Background: Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV) are both classified as 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 are people who 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 , which reduces liver cancer risk. Conclusions: From the model's results, we infer various steps (such as: campaigns to warn individuals about the consequences of having multiple sexual partners; distributing more condoms to individuals; continuing treatment for chronic HCV and AIDS) that policymakers could take to reduce the number of mono-infected and co-infected individuals.
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