Stability analysis of within-host SARS-CoV-2/HIV coinfection model
Afnan D Al Agha1, Ahmed M Elaiw2,3, Shaimaa A Azoz4
1Department of Mathematical Science, College of Engineering University of Business and Technology Jeddah Saudi Arabia.
Insights
Mathematical modeling of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human immunodeficiency virus (HIV) coinfection reveals that a weakened immune response increases SARS-CoV-2 viral load, leading to more severe COVID-19 outcomes in coinfected patients.
Area of Science:
- Virology
- Mathematical Biology
- Immunology
Background:
- The COVID-19 pandemic, caused by SARS-CoV-2, has seen reported coinfections with HIV globally.
- Understanding SARS-CoV-2/HIV coinfection dynamics is crucial for patient outcomes.
- Mathematical modeling aids in studying viral dynamics and coinfections.
Purpose of the Study:
- To develop and analyze a within-host mathematical model for SARS-CoV-2 and HIV coinfection.
- To investigate the impact of coinfection on viral loads and disease severity.
- To assess the role of CD4+ T cell immune response in SARS-CoV-2/HIV coinfection.
Main Methods:
- Development of a mathematical model comprising six ordinary differential equations.
- Analysis of model solutions for biological acceptability (nonnegativity, boundedness).
- Computation of steady states, derivation of positivity conditions, and proof of global asymptotic stability using Lyapunov functions.
- Numerical simulations to support stability analysis.
Main Results:
- The model demonstrates that a weak CD4+ T cell immune response or low CD4+ T cell counts elevate infected epithelial cells and SARS-CoV-2 viral load.
- This exacerbates SARS-CoV-2 infection severity in coinfected individuals.
- Findings align with studies indicating higher COVID-19 severity risk in HIV patients.
Conclusions:
- Mathematical modeling provides insights into SARS-CoV-2/HIV coinfection dynamics.
- Impaired CD4+ T cell immunity significantly worsens COVID-19 outcomes in coinfected patients.
- Further research is needed to elucidate coinfection mechanisms and immune responses.
Abstract:
The world has been suffering from the coronavirus disease 2019 (COVID-19) since late 2019. COVID-19 is caused by a virus called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The human immunodeficiency virus (HIV) coinfection with SARS-CoV-2 has been reported in many patients around the world. This has raised the alarm for the importance of understanding the dynamics of coinfection and its impact on the lives of patients. As in other pandemics, mathematical modeling is one of the important tools that can help medical and experimental studies of COVID-19. In this paper, we develop a within-host SARS-CoV-2/HIV coinfection model. The model consists of six ordinary differential equations. It depicts the interactions between uninfected epithelial cells, infected epithelial cells, free SARS-CoV-2 particles, uninfected CD4+ T cells, infected CD4+ T cells, and free HIV particles. We confirm that the solutions of the developed model are biologically acceptable by proving their nonnegativity and boundedness. We compute all possible steady states and derive their positivity conditions. We choose suitable Lyapunov functions to prove the global asymptotic stability of all steady states. We run some numerical simulations to enhance the global stability results. Based on our model, weak CD4+ T cell immune response or low CD4+ T cell counts in SARS-CoV-2/HIV coinfected patient increase the concentrations of infected epithelial cells and SARS-CoV-2 viral load. This causes the coinfected patient to suffer from severe SARS-CoV-2 infection. This result agrees with many studies which showed that HIV patients are at greater risk of suffering from severe COVID-19 when infected. More studies are needed to understand the nature of SARS-CoV-2/HIV coinfection and the role of different immune responses during infection.
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