Al Agha Afnan D, Elaiw Ahmed M, Azoz Shaimaa A, Ramadan Esraa
Department of Mathematical Science, College of Engineering University of Business and Technology Jeddah Saudi Arabia.
Department of Mathematics, Faculty of Science King Abdulaziz University Jeddah Saudi Arabia.
Math Methods Appl Sci. 2022 Jun 3. doi: 10.1002/mma.8457.
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.
自2019年末以来，全球一直在遭受2019冠状病毒病（COVID-19）的困扰。COVID-19由一种名为严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的病毒引起。世界各地的许多患者都报告了人类免疫缺陷病毒（HIV）与SARS-CoV-2的合并感染情况。这为了解合并感染的动态及其对患者生命的影响敲响了警钟。与其他大流行病一样，数学建模是有助于COVID-19医学和实验研究的重要工具之一。在本文中，我们建立了一个宿主内SARS-CoV-2/HIV合并感染模型。该模型由六个常微分方程组成。它描述了未感染的上皮细胞、感染的上皮细胞、游离的SARS-CoV-2颗粒、未感染的CD4 T细胞、感染的CD4 T细胞和游离的HIV颗粒之间的相互作用。我们通过证明所建立模型的解的非负性和有界性，确认其在生物学上是可接受的。我们计算了所有可能的稳态，并推导了它们的正性条件。我们选择合适的李雅普诺夫函数来证明所有稳态的全局渐近稳定性。我们进行了一些数值模拟以加强全局稳定性结果。基于我们的模型，SARS-CoV-2/HIV合并感染患者中较弱的CD4 T细胞免疫反应或较低的CD4 T细胞计数会增加感染上皮细胞的浓度和SARS-CoV-2病毒载量。这会导致合并感染患者患上严重的SARS-CoV-2感染。这一结果与许多研究一致，这些研究表明HIV患者在感染时患严重COVID-19的风险更高。需要更多的研究来了解SARS-CoV-2/HIV合并感染的本质以及感染期间不同免疫反应的作用。
