Global analysis of within-host SARS-CoV-2/HIV coinfection model with latency

Abstract

The coronavirus disease 2019 (COVID-19) is a respiratory disease caused by a virus called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this paper, we analyze a within-host SARS-CoV-2/HIV coinfection model. The model is made up of eight ordinary differential equations. These equations describe the interactions between healthy epithelial cells, latently infected epithelial cells, productively infected epithelial cells, SARS-CoV-2 particles, healthy CD4 + T cells, latently infected CD4 + T cells, productively infected CD4 + T cells, and HIV particles. We confirm that the solutions of the developed model are bounded and nonnegative. We calculate the different steady states of the model and derive their existence conditions. We choose appropriate Lyapunov functions to show the global stability of all steady states. We execute some numerical simulations to assist the theoretical contributions. Based on our results, weak CD4 + T cell immunity in SARS-CoV-2/HIV coinfected patients causes an increase in the concentrations of productively infected epithelial cells and SARS-CoV-2 particles. This may lead to severe SARS-CoV-2 infection in HIV patients. This result agrees with many studies that discussed the high risk of severe infection and death in HIV patients when they get SARS-CoV-2 infection. On the other hand, increasing the death rate of infected epithelial cells during the latency period can reduce the severity of SARS-CoV-2 infection in HIV patients. More studies are needed to understand the dynamics of SARS-CoV-2/HIV coinfection and find better ways to treat this vulnerable group of patients.

HIV and COVID-19 co-infection: A mathematical model and optimal control

“…Elaiw et al. [57] analyzed a within-host SARS-CoV and HIV co-infection model with latency. Besides the work in [52] , this study is seemingly the first of its kind to theoretically investigate the co-dynamics of COVID-19 and HIV, with specific inclusion of the AIDS compartment into the mathematical model.…”

Global stability of a delayed SARS-CoV-2 reactivation model with logistic growth, antibody immunity and general incidence rate

“…Elaiw et al [32] developed and proved the global stability of a SARS-CoV-2/cancer coinfection model with two immune responses: cancer-specific CTL immune response and SARS-CoV-2-specific antibody. Mathematical modeling and analysis of SARS-CoV-2/HIV coinfection dynamics were studied in [33] . Chhetri et al [34] formulated and analyzed SARS-CoV-2 dynamics model under the impact of immunomodulating and antiviral drug therapies.…”

“…Fractional differential equations (FDEs) were used in studying the SARS-CoV-2 dynamics between hosts [21] , [22] , [23] , [24] and within-host [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] . Ghanbari [25] extended the model presented in [20] by using fractional derivatives.…”

Global Dynamics of a Within‐Host COVID‐19/AIDS Coinfection Model with Distributed Delays

“…Mathematical models that consist of a system of differential equations have proven their efectiveness in studying the interactions between viruses and their hosts and the common interactions between diseases (see e.g., [12,[18][19][20][21][22][23][24]). HIV within-host models have been widely investigated and great results have been reached [18,19,[25][26][27][28].…”

“…where [21] adopted the same previous model with the addition of the efect of latent cells, and then, they made a comprehensive study of the proposed model. Ringa et al [22] presented a new mathematical model for COVID-19 and HIV/AIDS.…”