Abstract
Coronavirus disease 2019 (COVID-19) is a respiratory disease caused by SARS-CoV-2. It appeared in China in late 2019 and rapidly spread to most countries of the world. Cancer patients infected with SARS-CoV-2 are at higher risk of developing severe infection and death. This risk increases further in the presence of lymphopenia affecting the lymphocytes count. Here, we develop a delayed within-host SARS-CoV-2/cancer model. The model describes the occurrence of SARS-CoV-2 infection in cancer patients and its effect on the functionality of immune responses. The model considers the time delays that affect the growth rates of healthy epithelial cells and cancer cells. We provide a detailed analysis of the model by proving the nonnegativity and boundedness of the solutions, finding steady states, and showing the global stability of the different steady states. We perform numerical simulations to highlight some important observations. The results indicate that increasing the time delay in the growth rate of cancer cells reduced the size of tumors and decreased the likelihood of deterioration in the condition of SARS-CoV-2/cancer patients. On the other hand, lymphopenia increased the concentrations of SARS-CoV-2 particles and cancer cells, which worsened the condition of the patient.
Highlights
Accepted: 31 May 2021Coronavirus disease 2019 (COVID-19) is a respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
We show the effect of time delays and lymphopenia on the dynamics of model (1)
Cancer patients are at greater risk for hospitalization and death due to SARS-CoV-2 infection compared to other patients who do not have cancer [2]
Summary
Coronavirus disease 2019 (COVID-19) is a respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Many mathematical models have been developed at the epidemiological level for COVID19 [7,28,29,30,31,32,33] These models discuss the transmission of SARS-CoV-2 and predict the best strategies to reduce the spread of the disease between people [6,34]. Almocera et al [35] considered a model that depicts the interaction between SARS-CoV-2 and effector T cells They performed stability and bifurcation analysis to help understand how the virus can overcome the immune response and cause infection [35]. A small number of studies have been done to examine the impact of COVID-19 viral infection on cancer at the cellular level [10] This has raised the need for understanding the dynamics of SARS-CoV-2 in cancer patients and the role of immune responses in this situation.
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