Your browser doesn't support javascript.
Global dynamics of SARS-CoV-2/cancer model with immune responses.
Elaiw, A M; Al Agha, A D.
  • Elaiw AM; Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia.
  • Al Agha AD; Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut Branch, Assiut, Egypt.
Appl Math Comput ; 408: 126364, 2021 Nov 01.
Article in English | MEDLINE | ID: covidwho-1225115
ABSTRACT
The world is going through a critical period due to a new respiratory disease called coronavirus disease 2019 (COVID-19). This disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Mathematical modeling is one of the most important tools that can speed up finding a drug or vaccine for COVID-19. COVID-19 can lead to death especially for patients having chronic diseases such as cancer, AIDS, etc. We construct a new within-host SARS-CoV-2/cancer model. The model describes the interactions between six compartments nutrient, healthy epithelial cells, cancer cells, SARS-CoV-2 virus particles, cancer-specific CTLs, and SARS-CoV-2-specific antibodies. We verify the nonnegativity and boundedness of its solutions. We outline all possible equilibrium points of the proposed model. We prove the global stability of equilibria by constructing proper Lyapunov functions. We do some numerical simulations to visualize the obtained results. According to our model, lymphopenia in COVID-19 cancer patients may worsen the outcomes of the infection and lead to death. Understanding dysfunctions in immune responses during COVID-19 infection in cancer patients could have implications for the development of treatments for this high-risk group.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: Appl Math Comput Year: 2021 Document Type: Article Affiliation country: J.amc.2021.126364

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: Appl Math Comput Year: 2021 Document Type: Article Affiliation country: J.amc.2021.126364