Claim Missing Document
Check
Articles

Found 2 Documents
Search

Mathematical Model of SAR-CoV-2 and Influenza A Virus Coinfection within Host with CTL-Mediated Immunity Khumaeroh, Mia Siti; Nuwari, Najmudin; Erianto, Elvi Syukrina; Rizka, Nela
Jambura Journal of Biomathematics (JJBM) Volume 5, Issue 2: December 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v5i2.27782

Abstract

Coinfection of SARS-CoV-2 and Influenza A virus within a host poses a unique challenge in understanding immunological dynamics, especially the role of cytotoxic T lymphocytes (CTL) in mediating the immune response. This work present a mathematical model to examine the dynamics of coinfection within a host, highlighting CTL-mediated immunity. Generally, this model encompasses several compartments, including epithelial cells, free viruses, and CTLs specific of both SARS-CoV-2 and Influenza A. The basic properties of the model, equilibrum state analysis, stability using the Lyapunov function, and numerical simulations are examined to investigate the dynamics behavior of the model. Eight equilibrium states are identified: the virus-free equilibrium (E0), single SARS-CoV-2 infection without CTLs (E1), single Influenza A virus infection without CTLs (E2), single SARS-CoV-2 infection with SARS-CoV-2-specific CTLs (E3), single Influenza A virus infection with Influenza A virus-specific CTLs (E4), SARS-CoV-2 and Influenza A virus coinfection with SARS-CoV-2-specific CTLs (E5), SARS-CoV-2 and Influenza A virus coinfection with Influenza A virus-specific CTLs (E6), and SARS-CoV-2 and Influenza A virus coinfection with both SARS-CoV-2-specific and Influenza A virus-specific CTLs (E7). The existence and stability regions for each equilibrium state are determined and represented in the R1-R2 plane as threshold functions within the model. Numerical simulations confirm the results of the qualitative analysis, demonstrating that CTLs specific to SARS-CoV-2 and Influenza A virus can be activated, reducing the number of infected epithelial cells as well as inhibiting virus transmission within epithelial cells. Furthermore, analysis of parameter changes shows that increasing the proliferation rate of epithelial cells and CTLs, while lowering the virus formation rate, can shift the system's stability threshold and stabilize it at the virus-free equilibrium.
Drug-Drug Interactions Pharmacokinetic Models with Extravascular Administration: Estimation of Elimination and Absorption Rate Constants Zulkarnaen, Diny; Irfani, Muhammad Syifa; Erianto, Elvi Syukrina
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 4 (2023): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i4.16479

Abstract

One and two-compartment pharmacokinetic models with drug-drug interactions are proposed. Two drugs are given orally simultaneously, so that their interaction affects the drug absorption process and subsequently the elimination process. The aim of this paper is to estimate the elimination and absorption rate constants by evaluating the data set of time and drug concentration. This data set was divided into two time phases: large-time elimination phase to estimate the elimination rate constant, and small-time absorption phase to estimate the absorption rate constant. Since the models are nonlinear, the Taylor expansion is employed to so that the Wagner-Nelson and the Loo-Riegelman methods can be used for estimation. Finally, simulations were performed using the generated arbitrary data set of time and concentration, instead of an actual data set, to derive the solution of drug concentration concerning time numerically. In these simulations we compared the original parameter values with their estimates for the one and two-compartment models, and we concluded that the two-compartment model produced better estimates than the one-compartment model. Qualitatively, the two-compartment model gives smaller drug concentration curve deviations between the original and the estimated curve compared with the one-compartment model.