ANALISIS KESTABILAN MODEL SI UNTUK PENYAKIT MENULAR DENGAN ADANYA TRANSMISI VERTIKAL DAN TINGKAT KEJADIAN JENUH
Abstract
The transmission of infectious diseases can occur through two pathways: horizontal and vertical. Horizontal transmission occurs through direct or indirect physical contact with the infectious agent, while vertical transmission takes place when an infected mother transmits the disease to a fetus or a newborn. Within the context of disease transmission models, a critical feature is the saturation incidence rate, which refers to the impact of interventions that can reduce the rate of disease transmission among susceptible and infected individuals. This research aims to elucidate the formation of a model, determine equilibrium points, and calculate the basic reproduction number using the Next Generation Matrix method. The analysis involves assessing local stability through linearization methods and global stability using Lyapunov functions. Sensitivity analysis is conducted on the basic reproduction number, and numerical simulations are performed using the fourth-order Runge-Kutta method. The research findings indicate the establishment of an SIS (Susceptible-Infected) model for infectious diseases with vertical transmission and saturation incidence. This model depicts the spread of the disease in a population, where individuals can exist in susceptible or infected conditions. Equilibrium points include a disease-free equilibrium that is locally and globally stable when the basic reproduction number is less than one, and an endemic equilibrium that is locally and globally stable when the basic reproduction number exceeds one. Sensitivity analysis reveals that each parameter has varying influences on the basic reproduction number. An increase in the saturation incidence rate leads to a decrease in the number of infected subpopulations, while an increase in the vertical transmission rate results in a similar decline. Numerical simulations support stability analyses at equilibrium points. These findings provide a deeper understanding of the factors influencing the spread of diseases within a population.
Keywords
Full Text:
PDFReferences
Abta, A., Kaddar, A., & Alaoui, H. T. (2012). Global Stability for Delay Sir and Seir Epidemic Models with Saturated Incidence Rates. Electronic Journal of Differential Equations, 2012(23), 1–13.
Adepoju, O. A., & Olaniyi, S. (2021). Stability and optimal control of a disease model with vertical transmission and saturated incidence. Scientific African, 12, 1–12. https://doi.org/10.1016/j.sciaf.2021.e00800
Alzahrani, E. O., Ahmad, W., Khan, M. A., & Malebary, S. J. (2020). Optimal Control Strategies of Zika Virus Model with Mutant. Communications in Nonlinear Science and Numerical Simulation, 93, 1–17. https://doi.org/10.1016/j.cnsns.2020.105532
Annas, S., Isbar Pratama, M., Rifandi, M., Sanusi, W., & Side, S. (2020). Stability analysis and numerical simulation of SEIR model for pandemic COVID-19 spread in Indonesia. Chaos, Solitons and Fractals, 139. https://doi.org/10.1016/j.chaos.2020.110072
Bellomo, N., Preziosi, L. uigi, & Romano, A. (2005). Modeling and Simulation in Science , Engineering and Technology. Springer, New York City.
Bellomo, N., & Preziozi, L. (1995). Modelling Mathematical Methods Scientific Computation.
Braun, M. (1992). Differential Equations and their Applications (4th ed.). Springer Science. https://doi.org/10.1007/978-1-4612-4360-1
Chitnis, N., Hyman, J. M., & Cushing, J. M. (2008). Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model. Bulletin of Mathematical Biology, 70(5), 1272–1296. https://doi.org/10.1007/s11538-008-9299-0
Driessche, P. Van Den, & Watmough, J. (2002). Reproduction Numbers and Sub-threshold Endemic Equilibria for Compartmental Models of Disease Transmission. Mathematical Biosciences, 180(1–2), 29–48. https://doi.org/10.1016/S0025-5564(02)00108-6
Hethcote, H. W. (2000). The Mathematical Models of Diseases. SIAM Review, 42(4), 599–653.
Irwan. (2016). Epidemiologi Penyakit Menular. In Pengaruh Kualitas Pelayanan… Jurnal EMBA (Vol. 109, Issue 117).
Jamil, A. K., Yulida, Y., & Karim, M. A. (2023). Analisis Kestabilan dan Solusi Numerik pada Model SEIR untuk Penyakit Tuberkulosis. 17(1), 14–29.
Jiao, J., Cai, S., & Li, L. (2016). Dynamics of an SIR model with vertical transmission and impulsive dispersal. Journal of Applied Mathematics and Computing, 52(1–2), 139–155. https://doi.org/10.1007/s12190-015-0934-2
Kelatlhegile, G. R., & Kgosimore, M. (2016). Bifurcation analysis of vertical transmission model with preventive strategy. Journal of the Egyptian Mathematical Society, 24(0), 492–498. https://doi.org/10.1016/j.joems.2015.10.001
Lahrouz, A., Omari, L., & Kiouach, D. (2011). Global analysis of a deterministic and stochastic nonlinear SIRS epidemic model. Nonlinear Analysis: Modelling and Control, 16(1), 59–76. https://doi.org/10.15388/na.16.1.14115
Li, M. Y., Smith, H. A. L. L., & Wang, L. (2001). Global Dynamics of an Seir Epidemic Model With. SIAM J. Appl. Math., 62(1), 58–69.
Martcheva, M. (2015). in An Introduction to Mathematical Epidemiology. In An Introduction to Mathematical Epidemiology.
Sudiarta, I. W. (2019). Metode Numerik. Arga Puji Press.
Suryani, I., & Yuenita.E, M. (2016). Analisis Kestabilan Model MSEIR Penyebaran Penyakit Difteri Dengan Saturated Incidence Rate. Jurnal Sains Matematika Dan Statistika, 2(1), 75–85.
Wiggins, S. (2003). Texts in Applied Mathematics 2 Introduction to Applied Nonlinear Dynamical Systems and Chaos. In Texts in Applied Mathematics 2.
DOI: https://doi.org/10.20527/epsilon.v17i2.10826
Refbacks
- There are currently no refbacks.
Copyright (c) 2023 EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN
Indexed by:
EDITORIAL OFFICE
JMMTE is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.