Stability Analysis of COVID-19 Model with Quarantine

Full Text (PDF, 765KB), PP.26-45

Views: 0 Downloads: 0

Author(s)

Oladipupo S. Johnson 1,* Helen O. Edogbanya 2 Jacob Emmanuel 1 Seyi E. Olukanni 3

1. Kogi State Polytechnic/Department of Statistics, Nigeria

2. Federal University Lokoja/ Department of Mathematics, Nigeria

3. Department of Physics / Confluence University of Science and Technology Osara, Nigeria

* Corresponding author.

DOI: https://doi.org/10.5815/ijmsc.2023.03.03

Received: 24 May 2023 / Revised: 15 Jun. 2023 / Accepted: 7 Jul. 2023 / Published: 8 Aug. 2023

Index Terms

Epidemiology, Gaussian elimination, Routh-Hurwitz stability criteria, Reproduction number

Abstract

In this paper, A 6 (six) compartmental (S, IU, IS, IA, Q, R) model was presented to examine the dynamical behavior of disease transmission in the system with quarantine effect on the symptomatic infected, asymptomatic infected and Reproduction number R0 within a given population. The parameters model was analyzed and estimated experimentally using the real data of COVID-19 confirmed cases for Ethiopia via MATLAB 2021a. Reproduction number R0 which is a key indicator to whether a disease outbreak spread force will persist or die out within population. R0 was found using the next generation matrix with Gaussian elimination method to obtain the inverse of the transitive matrix. The model also aims at reducing R0 owning to the fact that when the basic reproduction number is less than 1 infected person, disease dies out and when the reproduction number is greater than 1 infected person, the disease persists. The facts about R0 geared us to mathematically check for the Routh-Hurwitz stability criteria and Lyapunov Functions to concisely establish the necessary and sufficient conditions for the Local and Global stability of model. results show that, when R0 < 1 and R0 > 1 the diseases free equilibrium and endemic equilibrium points are locally and globally asymptotically stable respectively. In order to interpret results and recommend possible control measure of disease, The dynamics of the Quarantine compartment in model was tested via sensitivity analysis to experimentally investigate transition/ transmission pattern. The effect of quarantine analysis on the model shows that preventive measures such as increase in quarantine with treatments during disease outbreak will significantly decrease the Reproduction number. Hence, increase in Quarantine compartment will flatten the curve of (S, IU, IS, IA, Q, R) dynamic model correspondingly.

Cite This Paper

Oladipupo S. Johnson, Helen O. Edogbanya, Jacob Emmanuel, Seyi E. Olukanni, "Stability Analysis of COVID-19 Model with Quarantine", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.9, No.3, pp. 26-45, 2023. DOI:10.5815/ijmsc.2023.03.03

Reference

[1]Wise, J. (2023). Covid-19: WHO declares end of global health emergency.
[2]Cucinotta, D., Vanelli, M. (2020). WHO declares COVID-19 a pandemic. Acta bio medica: Atenei parmensis,91(1), 157.
[3]Kupferschmidt, K., & Wadman, M. (2023). End of COVID-19 emergencies sparks debate. Science, 380(6645), 566-7.
[4]Brauer, F. (2017). Mathematical epidemiology: Past, present, and future. Infectious Disease Modelling, 2(2), 113-127.
[5]Weiss, H. H. (2013). The SIR model and the foundations of public health. Materials mathematics, 0001-17.
[6]Deressa, C. T., Duressa, G. F. (2021) Modeling and Optimal control analysis of transmission dynamics of COVID-19: The case of Ethiopia. Alexandria Engineering Journal, 60(1), 719-732.
[7]Liu,Y., Gayle, A.A., Wilder-Smith, A., Rocklov, J.(2020) The reproduction number of COVID-19 is higher compared to SARS coronavirus. Journal of travel medicine.
[8]Mpeshe, S. C., Nyerere N. (2021). Modeling the dynamics of coronavirus disease Pandemic Coupled with fear epidemics. Computational and Mathematical Methods in Medicine, 2021.
[9]Riyapan, P., Shuaib, S. E., Intarasit, A. (2021). A Mathematical model of COVID-19 Pandemic: A case Study of Bangkok, Thailand. Computational and Mathematical Methods in Medicine, 2021.
[10]Ojo, M.M., Akinpelu, F. O. (2017). Lyapunov functions and Global Properties of seir epidemic model. International journal of Chemistry, mathematics and physics (IJCMP),1(1).
[11]Edith, D. N., Mbah, G. C. E., and Bassey, B. E. (2020). Optimal control Analysis Model of Ebola Virus infection: Impact of Socio-Economic Status. Int. J. Appl. Sci. Math, 6, 2394-2894.
[12]Adedire O., Joel N. Ndam.” Mathematical model of the Spread of COVID-19 in Plateau State, Nigeria. Journal of the Egyptian Mathematical Society30.1 (2022):10.
[13]Zamir, M., Abdeljawad, T., Nadeem, F., Wahid, A., Yousef, A. (2021). An optimal control analysis of a COVID-19 model. Alexandria Engineering Journal, 60(3), 2875-2884.
[14]Mahardika, R., Sumanto, Y.D. (2019, May). Routh-Hurwitz criterion and bifurcation method for stability analysis of tuberculosis transmission model. in Journal of Physics: Conference series (Vol. 1217, No. 1, p. 012056). IOP Publishing.
[15]Kanchanarat, Siwaphorn, Settapat Chinviriyasit, W. (2022). Mathematical Assessment of impact of the Imperfect Vaccination on Diphtheria Transmission Dynamics. Symmetry, 14(10).
[16]Gebremeskel, A. A., Berhe, H. W., Abay, A. T. (2022). A Mathematical Modelling and Analysis of COVID-19 Transmission Dynamics with Optimal Control Strategy. Computational and Mathematical Methods in Medicine, 2022.