Dynamic Analysis of COVID-19 Model with Quarantine and Isolation
DOI:
https://doi.org/10.31764/jtam.v5i2.5167Keywords:
COVID-19 Model, Basic Reproduction Number, Local Stability, Numerical Simulations.Abstract
This study discusses the dynamic analysis of the COVID-19 model with quarantine and isolation. The population in this model is divided into seven subpopulations: subpopulation of susceptible, exposed, asymptomatic, symptomatic, quarantine, isolated and recovered. Two equilibrium points were obtained based on the analysis results, namely the disease-free and endemic equilibrium points. The existence and local stability of the equilibrium point depends on the value of the basic reproduction number . Then, the point of disease-free equilibrium always exists, and the point of endemic equilibrium exists when it meets . The point of disease-free equilibrium is locally asymptotically stable when it satisfies  and the endemic equilibrium point is locally asymptotically stable with conditions. Furthermore, numerical simulations are carried out to determine the model's behavior using the fourth-order Runge-Kutta method. The numerical simulation obtained supports the dynamic analysis results. Finally, the graphical results are presented. The findings here suggest that human-to-human contact is a potential cause of the COVID-19 outbreak. Therefore, quarantine of susceptible and exposed subpopulations can reduce the risk of infection. Likewise, isolation of infected subpopulations can reduce the risk of spreading COVID-19.References
Aldila, D., Ndii, M. Z., & Samiadji, B. M. (2020). Optimal control on COVID-19 eradication program in Indonesia under the effect of community awareness. Mathematical Biosciences and Engineering, 17(6), 6355–6389. https://doi.org/10.3934/mbe.2020335
Belgaid, Y., Helal, M., & Venturino, E. (2020). Analysis of a Model for Coronavirus Spread. Mathematics, 8(5), 1–30. https://doi.org/10.3390/MATH8050820
Brauer, F., & Castillo-Chavez, C. (2012). Mathematical Models in Population Biology and Epidemiology. In The American Mathematical Monthly (Second Edi, Vol. 110, Issue 3). Springer-Verlag New York. https://doi.org/10.2307/3647954
Chen, T. M., Rui, J., Wang, Q. P., Zhao, Z. Y., Cui, J. A., & Yin, L. (2020). A mathematical model for simulating the phase-based transmissibility of a novel coronavirus. Infectious Diseases of Poverty, 9(1), 1–8. https://doi.org/10.1186/s40249-020-00640-3
Feng, Z. (2007). Final and Peak Epidemic Sizes for SEIR Models with Quarantine and Isolation. Mathematical Biosciences and Engineering, 4(4), 675–686.
Heffernan, J. M., Smith, R. J., & Wahl, L. M. (2005). Perspectives on the basic reproductive ratio. Journal of the Royal Society Interface, 2(4), 281–293. https://doi.org/10.1098/rsif.2005.0042
Jia, J., Ding, J., Liu, S., Liao, G., Li, J., Duan, B., Wang, G., & Zhang, R. (2020). Modeling the control of COVID-19: Impact of policy interventions and meteorological factors. Electronic Journal of Differential Equations, 2020(23), 1–24.
Kucharski, A. J., Russell, T. W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., & Eggo, R. M. (2020). Early dynamics of transmission and control of COVID-19: a mathematical modelling study. The Lancet Infectious Diseases, 20(5), 553–558. https://doi.org/10.1016/S1473-3099(20)30144-4
Layek, G. C. (2015). An introduction to Dynamical Systems and Chaos. In An Introduction to Dynamical Systems and Chaos (1st ed.). Springer India. https://doi.org/10.1007/978-81-322-2556-0
Müller, J., & Kuttler, C. (2015). Methods and Models in Mathematical Biology. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-642-27251-6
Murray, J. D. (2002). Mathematical Biology I: An Introduction (3rd ed., Vol. 17). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/b98868
Nainggolan, E. U. (2020). Virus Corona, Mahkota yang Membahayakan. Www.Djkn.Kemenkeu.Go.Id. https://www.djkn.kemenkeu.go.id/artikel/baca/13002/Virus-Corona-Mahkota-yang-Membahayakan.html
Rao, Y., Hu, D., & Huang, G. (2021). Dynamical Analysis of COVID-19 Epidemic Model with Individual Mobility. Communications in Mathematical Biology and Neuroscience, 1–18. https://doi.org/10.28919/cmbn/5189
Rois, M. A., Trisilowati, & Habibah, U. (2021a). Local Sensitivity Analysis of COVID-19 Epidemic with Quarantine and Isolation using Normalized Index. Telematika, 14(1), 13–24. http://dx.doi.org/10.35671/telematika.v14i1.1191
Rois, M. A., Trisilowati, & Habibah, U. (2021b). Optimal Control of Mathematical Model for COVID-19 with Quarantine and Isolation. International Journal of Engineering Trends and Technology, 69(6), 154–160. https://doi.org/10.14445/22315381/IJETT-V69I6P223
Sasmita, N. R., Ikhwan, M., Suyanto, S., & Chongsuvivatwong, V. (2020). Optimal control on a mathematical model to pattern the progression of coronavirus disease 2019 (COVID-19) in Indonesia. Global Health Research and Policy, 5. https://doi.org/10.1186/s41256-020-00163-2
Soewono, E. (2020). On the analysis of Covid-19 transmission in Wuhan, Diamond Princess and Jakarta-cluster. Communication in Biomathematical Sciences, 3(1), 9–18. https://doi.org/10.5614/CBMS.2020.3.1.2
Tahir, M., Ali Shah, S. I., Zaman, G., & Khan, T. (2019). Stability behaviour of mathematical model MERS corona virus spread in population. Filomat, 33(12), 3947–3960. https://doi.org/10.2298/FIL1912947T
Tang, B., Wang, X., Li, Q., Bragazzi, N. L., Tang, S., Xiao, Y., & Wu, J. (2020). Estimation of the Transmission Risk of the 2019-nCoV and Its Implication for Public Health Interventions. Journal of Clinical Medicine, 9(2), 462. https://doi.org/10.3390/jcm9020462
Usaini, S., Hassan, A. S., Garba, S. M., & Lubuma, J. M. S. (2019). Modeling the transmission dynamics of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) with latent immigrants. Journal of Interdisciplinary Mathematics, 22(6), 903–930. https://doi.org/10.1080/09720502.2019.1692429
WHO. (2020a). Novel Coronavirus. https://www.who.int/indonesia/news/novel-coronavirus/qa-for-public
WHO. (2020b). Pertimbangan-pertimbangan untuk karantina individu dalam konteks penanggulangan penyakit coronavirus (COVID-19). https://www.who.int/docs/default-source/searo/indonesia/covid19/who-2019-covid19-ihr-quarantine-2020-indonesian.pdf?sfvrsn=31d7cbd8_2
Yousefpour, A., Jahanshahi, H., & Bekiros, S. (2020). Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak. Chaos, Solitons and Fractals, 136. https://doi.org/10.1016/j.chaos.2020.109883
Zeb, A., Alzahrani, E., Erturk, V. S., & Zaman, G. (2020). Mathematical Model for Coronavirus Disease 2019 (COVID-19) Containing Isolation Class. BioMed Research International, 2020. https://doi.org/10.1155/2020/3452402
Downloads
Published
Issue
Section
License
Authors who publish articles in JTAM (Jurnal Teori dan Aplikasi Matematika) agree to the following terms:
- Authors retain copyright of the article and grant the journal right of first publication with the work simultaneously licensed under a CC-BY-SA or The Creative Commons Attribution–ShareAlike License.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).