Solving Nonlinear COVID-19 Mathematical Model Using a Reliable Numerical Method
DOI:
https://doi.org/10.30526/35.2.2818Abstract
This research aims to numerically solve a nonlinear initial value problem presented as a system of ordinary differential equations. Our focus is on epidemiological systems in particular. The accurate numerical method that is the Runge-Kutta method of order four has been used to solve this problem that is represented in the epidemic model. The COVID-19 mathematical epidemic model in Iraq from 2020 to the next years is the application under study. Finally, the results obtained for the COVID-19 model have been discussed tabular and graphically. The spread of the COVID-19 pandemic can be observed via the behavior of the different stages of the model that approximates the behavior of actual the COVID-19 epidemic in Iraq. In our study, the COVID-19 pandemic will disappear during the next few years within about five years, through the behavior of all stages of the epidemic presented in our research.
References
Wang, C.; Horby, P. W.; Hayden, F. G.; Gao. G. F. A novel coronavirus outbreak of global health concern. The lancet. 2020, 395(10223), 470-473.
Zhao,S.; Chen, H. Modeling the epidemic dynamics and control of COVID-19 outbreak in China. Quantitative biology. 2020, 8(1), 11-19.
Huang, Y.; Yang, L.; Dai, H.; Tian, F.; Chen, K. Epidemic situation and forecasting of COVID-19 in and outside China. Bull World Health Organ. 2020, 10. doi:10.2471/BLT.20.255158
JD, V. W.; Osinga. S.; Kuip. V. M.; Tanck. M.; Hanegraaf. M.; Pluymaekers. M.; et al. Forecasting hospitalization and ICU rates of the COVID-19 outbreak: An efficient SEIR model.[Submitted]. Bull World Health Organ. 2020.
Yang,W.; Zhang, D.; Peng, L.; Zhuge, C.; Hong,L. Rational evaluation of various epidemic models based on the COVID-19 data of China. Epidemics. 2021, 37, 100-501.
Li, M. Y. An introduction to mathematical modeling of infectious diseases (Vol. 2): Springer, 2018, ISBN 978-3-319-722121-7.
Lutz, C. S.; Huynh, M. P.; Schroeder, M.; Anyatonwu, S.; Dahlgren. F. S.; Lutz. C. S.; Huynh.M. P.; Schroeder, M.; Anyatonwu, S.; Dahlgren,F. S. G.; Danyluk, D.; Fernandez, S.K.; Greene,N.; Kipshidze. L. L., et al. Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples. BMC Public Health. 2019, 19(1), 1-12.
Basu,S.; Andrews, J. Complexity in mathematical models of public health policies: a guide for consumers of models. PLoS medicine. 2013, 10(10), e1001540.
Han, X. N.; De Vlas, S. J.; Fang, L. Q.; Feng, D.; Cao, W. C.; Habbema, J. D. F. Mathematical modelling of SARS and other infectious diseases in China: a review. Tropical Medicine & International Health. 2009, 14, 92-100.
Beauchemin, C. A.; Handel, A. A review of mathematical models of influenza A infections within a host or cell culture: lessons learned and challenges ahead. BMC Public Health. 2011, 11(1), 1-15.
Kermack, W. O.; McKendrick,A. G. Contributions to the mathematical theory of epidemics--I. 1927. Bulletin of mathematical biology. 1991, 53(1-2), 33-55.
Kermack, W. O.; McKendrick, A. G. Contributions to the mathematical theory of epidemics. II.—The problem of endemicity. Proceedings of the Royal Society of London. Series A, containing papers of a mathematical and physical character. 1932, 138(834), 55-83.
Diekmann, O.; Heesterbeek, H..; Britton, T. Mathematical tools for understanding infectious disease dynamics: Princeton University Press, 2012; ISBN: 9781400845620
Kretzschmar, M.; Van H. S.; Wallinga, J.; Van W. J. Ring vaccination and smallpox control. Emerging infectious diseases. 2004, 10(5), 832.
Rodrigues, H. S.; Monteiro, M. T. T.; Torres, D. F. Vaccination models and optimal control strategies to dengue. Mathematical biosciences. 2014, 247, 1-12.
Mohammed, M. A., Noor, N. F. M., Siri, Z., ; Ibrahim, A. I. N. (2015). Numerical solution for weight reduction model due to health campaigns in Spain. Paper presented at the AIP Conference Proceedings.
Sabaa, M. A.; Mohammed, M. A., Abd Almjeed, S. H. Approximate Solutions for Alcohol Consumption Model in Spain. Ibn AL-Haitham Journal For Pure and Applied Sciences. 2019, 32(3), 153-164.
Sabaa, M. A.; Mohammed, M. A. Approximate Solutions of Nonlinear Smoking Habit Model. Iraqi Journal of Science. 2020, 435-443.
Mohammed, S. J.; Mohammed, M. A. (2021). Runge-kutta Numerical Method for Solving Nonlinear Influenza Model. Paper presented at the Journal of Physics: Conference Series.
Huisen, R. W.; Abd Almjeed, S. H.; Mohammed, A. S. A Reliable Iterative Transform Method for Solving an Epidemic Model. Iraqi Journal of Science. 2021, 4839-4846.
Mohsen, A. A.; Al-Husseiny, H. F.; Zhou, X.; Hattaf, K. Global stability of COVID-19 model involving the quarantine strategy and media coverage effects. AIMS public Health. 2020, 7(3), 587.
Ahmed, A.; Salam, B.; Mohammad, M.; Akgul, A.; Khoshnaw, S. H. Analysis coronavirus disease (COVID-19) model using numerical approaches and logistic model. Aims Bioeng. 2020, 7(3), 130-146.
Mohammed, D. A.; Tawfeeq, H. M.; Ali, K. M.; Rostam, H. M. Analysis and Prediction of COVID-19 Outbreak by the Numerical Modelling. Iraqi Journal of Science. 2021, 62 (5), 1452-1459.
Yavuz, M.; Coşar, F. Ö.; Günay, F.; Özdemir, F. N. A new mathematical modeling of the COVID-19 pandemic including the vaccination campaign. Open Journal of Modelling and Simulation. 2021, 9(3), 299-321.
Yousif, M.S. and Kashiem, B.E., Solving Linear Boundary Value Problem Using Shooting Continuous Explicit Runge-Kutta Method. Ibn AL-Haitham Journal For Pure and Applied Science, 2017, 26(3), 324-330.
Mandal,M.; Jana, S.; Nandi, S. K.; Khatua, A.; Adak, S.; Kar, T. A model based study on the dynamics of COVID-19: Prediction and control. Chaos, Solitons & Fractals. 2020, 136, 109889.
Tay, K. G.; Kek, S. L.; Cheong, T. H.; Abdul-Kahar, R.; Lee, M. F. The Fourth Order Runge-Kutta Spreadsheet Calculator Using VBA Programing for Ordinary Differential Equations. Procedia-Social and Behavioral Sciences. 2015, 204, 231-239.
World Health Organization. Weekly Report. 2022, January 5 “Weekly epidemiological update”. WHO TEAM. Retrieved January 28, 2022, from https://www.who.int/publications/m/item/weekly-epidemiological-update---5-january-2021
World Health Organization Weekly Report. 2022, January 5 “Weekly epidemiological update”. WHO TEAM. Retrieved January 28, 2022, from https://covid19.who.int/region/emro/country/iq.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Ibn AL- Haitham Journal For Pure and Applied Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.
licenseTerms