Volume 14 - Journal of Control, Vol. 14, No. 5, Special Issue on COVID-19                   JoC 2021, 14 - Journal of Control, Vol. 14, No. 5, Special Issue on COVID-19: 89-96 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Zare Z, Vasegh N. Modeling and analysis of the spread of the COVID-19 pandemic using the classical SIR model. JoC 2021; 14 (S1) :89-96
URL: http://joc.kntu.ac.ir/article-1-821-en.html
1- Shahid Rajaee Teacher Training University
Abstract:   (4518 Views)
In this paper modeling, analysis and prediction of novel epidemic of COVID-19 are concerned to identify effective spread parameters of it in Iran. For this purpose, the basic susceptible-infected-removed (SIR) model is used which has two parameters: the infection rate and remove rate. Because of several maximum points in the Iranian data and the single peak of the SIR model, it is not possible to use a model with the same parameters for all times. For this reason, the Iranian data is divided into five time periods and then the parameters of each period are obtained. In addition to adapting to the behavior of disease-related data, these time periods are consistent with the realities of society, including the timing of government decisions and the changing patterns of individuals in society. Finally, an analysis based on the obtained parameters and the trend of disease spread in the continuation of this year is presented. Since the economic, social and health consequences of this virus are catastrophic, using the results of mathematical modeling to identify the factors affecting the spread of the disease can be a step towards future actions to control the disease.
Full-Text [PDF 646 kb]   (4070 Downloads)    
Type of Article: Research paper | Subject: COVID-19
Received: 2020/12/30 | Accepted: 2021/02/13 | Published: 2021/02/28

References
1. C.Sohrabi, Z.Alsafiz, N,O'Neill, M.Khan, A.Kerwan, A.Al-Jabir, C.Iosifidis, R.Agha, ''World health organization declares global emergency: a review of the 2019 novel coronavirus (COVID-19) '' Int J Surg 2020; 76:71-6. doi: 10.1016/j.ijsu.2020. 02.034 [DOI:10.1016/j.ijsu.2020.02.034]
2. F. He, Y.Deng, W.Li. ''Coronavirus disease 2019 (COVID-19): what we know, ''J Med Virol 2020. doi: 10.1002/jmv.25766. [DOI:10.1002/jmv.25766]
3. L.Wang, Y. Wang, D.Ye, Qq.Liu, ''A review of the 2019 novel coronavirus (COVID-19) based on current evidence, '' Int J Antimicrob Agents 2020:105948.doi:10.1016/j.ijantimicag.2020.105948. [DOI:10.1016/j.ijantimicag.2020.105948]
4. P.Pulla, ''Covid-19: India imposes lockdown for 21 days and cases rise 2020. '' doi: 10.1136/bmj.m1251,2020. [DOI:10.1136/bmj.m1251]
5. H.Hethcote. ''The mathematics of infectious diseases, '' SIAM Rev. 42(4):599-653, 2020. [DOI:10.1137/S0036144500371907]
6. W. O. Kermack and G. Anderson McKendrick, ''Contributions to the mathematical theory of epidemics I. 1927,'' Bull. Math. Biol. vol. 53, pp. 33_55, Jan. 1991. [DOI:10.1016/S0092-8240(05)80040-0]
7. N. T. J. Baily, ''The Mathematical Theory of Infectious Diseases'', 2nd, New York, NY, USA: Hafner, 1975.
8. R. R. Tang, ''The singularly perturbed boundary value problem of non-linear integro-differential system,'' Ann. Differ. Equ, vol. 4, pp. 407_412, Dec. 2004.
9. M. Iannelli, M. Martcheva, and X. Z. Li, ''Strain replacement in an epidemic model with superinfection and perfect vaccination,'' Math. Biosci. vol. 195, no. 1, pp. 23_46, 2005. [DOI:10.1016/j.mbs.2005.01.004]
10. J. Liu, Y. Tang, and Z. R. Yang, ''The spread of disease with birth and death on networks,'' J. Stat. Mech. Theory Exp. vol. 2004, no. 8, 2004, Art.no. P08008. [DOI:10.1088/1742-5468/2004/08/P08008]
11. C.Dye, ''Epidemiology: Modeling the SARS Epidemic, '' Science, vol. 300, no. 5627, pp. 1884_1885, 2003. [DOI:10.1126/science.1086925]
12. X. N. Han, S. J. De Vlas, L. Q. Fang, D. Feng, W. C. Cao, and J. D. F. Habbema, ''Mathematical modelling of SARS and other infectious diseases in China: A review,'' vol. 14, no. s1, pp. 92_100, 2009, doi: 10.1111/j.1365-3156.2009. [DOI:10.1111/j.1365-3156.2009.02244.x]
13. O.Bjørnstad, BF. Finkenstädt, BT. Grenfell, ''Dynamics of measles epidemics: estimating scaling of transmission rates using a time series SIR model. '' Ecol Monogr 72:169-184, 2002. [DOI:10.1890/0012-9615(2002)072[0169:DOMEES]2.0.CO;2]
14. G.Giordano, F.Blanchini, R.Bruno, P.Colaneri, A.Di Filippo, A.Di Matteo, M.Colaneri, ''Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy. '' Nature Medicine 2020:1-6. [DOI:10.1038/s41591-020-0883-7]
15. C.Hou, J.Chen, Y. Zhou, L. Hua, J.Yuan, S.He, J. Zhang, '' The effectiveness of quarantine of Wuhan city against the corona virus disease 2019 (COVID-19): A well-mixed SEIR model analysis. '' Journal of medical virology.2019. [DOI:10.1002/jmv.25827]
16. C.Anastassopoulou, L.Russo, A.Tsakris, C.Siettos, ''Data-based analysis, modelling and forecasting of the COVID-19 outbreak. '' PloS one, 15(3). E0230405, 2020. [DOI:10.1371/journal.pone.0230405]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Control

Designed & Developed by : Yektaweb