Future of Mathematical Modelling: A Review of COVID-19 Infected Cases Using S-I-R Model A REVIEW OF COVID-19 INFECTED CASES USING S-I-R MODEL

Main Article Content

Azrul Azim Mohd Yunus
Arif Asraf Mohd Yunus
Muhammad Safwan Ibrahim
Shahrina Ismail

Abstract

The spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the R0 value from time to time, hoping that the virus will vanish one day.

Downloads

Download data is not yet available.

Article Details

How to Cite
1.
Mohd Yunus AA, Mohd Yunus AA, Ibrahim MS, Ismail S. Future of Mathematical Modelling: A Review of COVID-19 Infected Cases Using S-I-R Model: A REVIEW OF COVID-19 INFECTED CASES USING S-I-R MODEL. Baghdad Sci.J [Internet]. 2021Mar.30 [cited 2021Apr.13];18(1(Suppl.):0824. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5909
Section
article

References

Scarf PA. On the application of mathematical models in maintenance. Eur J Oper Res. 1997;99(6):493-506.

Chen D. Modeling the Spread of Infectious Diseases: A Review. Wiley Series in Probability and Statistics, John Wiley & Sons Inc. 2015;2015:19-42.

Momoh AA, Ibrahim MO, Tahir A, Adamu II. Application of homotopy analysis method for solving the SEIR models of epidemics. Nonlinear Analysis Differ Equ. 2015;3:53-68.

Rhodes T, Lancaster K. Mathematical models as public troubles in COVID-19 infection control: following the numbers. Health Sociol Rev. 2020;29(5):177-194.

Alsayed A, Sadir H, Kamil R, Sari H. Prediction of Epidemic Peak and Infected Cases for COVID-19 Disease in Malaysia, 2020. Int J Environ Res Public Health. 2020;17(6):e4076.

Jayanti P. A data-first approach to modelling Covid-19. medRxiv, 2020 (preprint)

Giuseppe CC, Carlo N, Corrado P. A Modified SIR Model for the COVID-19 Contagion in Italy. arXiv. 2020; 2003.14391v1.

Dimiter P. Analytical Parameter Estimation Of The Sir Epidemic Model. Applications To The Covid-19 Pandemic. arXiv. 2020; 2010.07000v1.

Adamu HA, Muhammad M, Jingi AMM, Usman MA. Mathematical modelling using improved SIR model with more realistic assumptions. Int J Eng Appl Sci. 2019;6(1):64-69.

Kermack WO, McKendrick AG. A contribution to the mathematical theory of epidemics. Proc R Soc Lond. 1927;700-721.

Weiss HH. The SIR model and the Foundations of Public Health. MATerials MATemàtics. 2013;3:1-17.

Hethcote HW. The Mathematics of Infectious Diseases. SIAM Rev. 2000;12(42): 599-653.

Shah AUM, Safri SNA, Thevadas R, Noordin NK, Rahman AA, Sekawi Z, et al. COVID-19 outbreak in Malaysia: Actions taken by the Malaysian government. Int J Infect Dis. 2020;97(8):108-116.

Salim N, Chan WH, Mansor S, Bazin NEN, Amaran S, Faudzi AAM, et al. COVID-19 epidemic in Malaysia: Impact of lockdown on infection dynamics. medRxiv, 2020:(preprint).

Liu Z, Magal P, Seydi O, Webb G. Understanding Unreported Cases in the COVID-19 Epidemic Outbreak in Wuhan, China, and the Importance of Major Public Health Interventions. Bio. 2020;9(3):50-61.

Baum J, Pasvol G, Carter R. The R0 journey: from 1950s malaria to COVID-19. Nature. 2020;582:488.

Neal P, Theparod T. The basic reproduction number, R0, in structured populations. Math Biosci. 2019;315(9):e108224.

Roberts M, Andreasen V, Lloyd A, Pellis L. Nine challenges for deterministic epidemic models. Epidemics. 2015;10(3):49-53.