Analysis Covid-19 Vaccine Effectiveness Using SIR Model

Mohd Rahimie Md Noor; Muhammad Fathillah Che Hassan; Muhammad Aidil Adzha Che Anuar; Sharifah Athirah Syed Adnan; Mohd Azry Abdul Malek; Ahmad Bukhari Mohd Yasin; Mohd Noor Azam Nafi; Mohd Zainuri Muhammad; Amri Ab Rahman

doi:10.47405/mjssh.v8i10.2536

Mohd Rahimie Md Noor Department of Mathematics, Faculty Mathematic and Computer Sciences Universiti Teknologi Mara Kelantan, 18500 Machang, Kelantan, Malaysia.
Muhammad Fathillah Che Hassan Department of Mathematics, Faculty Mathematic and Computer Sciences Universiti Teknologi Mara Kelantan, 18500 Machang, Kelantan, Malaysia.
Muhammad Aidil Adzha Che Anuar Department of Mathematics, Faculty Mathematic and Computer Sciences Universiti Teknologi Mara Kelantan, 18500 Machang, Kelantan, Malaysia.
Sharifah Athirah Syed Adnan Medical Department, Klinik Kesihatan Padang Luas, 22000 Jertih, Terengganu, Malaysia.
Mohd Azry Abdul Malek Department of Statistics, Faculty Mathematic and Computer Sciences Universiti Teknologi Mara Kelantan, 18500 Machang, Kelantan, Malaysia.
Ahmad Bukhari Mohd Yasin Department of Business, Faculty Business Management Universiti Teknologi Mara Kelantan, 15050 Kota Bharu, Kelantan, Malaysia.
Mohd Noor Azam Nafi Department of Statistics, Faculty Mathematic and Computer Sciences Universiti Teknologi Mara Kelantan, 15050 Kota Bharu, Kelantan, Malaysia.
Mohd Zainuri Muhammad Department of Business, Faculty Business Management Universiti Teknologi Mara Kelantan, 15050 Kota Bharu, Kelantan, Malaysia.
Amri Ab Rahman Department of Computer Science, Faculty Mathematic and Computer Sciences Universiti Teknologi Mara Kelantan, 18500 Machang, Kelantan, Malaysia.

DOI: https://doi.org/10.47405/mjssh.v8i10.2536

Keywords: SIR Model, Next Generation Matrix, Vaccinations

Abstract

Covid-19 is a new coronavirus disease that was labelled a pandemic by the World Health Organization (WHO) in March 2020. SIR Model is a versatile compartmental mathematical tool that may be used to simulate any pandemic dynamic, including the current Covid-19 out- break. In the conventional SIR model, the total population (N) is divided into three categories: susceptible(S), infected(I), and recovered(R). So, this research focused on finding the basic re- productive number, Ro of Covid-19 by using the Next Generation Matrix. Ro is greater than 1 means viruses begin to spread the population and Ro less than 1 means disease is about to vanish from the population. It is also analyze and compare the transmission of Covid-19 with and without vaccination. To apply this, the data from government websites is used to find the total number of cases and recover. With the help of mathematical software such as Maple to find the result of the graph. From the result produce from Maple, it can be observed that the slope of with vaccination is bigger than the slope of without vaccination. It clearly shows the comparison between them. The findings improved by having vaccination and then transmission rate low is good to decrease virus Covid-19 from infection.

Downloads

Download data is not yet available.

References

Badoual, M., Grammaticos, B., & Nakamura, G. (2021). Vaccination strategies for a seasonal epidemic: a simple sir model. Open Communications in Nonlinear Mathematical Physics, 1.

Covid Now (n.d.). COVIDNOW in Malaysia. Covid Now. https://covidnow.moh.gov.my/

Deng, J., Tang, S., & Shu, H. (2021). Joint impacts of media, vaccination and treatment on an epidemic filippov model with application to covid-19. Journal of Theoretical Biology, 523, 110698.

Department of Statistics Malaysia. (2021). Number of Population. Department of Statistics Malaysia.

Karabay, A., Kuzdeuov, A., Ospanova, S., Lewis, M., & Varol, H. A. (2021). A vaccination simulator for covid- 19: Effective and sterilizing immunization cases. IEEE Journal of Biomedical and Health Informatics, 25(12), 4317–4327.

Kementerian Kesihatan Malaysia. (2022). Nilai r malaysia. Retrieved from https://covid-19.moh.gov.my/kajian-dan-penyelidikan/nilai-r-malaysia.

Moghadas, S. M., Vilches, T. N., Zhang, K., Nourbakhsh, S., Sah, P., Fitzpatrick, M. C., & Galvani, A. P. (2021). Evaluation of covid-19 vaccination strategies with a delayed second dose. PLoS biology, 19(4), e3001211.

Roda, W. C., Varughese, M. B., Han, D., & Li, M. Y. (2020). Why is it difficult to accurately predict the covid-19 epidemic? Infectious disease modelling, 5, 271–281.

Salim, N., Chan, W. H., Mansor, S., Bazin, N. E. N., Amaran, S., Faudzi, A. A. M., Zainal, A., Huspi, S.H., Hooi, E.K.J., Shithil, S. M. (2020). Covid-19 epidemic in malaysia: Impact of lockdown on infection dynamics. MedRxiv. https://doi.org/10.1101/2020.04.08.20057463.

Ram, V., Schaposnik, L.P. (2021). A modifed age-structured SIR model for COVID-19 type viruses. Sci. Rep., 11, 15194. https://doi: 10.1038/s41598-021-94609-3.

Wong, W., Juwono, F. H., & Chua, T. H. (2021). Sir simulation of covid-19 pandemic in malaysia: Will the vaccination program be effective? arXiv preprint arXiv:2101.07494.