A simple application of Runge-Kutta 4thorder method in predicting the COVID-19 herd immunity in Malaysia

• Published in: AIP Conference Proceedings
• Main Author: Latif N.S.A.; Latip A.S.A.; Murzaki S.F.S.
• Format: Conference paper
• Language: English
• Published: American Institute of Physics 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194142014&doi=10.1063%2f5.0208536&partnerID=40&md5=5ca17cab838f1806952bad59b5d1f7cc

There has been a fast spread of the coronavirus disease 2019 (COVID-2019) over the globe, and vaccination is the most efficient strategy to combat this disease. More than ten COVID-19 vaccines have been approved internationally, but only five have been used in Malaysia. According to the Director-General of Health Malaysia, Tan Sri Dr Noor Hisham Abdullah, the government aimed to achieve herd immunity for COVID19 by 2021. To achieve herd immunity, at least 80% of the total population in Malaysia, which is approximately 26.2 million people, needed to be vaccinated. Program Immunisasi COVID-19 Kebangsaan (PICK) has started its first implementation on 18th March 2021. Therefore, this study used a simple Runge-Kutta 4th Order method to predict when Malaysia would achieve the herd immunity of COVID19 disease. With few assumptions, the logistic growth model was used to represent the vaccinated population in Malaysia. It was then solved using Runge-Kutta order 4 (RK4) in Excel and MATLAB (curve fitting tool). This numerical exercise showed that approximately 24.23 million people would receive COVID-19 vaccination by the end of 2021. In comparing this result, a Matlab using curve fitting tool was also used to predict the number of vaccinated people based on the current vaccination data from CovidNow with only 26 million vaccinated people. The result showed that Malaysia failed to achieve its targeted plan to achieve herd immunity for COVID19 b y 2021. To conclude, the government should ramp up its PICK program and revise its current SOP to curb this COVID-19 disease spread. © 2024 Author(s).