COVID-19 epidemic in Malaysia: Impact of lock-down on infection dynamics

Naomie Salim; Weng Howe Chan; Shuhaimi Mansor; Nor Erne Nazira Bazin; Safiya Amaran; Ahmad Athif Mohd Faudzi; Anazida Zainal; Sharin Hazlin Huspi; Eric Jiun Hooi Khoo; Shaekh Mohammad Shithil

Therefore, in this work, we try to predict the projection of COVID-19 outbreak cases in Malaysia using three mathematical models; Curve Fitting Model with Probability Density Function and Skewness Effect, SIR model, System Dynamic model. We used a combination of actual daily data and analysis of patterns and trends from previous cases in other countries to predict the projection of upcoming cases for Malaysia. The projection serves to support the needs for lockdown period and activity to mitigate the spread of coronavirus cases. Accurate prediction is very crucial to support right decision for upcoming lockdown period and activity. For instance, extended period for MCO can be decided based on increasing and descending trends of COVID-19 cases. This paper is organized in five sections. Section 2 reviews some prediction modelling concepts and their related works. Section 3 describes the three prediction methods (Curve Fitting Model, SIR Model and System Dynamics) used in this study and their experimental assumptions made. Finally, Section 4 presents results obtained by each of these prediction models and Section 5 concludes the paper.