Analysis of COVID-19 death cases using SIR model and ARIMA model – pre and post pick program / Farzanah Ahmad Sukri

Ahmad Sukri, Farzanah (2022) Analysis of COVID-19 death cases using SIR model and ARIMA model – pre and post pick program / Farzanah Ahmad Sukri. [Student Project] (Submitted)

Abstract

In the year 2020, a significant risk to public health was discovered. The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic began in December 2019 in Wuhan City, Hubei Province, China, and spread to the rest of the world. According to the World Health Organization, this disease is known as COVID-19. The number of death cases increasing day by day. The goal is to analyse the trend of COVID-19 death cases rising or falling in Malaysia. Susceptible-Infected-Recovered (SIR) model and ARIMA model is used in this study to forecast the number of death cases in Malaysia. The prediction data has divided into three classes which is prediction before vaccination program has started, prediction after first and second dose and prediction after booster dose. SIR model result is suited to predicting epidemic trend while ARIMA model is the best model to comparing actual and predicted values. The models are compared, and the further research were recommended.

Metadata

Item Type: Student Project
Creators:
Creators
Email / ID Num.
Ahmad Sukri, Farzanah
UNSPECIFIED
Contributors:
Contribution
Name
Email / ID Num.
Advisor
Moktar, Balkiah
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Time-series analysis
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Science (Hons.) Management Mathematics
Keywords: COVID-19 death cases, SIR model, ARIMA model
Date: 2022
URI: https://ir.uitm.edu.my/id/eprint/83272
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