Mohammad Aidid, Edre and Zainal Abidin, Muhammad 'Adil and Ab Rahman, Jamalludin (2020) Forecasting Malaysia COVID-19 Incidence based on Movement Control Order using ARIMA and Expert Modeler. IIUM Medical Journal Malaysia (IMJM), Vol. 19 (2). pp. 1-4. ISSN 1823-4631
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Abstract
Coronavirus disease (COVID-19) is a novel pandemic that affects every other country in the world. Various countries have adopted control measures involving restriction of movement. Several studies have used mathematical modelling to predict the dynamic of this pandemic. Forecasting techniques can be used to predict the incidence cases for the short term. The study aims to forecast the COVID-19 incidence using the Auto Regressive Integrated Moving Average (ARIMA) method. MATERIALS AND METHODS: Using publicly available data, we performed a forecast of Malaysia COVID-19 new cases using Expert Modeler Method in SPSS and ARIMA model in R to predict COVID-19 cases in Malaysia. We compare 3 different time frames based on different Movement Control Order (MCO) period. We compare the model fit and prediction across models. RESULTS: All models show static cases for each MCO 7-day prediction. For prediction until 12 May, the third MCO time frame shows the best model fit for both techniques. Both software shows a stationary trend of cases of below 100. CONCLUSION: These MCO models have shown to stabilize the rate of new cases. Further sub analysis and quality of data is needed to improve the accuracy of the model.
Item Type: | Article (Review) |
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Additional Information: | 7187/81920 |
Uncontrolled Keywords: | Coronavirus disease ; COVID-19 ; a novel pandemic |
Subjects: | R Medicine > RA Public aspects of medicine > RA643 Communicable Diseases and Public Health |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Medicine > Department of Community Medicine (Effective: 1st January 2011) |
Depositing User: | Dr Muhammad Adil Zainal Abidin |
Date Deposited: | 30 Jul 2020 11:34 |
Last Modified: | 02 Apr 2021 09:22 |
URI: | http://irep.iium.edu.my/id/eprint/81920 |
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