Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia

Cia Vei Tan, Sarbhan Singh, Chee Herng Lai, Ahmed Syahmi Syafiq Md Zamri, Sarat Chandra Dass, Tahir Bin Aris, Hishamshah Mohd Ibrahim and Balvinder Singh Gill
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Cia Vei Tan: Institute for Medical Research (IMR), Ministry of Health Malaysia, Shah Alam 40170, Malaysia
Sarbhan Singh: Institute for Medical Research (IMR), Ministry of Health Malaysia, Shah Alam 40170, Malaysia
Chee Herng Lai: Institute for Medical Research (IMR), Ministry of Health Malaysia, Shah Alam 40170, Malaysia
Ahmed Syahmi Syafiq Md Zamri: Institute for Medical Research (IMR), Ministry of Health Malaysia, Shah Alam 40170, Malaysia
Sarat Chandra Dass: School of Mathematical and Computer Sciences, Heriot-Watt University Malaysia, Putrajaya 62200, Malaysia
Tahir Bin Aris: Institute for Medical Research (IMR), Ministry of Health Malaysia, Shah Alam 40170, Malaysia
Hishamshah Mohd Ibrahim: Ministry of Health, Malaysia, Putrajaya 62590, Malaysia
Balvinder Singh Gill: Institute for Medical Research (IMR), Ministry of Health Malaysia, Shah Alam 40170, Malaysia

IJERPH, 2022, vol. 19, issue 3, 1-12

Abstract: With many countries experiencing a resurgence in COVID-19 cases, it is important to forecast disease trends to enable effective planning and implementation of control measures. This study aims to develop Seasonal Autoregressive Integrated Moving Average (SARIMA) models using 593 data points and smoothened case and covariate time-series data to generate a 28-day forecast of COVID-19 case trends during the third wave in Malaysia. SARIMA models were developed using COVID-19 case data sourced from the Ministry of Health Malaysia’s official website. Model training and validation was conducted from 22 January 2020 to 5 September 2021 using daily COVID-19 case data. The SARIMA model with the lowest root mean square error (RMSE), mean absolute percentage error (MAE) and Bayesian information criterion (BIC) was selected to generate forecasts from 6 September to 3 October 2021. The best SARIMA model with a RMSE = 73.374, MAE = 39.716 and BIC = 8.656 showed a downward trend of COVID-19 cases during the forecast period, wherein the observed daily cases were within the forecast range. The majority (89%) of the difference between the forecasted and observed values was well within a deviation range of 25%. Based on this work, we conclude that SARIMA models developed in this paper using 593 data points and smoothened data and sensitive covariates can generate accurate forecast of COVID-19 case trends.

Keywords: COVID-19; forecast; ARIMA; Malaysia (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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