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, Balvinder Singh Gill

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
154 Downloads (Pure)

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.

Original languageEnglish
Article number1504
JournalInternational Journal of Environmental Research and Public Health
Volume19
Issue number3
Early online date28 Jan 2022
DOIs
Publication statusPublished - 1 Feb 2022

Keywords

  • ARIMA
  • COVID-19
  • Forecast
  • Malaysia

ASJC Scopus subject areas

  • Pollution
  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

Fingerprint

Dive into the research topics of 'Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia'. Together they form a unique fingerprint.

Cite this