Publication:
Forecasting daily confirmed COVID-19 cases in Malaysia using ARIMA models

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dc.contributor.authorSarbhan Singh
dc.contributor.authorBala Murali Sundram
dc.contributor.authorKamesh Rajendran
dc.contributor.authorKian Boon Law
dc.contributor.authorTahir Aris
dc.contributor.authorHishamshah Ibrahim
dc.contributor.authorSarat Chandra Dass
dc.contributor.authorBalvinder Singh Gill
dc.date.accessioned2024-07-19T09:00:38Z
dc.date.available2024-07-19T09:00:38Z
dc.date.issued2020
dc.description.abstractIntroduction: The novel coronavirus infection has become a global threat affecting almost every country in the world. As a result, it has become important to understand the disease trends in order to mitigate its effects. The aim of this study is firstly to develop a prediction model for daily confirmed COVID-19 cases based on several covariates, and secondly, to select the best prediction model based on a subset of these covariates. Methodology: This study was conducted using daily confirmed cases of COVID-19 collected from the official Ministry of Health, Malaysia (MOH) and John Hopkins University websites. An Autoregressive Integrated Moving Average (ARIMA) model was fitted to the training data of observed cases from 22 January to 31 March 2020, and subsequently validated using data on cases from 1 April to 17 April 2020. The ARIMA model satisfactorily forecasted the daily confirmed COVID-19 cases from 18 April 2020 to 1 May 2020 (the testing phase). Results: The ARIMA (0,1,0) model produced the best fit to the observed data with a Mean Absolute Percentage Error (MAPE) value of 16.01 and a Bayes Information Criteria (BIC) value of 4.170. The forecasted values showed a downward trend of COVID-19 cases until 1 May 2020. Observed cases during the forecast period were accurately predicted and were placed within the prediction intervals generated by the fitted model. Conclusions: This study finds that ARIMA models with optimally selected covariates are useful tools for monitoring and predicting trends of COVID-19 cases in Malaysia.
dc.identifier.doi10.3855/jidc.13116
dc.identifier.urihttps://www.jidc.org/index.php/journal/article/view/33031083
dc.identifier.urihttps://repository.nih.gov.my/handle/123456789/675
dc.language.isoen
dc.publisherThe Journal of Infection in Developing Countries
dc.relation.ispartofThe Journal of Infection in Developing Countries
dc.relation.issn1972-2680
dc.relation.journalThe Journal of Infection in Developing Countries
dc.subjectCOVID-19
dc.subjectARIMA
dc.subjectforecast
dc.subjectpandemic
dc.titleForecasting daily confirmed COVID-19 cases in Malaysia using ARIMA models
dc.typejournal-article
dspace.entity.typePublication
oaire.citation.endPage976
oaire.citation.issue09
oaire.citation.startPage971
oaire.citation.volume14
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