Forecasting Dengue Outbreak Data Using ARIMA Model

Nur Aqilah Ali,Nur Syuhada Muhammat Pazil,Siti Hafawati Jamaluddin,Norwaziah Mahmud

doi:10.6007/ijarbss/v11-i6/10106

Nur Aqilah Ali, Nur Syuhada Muhammat Pazil + Show 2 more

Open Access

https://doi.org/10.6007/ijarbss/v11-i6/10106

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Abstract

Dengue fever is an internationally recognised virus that is spread by mosquitoes and can result in death. From recorded cases, Selangor has the highest rate of dengue infection among Malaysian populations. Corona disease (COVID-19), a new pandemic that has swept the globe, like Selangor, has prompted this report on the pattern of dengue cases during COVID-19 pandemic. Due to the new outbreak of COVID-19, the Movement Control Order (MCO) has been extended from time to time, and with most health resources at the state and federal levels being used to combat COVID-19, dengue control activities have been limited to a non-contact activity in outbreaks and hotspot areas. The importance of this study is to investigate the increase in dengue cases in Selangor because Selangor recorded the highest number of cases in Malaysia. Considering that there are not many studies conducted in Selangor, this study is important to predict dengue cases, and the authorities can take immediate action to overcome this problem. The aim of this research is to find the best ARIMA model for predicting the dengue cases in Selangor in the future. Several ARIMA models were used to test dengue cases data obtained in Selangor in order to achieve the objectives. The best model was calculated by comparing the Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Percent Error (MAPE) measurement errors. Then, the predicted number of dengue cases was calculated using the best model generated. The model for which the values of criteria are the smallest is considered as the best model. Hence ARIMA (1,1,2) was found to be the best model for predicting the dengue cases data series and this model is used to predict the number of dengue cases in Selangor with the smallest Mean Square Error (MSE) value of 12837.4327 and Root Mean Square Error (RMSE) value of 113.3024. The forecasted values showed a decreasing number of dengue cases. This study was carried out using R- studio software and excel. Further research can be conducted using another time series method, for example Holt-winters method.

Highlights

Dengue is one of the most serious and fast emerging tropical viruses that is transmitted by female mosquitoes mainly of the species Aedes aegypti and, to a lesser extent, Ae
This study was analysed using Autoregressive Integrated Moving Average (ARIMA) (1,1,2), since the model was chosen as the best method for assessing the actual dengue case data in Selangor from Epidemic Week 1 January 2018 to Epidemic Week 46 November 2020
As the new pandemic (COVID-19) occurred in early 2020, it shows that the number of dengue cases started to drop dramatically from Epidemic Week 3 to Epidemic Week 16

Summary

Introduction

Dengue is one of the most serious and fast emerging tropical viruses that is transmitted by female mosquitoes mainly of the species Aedes aegypti and, to a lesser extent, Ae. Albopictus. Mosquitoes can thrive in places with standing water, such as water tanks, buckets, and stagnant pools of water. According to the World Health Organization (WHO), about 2.5 billion people are currently living in dengue-infested areas. There are four dengue serotypes that cause dengue outbreaks designated as DEN-1, DEN-2, DEN-3, and DEN-4 (Martinez et al, 2011). The disease is endemic in 128 countries throughout the South Asia, South East-Asia, Africa, the Americas, the Western Pacific and Eastern Mediterranean Region. The disease is endemic in 128 countries throughout the South Asia, South East-Asia, Africa, the Americas, the Western Pacific and Eastern Mediterranean Region. (Salim et al, 2021)

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