1. Time Series Forecasting of COVID-19 Infections in United Arab Emirates using ARIMA
- Author
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Sumyah Alkatheri, Shaikhah Alhmoudi, and Leila Ismail
- Subjects
2019-20 coronavirus outbreak ,Series (mathematics) ,Coronavirus disease 2019 (COVID-19) ,Computer science ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Pandemic ,Econometrics ,Autoregressive integrated moving average ,Time series - Abstract
Machine learning time series models have been used to predict COVID-19 pandemic infections. Based on the public dataset from Johns Hopkins, we present a novel framework for forecasting COVID-19 infections. We implement our framework for the United Arab Emirates (UAE) and develop autoregressive integrated moving average (ARIMA) time series forecast model. To the best of our knowledge, this is the only study to forecast the infections in UAE using the time series model.
- Published
- 2020
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