Forecasting the spread of the COVID-19 pandemic in Saudi Arabia using ARIMA prediction model under current public health interventions.
Forecasting the spread of the COVID-19 pandemic in Saudi Arabia using ARIMA prediction model under current public health interventions.
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DOI：
10.1016/j.jiph.2020.06.001
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发表时间：
2020-07
影响因子：
6.7
通讯作者：
Al-Fakih EA
中科院分区：
文献类型：
--
作者：
Alzahrani SI;Aljamaan IA;Al-Fakih EA
全球每日新增冠状病毒感染病例数量的大幅增加令人震惊，几位研究人员目前正在使用各种数学和基于机器学习的预测模型来估计这一大流行病的未来趋势。在这项工作中，我们采用自回归综合移动平均（ARIMA）模型来预测未来四周沙特阿拉伯的COVID-19病例的预期每日数量。我们首先进行了四种不同的预测模型;自回归模型，移动平均，两者的组合（阿尔马）和集成阿尔马（ARIMA），以确定最佳模型拟合，我们发现ARIMA模型优于其他模型。预测结果显示，如果不采取严格的预防和控制措施来限制COVID-19的传播，沙特阿拉伯的趋势将继续增长，并可能在四周内达到每天7668例新病例和超过127，129例累计每日病例。这表明，预计将有近200万穆斯林在7月中旬前往沙特阿拉伯麦加和麦地那两个圣城进行的副朝和朝觐可能会暂停。为了避免这种情况，提出了一套极端的预防和控制措施。
The substantial increase in the number of daily new cases infected with coronavirus around the world is alarming, and several researchers are currently using various mathematical and machine learning-based prediction models to estimate the future trend of this pandemic. In this work, we employed the Autoregressive Integrated Moving Average (ARIMA) model to forecast the expected daily number of COVID-19 cases in Saudi Arabia in the next four weeks. We first performed four different prediction models; Autoregressive Model, Moving Average, a combination of both (ARMA), and integrated ARMA (ARIMA), to determine the best model fit, and we found out that the ARIMA model outperformed the other models. The forecasting results showed that the trend in Saudi Arabia will continue growing and may reach up to 7668 new cases per day and over 127,129 cumulative daily cases in a matter of four weeks if stringent precautionary and control measures are not implemented to limit the spread of COVID-19. This indicates that the Umrah and Hajj Pilgrimages to the two holy cities of Mecca and Medina in Saudi Arabia that are supposedly scheduled to be performed by nearly 2 million Muslims in mid-July may be suspended. A set of extreme preventive and control measures are proposed in an effort to avoid such a situation.
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