Abuhasel Khaled Ali, Khadr Mosaad, Alquraish Mohammed M
Department of Mechanical Engineering, College of Engineering University of Bisha Bisha Kingdom of Saudi Arabia.
Department of Civil Engineering, College of Engineering University of Bisha Bisha Kingdom of Saudi Arabia.
Comput Intell. 2022 Jun;38(3):770-783. doi: 10.1111/coin.12407. Epub 2020 Oct 5.
The novel coronavirus COVID-19 is spreading all across the globe. By June 29, 2020, the World Health Organization announced that the number of cases worldwide had reached 9 994 206 and resulted in more than 499 024 deaths. The earliest case of COVID-19 in the Kingdom of Saudi Arabia (KSA) was registered on March 2 in 2020. Since then, the number of infections as per the outcome of the tests increased gradually on a daily basis. The KSA has 182 493 cases, with 124 755 recoveries and 1551 deaths on June 29, 2020. There have been significant efforts to develop models that forecast the risks, parameters, and impacts of this epidemic. These models can aid in controlling and preventing the outbreak of these infections. In this regard, this article details the extent to which the infection cases, prevalence, and recovery rate of this pandemic are in the country and the predictions that can be made using the past and current data. The well-known classical SIR model was applied to predict the highest number of cases that may be realized and the flattening of the curve afterward. On the other hand, the ARIMA model was used to predict the prevalence cases. Results of the SIR model indicate that the repatriation plan reduced the estimated reproduction number. The results further affirm that the containment technique used by Saudi Arabia to curb the spread of the disease was efficient. Moreover, using the results, close interaction between people, despite the current measures remains a great risk factor to the spread of the disease. This may force the government to take even more stringent measures. By validating the performance of the applied models, ARIMA proved to be a good forecasting method from current data. The past data and the forecasted data, as per the ARIMA model provided high correlation, showing that there were minimum errors.
新型冠状病毒COVID-19正在全球范围内传播。截至2020年6月29日，世界卫生组织宣布全球病例数已达9994206例，导致超过499024人死亡。沙特阿拉伯王国最早的COVID-19病例于2020年3月2日登记。从那时起，检测结果显示的感染人数每天逐渐增加。截至2020年6月29日，沙特阿拉伯有182493例病例，其中124755例康复，1551例死亡。人们已经做出了巨大努力来开发预测这种流行病风险、参数和影响的模型。这些模型有助于控制和预防这些感染的爆发。在这方面，本文详细介绍了该国这种大流行病的感染病例、患病率和康复率情况，以及利用过去和当前数据所做的预测。采用了著名的经典SIR模型来预测可能出现的最高病例数以及随后曲线的平缓情况。另一方面，使用ARIMA模型来预测患病病例数。SIR模型的结果表明，遣返计划降低了估计的繁殖数。结果进一步证实，沙特阿拉伯用于遏制疾病传播的控制技术是有效的。此外，根据结果，尽管目前采取了措施，但人与人之间的密切互动仍然是疾病传播的一个重大风险因素。这可能迫使政府采取更加严格的措施。通过验证所应用模型的性能，ARIMA被证明是一种从当前数据来看很好的预测方法。根据ARIMA模型，过去的数据和预测数据具有高度相关性，表明误差最小。
