On Statistical Analysis of Forecasting COVID-19 for the Upcoming Months in the Kingdom of Saudi Arabia

Bachioua Lahcene
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引用次数: 1

Abstract

This paper presents a statistical analysis using fitted prediction models that revealed a high exponential growth in the number of confirmed cases, deaths, and treated case processes based on our model predictions and the results of experimental COVID-19 predictions. The studies aimed to build inductive statistical models using the automatic integrated mean regression model methodology, and its preferred method for tracking data that represent the spread of the epidemic and then effectively predicting its numbers over the next six months, in addition to the number of deaths and cases that responded to recovery treatment using ARIMA. Moreover, the number of infected cases per day is expected to stabilize less than 500, daily deaths are less than 15, and this situation will continue until the largest number of people are vaccinated in order to obtain herd immunity, and control the causes of the spread of the epidemic such as human gatherings and friction. Among individuals, in addition to obtaining the appropriate vaccine in the future, especially since the Kingdom of Saudi Arabia is waiting for this year's pilgrims from inside and outside the Kingdom, the results of this work will be useful for practitioners in various fields of theoretical and applied sciences.
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沙特阿拉伯王国未来几个月预测新冠肺炎的统计分析
本文根据我们的模型预测和新冠肺炎实验预测结果,使用拟合预测模型进行统计分析,揭示了确诊病例、死亡人数和治疗病例过程的高指数增长。这些研究旨在使用自动综合平均回归模型方法及其首选方法建立归纳统计模型,以跟踪代表疫情传播的数据,然后有效预测未来六个月的疫情数字,以及使用ARIMA进行康复治疗的死亡人数和病例数。此外,预计每天的感染病例数将稳定在500例以下,每日死亡人数将低于15人,这种情况将持续到最多的人接种疫苗,以获得群体免疫,并控制人类聚会和摩擦等疫情传播的原因。在个人中,除了在未来获得适当的疫苗外,特别是由于沙特阿拉伯王国正在等待今年来自王国内外的朝圣者,这项工作的结果将对理论和应用科学各个领域的从业者有用。
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