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一种利用改进的易感-暴露-感染-康复模型和开放数据源对沙特阿拉伯COVID-19大流行进行建模的混合方法。

A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources.

作者信息

Ahmad Naim, Qahmash Ayman

机构信息

Information Systems, King Khalid University, Abha, SAU.

出版信息

Cureus. 2021 Dec 8;13(12):e20279. doi: 10.7759/cureus.20279. eCollection 2021 Dec.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has caused the world to operate uncharacteristically for almost the last two years. Governments across the globe have taken different control measures to eradicate it. The Oxford COVID-19 Government Response Tracker (OxCGRT) provides open access data for different countries on 20 control measures, including numerous aggregated indices. This paper employs the modified Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiology model to study the COVID-19 pandemic in Saudi Arabia. The modification has been achieved by including control measures and the infectiousness of exposed compartment. A hybrid approach has been used to estimate and incorporate control measures. Initially, a composite control measure has been derived from OxCGRT data to make an attempt to fit the COVID-19 pattern in Saudi Arabia. The derived model has proven to be satisfactory through statistical tests. Nonetheless, the model patterns do not resemble the reported patterns more closely. Hence, a second heuristic approach has been utilized to devise effective control measures from the reported pattern of COVID-19 from the Saudi government agency. A satisfactory model was derived utilizing this approach with successful validation through statistical tests. Also, the model patterns more closely resemble the reported patterns of COVID-19 cases. This hybrid approach proves more robust and ensures the validity of model parameters better. The R naught (R) value with the current control measures has varied from 0.515 to 1.892, with a mean value of 1.119, and is presently less than 1. The threshold herd immunity, in the absence of any control measure, is estimated to be 47.12% with an R value of 1.89 and would end up infecting 76.32% of the population. The scenario analysis with gradual partial and complete relaxations up to December 31, 2021, shows that the peaks are likely to occur in 2022; therefore, Saudi Arabia must continue to inoculate its population to eradicate COVID-19.

摘要

在过去近两年的时间里,2019冠状病毒病(COVID-19)大流行使得整个世界的运转变得异乎寻常。全球各国政府采取了不同的防控措施来根除这一疾病。牛津COVID-19政府应对追踪器(OxCGRT)为不同国家提供了关于20项防控措施的开放获取数据,包括众多综合指标。本文采用改进的易感-暴露-感染-康复(SEIR)流行病学模型来研究沙特阿拉伯的COVID-19大流行情况。改进之处在于纳入了防控措施以及暴露人群的传染性。采用了一种混合方法来估计和纳入防控措施。首先,从OxCGRT数据中得出了一项综合防控措施,试图拟合沙特阿拉伯的COVID-19疫情模式。通过统计检验证明所推导的模型是令人满意的。然而,模型模式与报告模式的相似程度并不高。因此,采用了第二种启发式方法,根据沙特政府机构报告的COVID-19模式来制定有效的防控措施。利用这种方法得出了一个令人满意的模型,并通过统计检验成功验证。此外,模型模式更接近于报告的COVID-19病例模式。这种混合方法证明更为稳健,能更好地确保模型参数的有效性。在当前防控措施下,基本传染数(R)值在0.515至1.892之间变化,平均值为1.119,目前小于1。在没有任何防控措施的情况下,估计阈值群体免疫率为47.12%,R值为1.89,最终将导致76.32%的人口感染。对截至2021年12月31日逐步部分和完全放松防控措施的情景分析表明,疫情高峰可能出现在2022年;因此,沙特阿拉伯必须继续为其民众接种疫苗以根除COVID-19。

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