Estimation and prediction of the multiply exponentially decaying daily case fatality rate of COVID-19.

IF 2.5 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Journal of Supercomputing Pub Date : 2023-01-01 Epub Date: 2023-02-23 DOI:10.1007/s11227-023-05119-0
Soobin Kwak, Seokjun Ham, Youngjin Hwang, Junseok Kim
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引用次数: 0

Abstract

The spread of the COVID-19 disease has had significant social and economic impacts all over the world. Numerous measures such as school closures, social distancing, and travel restrictions were implemented during the COVID-19 pandemic outbreak. Currently, as we move into the post-COVID-19 world, we must be prepared for another pandemic outbreak in the future. Having experienced the COVID-19 pandemic, it is imperative to ascertain the conclusion of the pandemic to return to normalcy and plan for the future. One of the beneficial features for deciding the termination of the pandemic disease is the small value of the case fatality rate (CFR) of coronavirus disease 2019 (COVID-19). There is a tendency of gradually decreasing CFR after several increases in CFR during the COVID-19 pandemic outbreak. However, it is difficult to capture the time-dependent CFR of a pandemic outbreak using a single exponential coefficient because it contains multiple exponential decays, i.e., fast and slow decays. Therefore, in this study, we develop a mathematical model for estimating and predicting the multiply exponentially decaying CFRs of the COVID-19 pandemic in different nations: the Republic of Korea, the USA, Japan, and the UK. We perform numerical experiments to validate the proposed method with COVID-19 data from the above-mentioned four nations.

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估计和预测 COVID-19 的乘指数衰减日病例死亡率。
COVID-19 疾病的传播对全世界的社会和经济产生了重大影响。在 COVID-19 大流行爆发期间,采取了许多措施,如学校关闭、社会疏远和旅行限制。目前,随着我们进入后 COVID-19 世界,我们必须为未来再次爆发大流行病做好准备。在经历了 COVID-19 大流行之后,当务之急是确定大流行的结论,以恢复正常状态并规划未来。2019 年冠状病毒病(COVID-19)的病死率(CFR)值较小,这是决定疾病大流行结束的有利特征之一。在 COVID-19 大流行爆发期间,病死率在多次上升后有逐渐下降的趋势。然而,由于大流行疫情包含多种指数衰减,即快速衰减和慢速衰减,因此很难使用单一指数系数来捕捉大流行疫情随时间变化的死亡率。因此,在本研究中,我们建立了一个数学模型,用于估计和预测 COVID-19 大流行在不同国家(大韩民国、美国、日本和英国)的多指数衰减 CFR。我们利用上述四个国家的 COVID-19 数据进行了数值实验,以验证所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Supercomputing
Journal of Supercomputing 工程技术-工程:电子与电气
CiteScore
6.30
自引率
12.10%
发文量
734
审稿时长
13 months
期刊介绍: The Journal of Supercomputing publishes papers on the technology, architecture and systems, algorithms, languages and programs, performance measures and methods, and applications of all aspects of Supercomputing. Tutorial and survey papers are intended for workers and students in the fields associated with and employing advanced computer systems. The journal also publishes letters to the editor, especially in areas relating to policy, succinct statements of paradoxes, intuitively puzzling results, partial results and real needs. Published theoretical and practical papers are advanced, in-depth treatments describing new developments and new ideas. Each includes an introduction summarizing prior, directly pertinent work that is useful for the reader to understand, in order to appreciate the advances being described.
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