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建模 COVID-19 小规模爆发。

Modeling of the Small-Scale Outbreak of COVID-19.

机构信息

Department of Digital Media Technology, College of Computer Science and Technology, Huaqiao University, Xiamen, China.

Fujian Key Laboratory of Big Data Intelligence and Security, Huaqiao University, Xiamen, China.

出版信息

Front Public Health. 2022 Jul 1;10:907814. doi: 10.3389/fpubh.2022.907814. eCollection 2022.

Abstract

With the improvement of treatment and prevention methods, many countries have the pandemic under control. Different from the globally large-scale outbreak of COVID-19 in 2020, now the outbreak in these countries shows new characteristics, which calls for an effective epidemic model to describe the transmission dynamics. Meeting this need, first, we extensively investigate the small-scale outbreaks in different provinces of China and use classic compartmental models, which have been widely used in predictions, to forecast the outbreaks. Additionally, we further propose a new version of cellular automata with a time matrix, to simulate outbreaks. Finally, the experimental results show that the proposed cellular automata could effectively simulate the small-scale outbreak of COVID-19, which provides insights into the transmission dynamics of COVID-19 in China and help countries with small-scale outbreaks to determine and implement effective intervention measures. The countries with relatively small populations will also get useful information about the epidemic from our research.

摘要

随着治疗和预防方法的改进,许多国家已经控制了疫情。与 2020 年 COVID-19 在全球范围内大规模爆发不同,现在这些国家的疫情呈现出新的特点,这就需要一个有效的疫情模型来描述其传播动态。为了满足这一需求,我们首先广泛调查了中国不同省份的小规模疫情,并使用经典的房室模型(已广泛用于预测)对疫情进行预测。此外,我们进一步提出了一种带有时间矩阵的新型元胞自动机,以模拟疫情爆发。最后,实验结果表明,所提出的元胞自动机能够有效地模拟 COVID-19 的小规模爆发,这为我们深入了解 COVID-19 在我国的传播动态提供了帮助,并有助于疫情规模较小的国家确定和实施有效的干预措施。人口相对较少的国家也可以从我们的研究中获得有关疫情的有用信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/9283974/13818adbc430/fpubh-10-907814-g0001.jpg

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