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Prediction of COVID-19 Outbreak in China and Optimal Return Date for University Students Based on Propagation Dynamics

机译:基于传播动力学的中国COVID-19暴发预测及大学生最佳归还日期

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摘要

On 12 December 2019, a novel coronavirus disease, named COVID-19, began to spread around the world from Wuhan, China. It is useful and urgent to consider the future trend of this outbreak. We establish the 4+1 penta-group model to predict the development of the COVID-19 outbreak. In this model, we use the collected data to calibrate the parameters, and let the recovery rate and mortality change according to the actual situation. Furthermore, we propose the BAT model, which is composed of three parts: simulation of the return rush (Back), analytic hierarchy process (AHP) method, and technique for order preference by similarity to an ideal solution (TOPSIS) method, to figure out the best return date for university students. We also discuss the impacts of some factors that may occur in the future, such as secondary infection, emergence of effective drugs, and population flow from Korea to China.
机译:2019年12月12日,一种名为COVID-19的新型冠状病毒病从中国武汉开始在世界范围内传播。考虑到这一暴发的未来趋势是非常有用和紧迫的。我们建立4 + 1五群模型来预测COVID-19爆发的发展。在该模型中,我们使用收集到的数据来校准参数,并让恢复率和死亡率根据实际情况而变化。此外,我们提出了BAT模型,该模型由三部分组成:返回急动的模拟(Back),层次分析法(AHP)和通过类似于理想解决方案(TOPSIS)的方法进行订单偏好的技术。确定大学生的最佳归还日期。我们还讨论了将来可能发生的某些因素的影响,例如继发感染,有效药物的出现以及从韩国到中国的人口流动。

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