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遗传算法与改进的 SEIR 模型在中国预测 COVID-19 疫情趋势中的应用。

Application of genetic algorithm combined with improved SEIR model in predicting the epidemic trend of COVID-19, China.

机构信息

School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, China.

出版信息

Sci Rep. 2022 May 26;12(1):8910. doi: 10.1038/s41598-022-12958-z.

Abstract

Since the outbreak of the 2019 Coronavirus disease (COVID-19) at the end of 2019, it has caused great adverse effects on the whole world, and it has been hindering the global economy. It is ergent to establish an infectious disease model for the current COVID-19 epidemic to predict the trend of the epidemic. Based on the SEIR model, the improved SEIR models were established with considering the incubation period, the isolated population, and genetic algorithm (GA) parameter optimization method. The improved SEIR models can predict the trend of the epidemic situation better and obtain the more accurate epidemic-related parameters. Comparing some key parameters, it is capable to evaluate the impact of different epidemic prevention measures and the implementation of different epidemic prevention levels on the COVID-19, which has significant guidance for further epidemic prevention measures.

摘要

自 2019 年底 2019 年冠状病毒病(COVID-19)爆发以来,它对全世界造成了巨大的负面影响,阻碍了全球经济的发展。目前,迫切需要建立一种传染病模型来预测 COVID-19 疫情的趋势。基于 SEIR 模型,考虑潜伏期、隔离人群和遗传算法(GA)参数优化方法,建立了改进的 SEIR 模型。改进的 SEIR 模型可以更好地预测疫情趋势,获得更准确的疫情相关参数。通过比较一些关键参数,可以评估不同的防疫措施和不同的防疫水平对 COVID-19 的影响,这对进一步的防疫措施具有重要的指导意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6a/9135764/47a1d3a01499/41598_2022_12958_Fig1_HTML.jpg

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