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Prediction of the COVID-19 epidemic trends based on SEIR and AI models

机译:基于SEIR和AI模型的Covid-19流行病趋势预测

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In December 2019, the outbreak of a new coronavirus-caused pneumonia (COVID-19) in Wuhan attracted close attention in China and the world. The Chinese government took strong national intervention measures on January 23 to control the spread of the epidemic. We are trying to show the impact of these controls on the spread of the epidemic. We proposed an SEIR(Susceptible-Exposed-Infectious-Removed) model to analyze the epidemic trend in Wuhan and use the AI model to analyze the epidemic trend in non-Wuhan areas. We found that if the closure was lifted, the outbreak in non-Wuhan areas of mainland China would double in size. Our SEIR and AI model was effective in predicting the COVID-19 epidemic peaks and sizes. The epidemic control measures taken by the Chinese government, especially the city closure measures, reduced the scale of the COVID-19 epidemic.
机译:2019年12月,武汉爆发了新的冠状病毒导致肺炎(Covid-19)引起了中国和世界的密切关注。 中国政府在1月23日采取了强大的国家干预措施,以控制流行病的蔓延。 我们正试图展示这些控制对流行病的蔓延的影响。 我们提出了SEIR(易感暴露的暴露)模型,分析了武汉的流行病,并利用AI模型分析了非武汉地区的流行病。 我们发现,如果关闭,中国大陆非武汉地区的爆发将较大。 我们的SEIR和AI模型在预测Covid-19流行病峰和尺寸方面是有效的。 中国政府采取的疫情控制措施,尤其是城市关闭措施,减少了Covid-19流行病的规模。

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