考虑不同时段接触数和疫苗接种因素的COVID-19动态SEIR模型

Dynamic SEIR Model of COVID-19 Considering Exposure and Vaccination at Different Time Periods

摘要: 随着COVID-19的肆虐传播，全球大部分国家都采取了相应的应对措施，通过构建合理的数学模型，可以科学地分析传染病在不同地区的发展趋势并对发展阶段进行合理的评估，具有重要的现实意义。自2020年12月初，部分国家开始接种新冠疫苗。本文建立了考虑不同时段接触数和疫苗接种因素的SEIRV模型，并对疫情的发展做了模拟。利用英国疫情数据进行验证，模型拟合结果与实际情况吻合的很好，表明模型具有较好的拟合能力。此外，根据新冠疫苗的接种特点，分析了接种率和接种时间对疫情的影响，结果表明第一针接种率和接种时间的影响较大，居民应尽可能普遍、尽早地接种疫苗。

Abstract: With the spread of COVID-19, most countries in the world have taken corresponding measures to deal with it. It is of great practical significance to scientifically analyze the development trend of infectious diseases in different regions and reasonably evaluate the development stages through the construction of reasonable mathematical models. Starting in early December 2020, some countries began to vaccinate against COVID-19. In this paper, a SEIRV model considering exposure and vaccination at different time periods was established, and the development of the epidemic was simulated. The results of the model fit well with the actual situation by using the epidemic data of the UK, indicating that the model has good fitting ability. In addition, according to the vaccination characteristics of the new coronavirus vaccine, the effects of vaccination rate and vaccination time on the epidemic were analyzed. The results showed that the first vaccination rate and vaccination time had a greater impact, and the population should be vaccinated as widely and as soon as possible.