基于SEIAQR动力学模型的突发疫情预测
Forecast of Sudden Epidemic Based on SEIAQR Dynamic Model
DOI: 10.12677/AAM.2023.125262, PDF,    科研立项经费支持
作者: 常瑜洋, 郑梦凡, 杜彦斌*：河南科技大学数学与统计学院，河南 洛阳
关键词: SEIAQR模型；指数模型；基本再生数；灵敏度分析；SEIAQR Model； Exponential Model； Basic Regeneration Number； Sensitivity Analysis
摘要: 科学的预测传染病的发展规律对疫情防控至关重要。本文在经典的SEIR模型的基础上考虑到无症状感染者和隔离措施，提出SEIAQR动力学模型，且潜伏者和无症状感染者均具有传染性。基于第二代再生矩阵的方法计算基本再生数R0的表达式，并进行了灵敏度分析。数据拟合结果表明，SEIAQR模型预测结果与真实数据比较吻合，可以较好地描述疫情的早期传播规律。最后，根据参数敏感性分析结果为突发疫情防控提出了合理建议。
Abstract: Scientific prediction of the development trend of infectious diseases is essential for epidemic pre-vention and control. In this paper, we consider a SEIAQR dynamic model with asymptomatic in-fected persons and isolation chambers, and both the latent and asymptomatic infected persons are infectious. The expression of basic regeneration number is calculated based on the second genera-tion regeneration matrix method, and the sensitivity analysis is carried out. The data fitting results showed that the prediction results of SEIAQR model are in good agreement with the real data and can better describe the early transmission law of the epidemic. Finally, according to the results of parameter sensitivity analysis, some suggestions for epidemic prevention and control were put forward.
文章引用：常瑜洋, 郑梦凡, 杜彦斌. 基于SEIAQR动力学模型的突发疫情预测[J]. 应用数学进展, 2023, 12(5): 2613-2621. https://doi.org/10.12677/AAM.2023.125262

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