SQEIR：一种流行病病毒传播分析与预测模型。
SQEIR: An epidemic virus spread analysis and prediction model.
作者信息
Wu Yichun, Sun Yaqi, Lin Mugang
机构信息
College of Computer Science and Technology, Hengyang Normal University, Hengyang, 421002, China.
Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, 421002, China.
出版信息
Comput Electr Eng. 2022 Sep;102:108230. doi: 10.1016/j.compeleceng.2022.108230. Epub 2022 Aug 10.
In 2019, a new strain of coronavirus pneumonia spread quickly worldwide. Viral propagation may be simulated using the Susceptible Infectious Removed (SIR) model. However, the SIR model fails to consider that separation of patients in the COVID-19 incubation stage entails difficulty and that these patients have high transmission potential. The model also ignores the positive effect of quarantine measures on the spread of the epidemic. To address the two flaws in the SIR model, this study proposes a new infectious disease model referred to as the Susceptible Quarantined Exposed Infective Removed (SQEIR) model. The proposed model uses the weighted least squares for the optimal estimation of important parameters in the infectious disease model. Based on these parameters, new differential equations were developed to describe the spread of the epidemic. The experimental results show that this model exhibits an accuracy 6.7% higher than that of traditional infectious disease models.
2019年，一种新型冠状病毒肺炎在全球迅速传播。可以使用易感-感染-康复（SIR）模型来模拟病毒传播。然而，SIR模型没有考虑到新冠病毒潜伏期患者的隔离存在困难，且这些患者具有较高的传播潜力。该模型还忽视了隔离措施对疫情传播的积极作用。为解决SIR模型中的这两个缺陷，本研究提出了一种新的传染病模型，即易感-隔离-暴露-感染-康复（SQEIR）模型。所提出的模型使用加权最小二乘法对传染病模型中的重要参数进行最优估计。基于这些参数，建立了新的微分方程来描述疫情的传播。实验结果表明，该模型的准确率比传统传染病模型高6.7%。
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