Department of Applied Mathematics, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Department of Mathematics, University of Ruhuna, Matara 81000, Sri Lanka.
Viruses. 2023 May 19;15(5):1201. doi: 10.3390/v15051201.
COVID-19, which broke out globally in 2019, is an infectious disease caused by a novel strain of coronavirus, and its spread is highly contagious and concealed. Environmental vectors play an important role in viral infection and transmission, which brings new difficulties and challenges to disease prevention and control. In this paper, a type of differential equation model is constructed according to the spreading functions and characteristics of exposed individuals and environmental vectors during the virus infection process. In the proposed model, five compartments were considered, namely, susceptible individuals, exposed individuals, infected individuals, recovered individuals, and environmental vectors (contaminated with free virus particles). In particular, the re-positive factor was taken into account (i.e., recovered individuals who have lost sufficient immune protection may still return to the exposed class). With the basic reproduction number R0 of the model, the global stability of the disease-free equilibrium and uniform persistence of the model were completely analyzed. Furthermore, sufficient conditions for the global stability of the endemic equilibrium of the model were also given. Finally, the effective predictability of the model was tested by fitting COVID-19 data from Japan and Italy.
2019 年在全球爆发的 COVID-19 是一种由新型冠状病毒引起的传染病，其传播具有高度传染性和隐匿性。环境载体在病毒感染和传播中起着重要作用，这给疾病防控带来了新的困难和挑战。本文根据病毒感染过程中暴露个体和环境载体的传播功能和特征，构建了一类微分方程模型。在提出的模型中，考虑了五个隔室，即易感个体、暴露个体、感染个体、恢复个体和环境载体（污染有游离病毒颗粒）。特别地，考虑了再阳性因素（即已失去足够免疫保护的恢复个体仍可能回到暴露类）。利用模型的基本再生数 R0，完全分析了无病平衡点的全局稳定性和模型的一致持久性。此外，还给出了模型地方病平衡点全局稳定性的充分条件。最后，通过拟合日本和意大利的 COVID-19 数据，验证了模型的有效可预测性。
