Zhu Hongjun, Li Yan, Jin Xuelian, Huang Jiangping, Liu Xin, Qian Ying, Tan Jindong
School of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Chongqing Engineering Research Center of Software Quality Assurance, Testing and Assessment, Chongqing 400065, China.
Appl Math Model. 2021 Jan;89:1983-1998. doi: 10.1016/j.apm.2020.08.056. Epub 2020 Sep 21.
The coronavirus disease 2019 (COVID-19) has grown up to be a pandemic within a short span of time. To investigate transmission dynamics and then determine control methodology, we took epidemic in Wuhan as a study case. Unfortunately, to our best knowledge, the existing models are based on the common assumption that the total population follows a homogeneous spatial distribution, which is not the case for the prevalence occurred both in the community and in hospital due to the difference in the contact rate. To solve this problem, we propose a novel epidemic model called SEIR-HC, which is a model with two different social circles (i.e., individuals in hospital and community). Using the model alongside the exclusive optimization algorithm, the spread process of COVID-19 epidemic in Wuhan city is reproduced and then the propagation characteristics and unknown data are estimated. The basic reproduction number of COVID-19 is estimated to be 7.9, which is far higher than that of the severe acute respiratory syndrome (SARS). Furthermore, the control measures implemented in Wuhan are assessed and the control methodology of COVID-19 is discussed to provide guidance for limiting the epidemic spread.
2019年冠状病毒病(COVID-19)在短时间内已发展成为一场大流行病。为了研究传播动态并确定控制方法,我们将武汉的疫情作为研究案例。遗憾的是,据我们所知,现有模型基于总人口遵循均匀空间分布这一常见假设,但由于社区和医院接触率不同,社区和医院出现的疫情并非如此。为解决这一问题,我们提出了一种名为SEIR-HC的新型流行病模型,该模型具有两个不同的社会圈子(即医院中的个体和社区中的个体)。使用该模型并结合专用优化算法,再现了武汉市COVID-19疫情的传播过程,进而估计了传播特征和未知数据。COVID-19的基本再生数估计为7.9,远高于严重急性呼吸综合征(SARS)。此外,对武汉实施的控制措施进行了评估,并讨论了COVID-19的控制方法,以提供限制疫情传播的指导。