Narrow Results

In this paper, a stochastic SEIR epidemic model on heterogeneous networks is established, and the law of large numbers and the central limit theorem of the epidemic process are obtained. By using the random time transformation, the mean behavior of the epidemic process is analyzed, that is, the solution of the deterministic model is given. Further, the asymptotic distribution of the final size is provided. Then, the network-based stochastic epidemic model is applied to a COVID-19 infection at a construction site in Qingpu District of Shanghai, and the parameters of the model are estimated by fitting the data of confirmed cases. Based on the estimated parameter values, the intervention measure implemented at the site is assessed by numerical simulations, and we find that the intervention does not effectively curb the development of the disease. In addition, simulation results show that the asymptotic approximation for the final size is good. The impact of the detecting or symptomatic rate on the final size is also analyzed by numerical studies. The results indicate that as the rate increases, the mean of the final size decreases and the variance increases, which is more conducive to controlling the spread of the disease.

Traditional Chinese medicine (TCM) plays an active role in the prevention and control of COVID-19 epidemic. Currently, there are many TCM intervention programs for the COVID-19 infections, and the clinical effect is better. However, there are some problems in the design of actual clinical programs. This paper analyzes the advantages and disadvantages of various TCM interventions for the COVID-19 infection from the perspective of scientific and clinical research. We can scientifically use the TCM theory to guide and design clinical research, and come up with real data and treatment, to provide new models and explorations for the research of the modernization of Chinese medicine.