Modelling and estimation of COVID-19 pandemic with the face mask and vaccination
crossref(2022)
摘要
Abstract COVID-19 is a public health emergency for human beings and brings some very harmful consequences in social and economic fields. In order to model COVID-19 and develop the effective controlling measures, this paper proposes an SEIR-type epidemic model with the mask wearing and the vaccination. Firstly, the effective reproduction number and the threshold conditions are obtained by analyzing the dynamical behaviors of the proposed epidemic model. Secondly, selecting the data of South Korea from January 20, 2022 to March 21, 2022, all model parameters are defined and estimated. Finally, based on the estimated parameters, the numerical simulations are conducted and the simulation suitably fit with the presented model. The results show that the mask wearing ratio, the effectiveness of the certain face mask, the vaccination rate and effectiveness of vaccination for the susceptible individuals play an important role in preventing and controlling COVID-19 pandemic. The face mask wearing is associated with 83% and 90% reductions in the numbers of the cumulative cases and the newly confirmed cases respectively after sixty days while the face mask wearing rate increases 15%, and the vaccination rate is associated with 75% and 80% reductions in the numbers of the cumulative cases and the newly confirmed cases respectively after sixty days while the vaccination rate augments 15\%. Therefore, the effect of the mask wearing on reducing the cumulative cases and the newly confirmed cases is more remarkable than that of the vaccination, this means the disease control departments should strongly recommended that peoples should wear the face mask to prevent themselves from becoming infected when the vaccination willingness of individuals is relative low. The face mask wearing still the primary measure to prevent and control the transmission of COVID-19 pandemic.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要