The unprecedented coronavirus disease 2019(COVID-19)pandemic is still raging(in year 2021)in many countries worldwide.Various response strategies to study the characteristics and distributions of the virus in various ...The unprecedented coronavirus disease 2019(COVID-19)pandemic is still raging(in year 2021)in many countries worldwide.Various response strategies to study the characteristics and distributions of the virus in various regions of the world have been developed to assist in the prevention and control of this epidemic.Descriptive statistics and regression analysis on COVID-19 data from different countries were conducted in this study to compare and evaluate various regression models.Results showed that the extreme random forest regression(ERFR)model had the best performance,and factors such as population density,ozone,median age,life expectancy,and Human Development Index(HDI)were relatively influential on the spread and diffusion of COVID-19 in the ERFR model.In addition,the epidemic clustering characteristics were analyzed through the spectral clustering algorithm.The visualization results of spectral clustering showed that the geographical distribution of global COVID-19 pandemic spread formation was highly clustered,and its clustering characteristics and influencing factors also exhibited some consistency in distribution.This study aims to deepen the understanding of the international community regarding the global COVID-19 pandemic to develop measures for countries worldwide to mitigate potential large-scale outbreaks and improve the ability to respond to such public health emergencies.展开更多
基金This work was supported in part by the National University Student Innovation and Entrepreneurship in Training Program of China(No.202110373044)the National Natural Science Foundation of China(No.71801108)+1 种基金the Laboratory Opening Project Fund of Huaibei Normal University(No.2021sykf041)the Special Needs Project of Huaibei Normal University(No.2021zlgc147)。
文摘The unprecedented coronavirus disease 2019(COVID-19)pandemic is still raging(in year 2021)in many countries worldwide.Various response strategies to study the characteristics and distributions of the virus in various regions of the world have been developed to assist in the prevention and control of this epidemic.Descriptive statistics and regression analysis on COVID-19 data from different countries were conducted in this study to compare and evaluate various regression models.Results showed that the extreme random forest regression(ERFR)model had the best performance,and factors such as population density,ozone,median age,life expectancy,and Human Development Index(HDI)were relatively influential on the spread and diffusion of COVID-19 in the ERFR model.In addition,the epidemic clustering characteristics were analyzed through the spectral clustering algorithm.The visualization results of spectral clustering showed that the geographical distribution of global COVID-19 pandemic spread formation was highly clustered,and its clustering characteristics and influencing factors also exhibited some consistency in distribution.This study aims to deepen the understanding of the international community regarding the global COVID-19 pandemic to develop measures for countries worldwide to mitigate potential large-scale outbreaks and improve the ability to respond to such public health emergencies.
