We identified four distinct clusters of 151 countries based on COVID-19 prevalence rate from 1 February 2020 to 29 May 2021 by performing nonparametric K-means cluster analysis (KmL). We forecasted… Click to show full abstract
We identified four distinct clusters of 151 countries based on COVID-19 prevalence rate from 1 February 2020 to 29 May 2021 by performing nonparametric K-means cluster analysis (KmL). We forecasted future development of the clusters by using a nonlinear 3-parameter logistic (3PL) model, and found that peak points of development are the latest for Cluster I and earliest for Cluster IV. Based on partial least squares structural equation modeling (PLS-SEM) for the first twenty weeks after 1 February 2020, we found that the prevalence rate of COVID-19 has been significantly influenced by major elements of human systems. Better health infrastructure, more restriction of human mobility, higher urban population density, and less urban environmental degradation are associated with lower levels of prevalence rate (PR) of COVID-19. The most striking discovery of this study is that economic development hindered the control of COVID-19 spread among countries in the early stage of the pandemic. Highlights: While richer countries have advantages in health and other urban infrastructures that may alleviate the prevalence rate of COVID-19, the combination of high economic development level and low restriction on human mobility has led to faster spread of the virus in the first 20 weeks after 1 February 2020.
               
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