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Analysis and prediction of COVID-19 trends in the United States

This paper is mainly to analyze and predict some situations of COVID-19 in the United States. The first part of this paper mainly analyzes the relationship between the mortality rate of COVID-19 disease and population structure and density by analyzing the publicly reported COVID-19 data from various counties in the United States. We found that there is a negative correlation between population density and death rate. Secondly, through a software called Shiny we introduced, it can predict the future development trend of the epidemic in the United States based on the existing data. The development trend of the past data presented by the shiny application matches with the actual trend, which has a certain credibility. In this work, the result can help us to have a better understanding of COVID-19. Although the analysis object is the United States, it can be used as a reference for many countries.