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

Zhengyang Guo, Wenqi Yang, T. Yan, Y. Lin, Jiawei Wang
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Abstract

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.
美国COVID-19趋势分析与预测
本文主要分析和预测美国新冠肺炎疫情的一些情况。本文第一部分主要通过分析美国各县公开报告的COVID-19数据,分析COVID-19疾病死亡率与人口结构和密度的关系。我们发现人口密度与死亡率呈负相关。其次,通过我们介绍的一个叫做Shiny的软件,它可以根据现有的数据预测未来美国疫情的发展趋势。闪亮应用所呈现的过去数据的发展趋势与实际趋势相吻合,具有一定的可信度。在这项工作中,研究结果可以帮助我们更好地了解COVID-19。虽然分析对象是美国,但它可以作为许多国家的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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