The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported high number of positive cases and deaths, while some reported lower COVID-19 related cases and mortality. In this paper, the factors that could affect the risk of COVID-19 infection and mortality were analyzed in county level. An innovative method by using K-means clustering and several classification models is utilized to determine the most critical factors. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, population density, wind speed, longitude, and percent of uninsured people were the most significant attributes
翻译:COVID-19疾病迅速蔓延,在第一个阳性病例在中国确诊后近三个月,科罗纳病毒开始在全美国蔓延。一些州和县报告了大量呈阳性病例和死亡人数,而一些州和县报告与COVID-19有关的病例和死亡率较低。在本文件中,对县一级可影响COVID-19感染和死亡风险的因素进行了分析。采用了一种创新方法,即使用K手段集群和若干分类模型来确定最关键的因素。结果显示,平均温度、贫困人口百分比、肥胖、空气压力、人口密度、风速、经度和未保险人口百分比是最重要的特征。