With the severity of the COVID-19 outbreak, we characterize the nature of the growth trajectories of counties in the United States using a novel combination of spectral clustering and the correlation matrix. As the U.S. and the rest of the world are experiencing a severe second wave of infections, the importance of assigning growth membership to counties and understanding the determinants of the growth are increasingly evident. Subsequently, we select the demographic features that are most statistically significant in distinguishing the communities. Lastly, we effectively predict the future growth of a given county with an LSTM using three social distancing scores. This comprehensive study captures the nature of counties' growth in cases at a very micro-level using growth communities, demographic factors, and social distancing performance to help government agencies utilize known information to make appropriate decisions regarding which potential counties to target resources and funding to.
翻译:随着COVID-19疫情的严重性,我们利用光谱集群和关联矩阵的新组合,确定美国各州增长轨迹的性质,因为美国和世界其他地区正经历严重的第二波感染浪潮,将增长成员分配到各州和了解增长决定因素的重要性日益明显。随后,我们选择了在统计上对区分社区最为重要的人口特征。最后,我们利用三种社会平衡分数,有效地预测特定州未来增长情况,使用LSTM,预测特定州未来增长情况。这一全面研究利用增长社区、人口因素和社会平衡性表现,掌握了各州在非常微观一级增长的性质,以帮助政府机构利用已知信息,就哪些潜在的州将资源和资金用于哪些地方作出适当决定。