论文标题
美国Covid-19美国：轨迹和第二次涌现行为
COVID-19 in the United States: Trajectories and second surge behavior
论文作者
论文摘要
本文介绍了一个数学框架，用于确定美国Covid-19病例的第二次涌动行为。在此框架内，一种灵活的算法方法为每个状态选择一组转弯点，计算它们之间的距离，并确定每个状态是否在（还是超过）第一或第二次激增。然后，使用归一化时间序列之间的适当距离来进一步分析一个月一个月的病例轨迹之间的关系。我们的算法表明，有31个州正在经历第二次潮流，而10个最大州中的4个仍处于第一次激增，案件计数从未减少。该分析可以有助于强调对Covid-19的最成功和最不成功的状态响应。
This paper introduces a mathematical framework for determining second surge behavior of COVID-19 cases in the United States. Within this framework, a flexible algorithmic approach selects a set of turning points for each state, computes distances between them, and determines whether each state is in (or over) a first or second surge. Then, appropriate distances between normalized time series are used to further analyze the relationships between case trajectories on a month-by-month basis. Our algorithm shows that 31 states are experiencing second surges, while 4 of the 10 largest states are still in their first surge, with case counts that have never decreased. This analysis can aid in highlighting the most and least successful state responses to COVID-19.
