In the USA, COVID-19 first infection cases were imported by external travelers. At the epidemic onset days, we assume that the disease partially spreads due to domestic passengers air transportation in its densely connected airport network. Taking into account all USA states, we arranged COVID-19 infected cases data in a convenient common time origin timeline as if the beginning of the epidemic would have occurred simultaneously in every state. Looking for a trend between cases and air passengers, we obtained with this timeline very good statistical Pearson and Spearman correlations between accumulated infected cases by state and a positive power of the product [Formula: see text], where [Formula: see text] is the domestic flight passengers (travelers) inflow by state before the epidemic and [Formula: see text] is its population. We also found a good correlation between percentages of urban area by state and their COVID-19 daily new cases growth rates at onset days.

中文翻译：

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将美国 COVID-19 流行病发病日的病例与各州国内航班旅客流入量相关联

在美国，COVID-19 首次感染病例是由外部旅行者输入的。在疫情爆发的日子里，我们假设该疾病的部分传播是由于其密集连接的机场网络中的国内旅客航空运输。考虑到美国所有州，我们将 COVID-19 感染病例数据安排在一个方便的共同时间起源时间线上，就好像流行病的开始会在每个州同时发生一样。寻找病例和航空乘客之间的趋势，我们通过这个时间线获得了非常好的统计 Pearson 和 Spearman 相关性，即各州累计感染病例与乘积的正幂 [公式：见文本]，其中 [公式：见文本] 是疫情前各州国内航班旅客（旅客）流入量，[公式：见正文]为其人口。