论文标题
关于在COVID-19案件分布中的权力法的出现
On the Emergence of a Power Law in the Distribution of COVID-19 Cases
论文作者
论文摘要
据报道，2019年1月21日，美国第一个确认的2019年冠状病毒疾病病例（COVID-19）。到2020年3月底，美国有180000年以上确认的病例在2000多个县分布。我们发现该发行版的右尾巴表现出一项权力法，而帕累托指数接近一个。我们调查了涉及吉布拉特定律的1900案例增长的简单模型是否可以解释该权力定律的出现。对该模型进行了校准以匹配（i）确认病例的增长率，以及（ii）在每个县内共有19个covid-19的时间长度。因此，经过校准，该模型生成了帕累托指数的功率定律，几乎完全等于3月底的确认案件的分布直接估计的指数。
The first confirmed case of Coronavirus Disease 2019 (COVID-19) in the US was reported on January 21, 2020. By the end of March, 2020, there were more than 180000 confirmed cases in the US, distributed across more than 2000 counties. We find that the right tail of this distribution exhibits a power law, with Pareto exponent close to one. We investigate whether a simple model of the growth of COVID-19 cases involving Gibrat's law can explain the emergence of this power law. The model is calibrated to match (i) the growth rates of confirmed cases, and (ii) the varying lengths of time during which COVID-19 had been present within each county. Thus calibrated, the model generates a power law with Pareto exponent nearly exactly equal to the exponent estimated directly from the distribution of confirmed cases across counties at the end of March.
