论文标题
科学评论“传染性疾病的尾巴风险”
Scientific comment on "Tail risk of contagious diseases"
论文作者
论文摘要
Cirillo和Taleb [Nature Phys。 16，606-613（2020）]研究人类历史上主要流行病的大小，就死亡人数而言。他们使用72个流行病的数字，从雅典的瘟疫（公元前429年）到COVID-19（2019-2020），他们声称由此产生的死亡分布是``极度脂肪尾巴''，即无效的权力定律。这对风险具有重要的后果，因为死亡分布的平均值变得无限。重新分析相同的数据，我们发现，尽管数据可能与幂律尾巴兼容，但这些结果不是结论性的，而其他分布却没有脂肪，但可以很好地解释数据。对数正态分布的随机变量的仿真提供了合成数据，其统计数据与经验数据的统计数据无法区分。
Cirillo and Taleb [Nature Phys. 16, 606-613 (2020)] study the size of major epidemics in human history in terms of the number of fatalities. Using the figures from 72 epidemics, from the plague of Athens (429 BC) to the COVID-19 (2019-2020), they claim that the resulting fatality distribution is ``extremely fat-tailed'', i.e., asymptotically a power law. This has important consequences for risk, as the mean value of the fatality distribution becomes infinite. Reanalyzing the same data, we find that, although the data may be compatible with a power-law tail, these results are not conclusive, and other distributions, not fat-tailed, could explain the data equally well. Simulation of a log-normally distributed random variable provides synthetic data whose statistics are undistinguishable from the statistics of the empirical data.
