论文标题
流行病的死亡分布的尾巴
Tail of the distribution of fatalities in epidemics
论文作者
论文摘要
根据死亡人数来衡量流行病的大小是极其相关的数量。最近据称[Cirillo＆Taleb，Nature Physics 2020]，人类历史上主要流行病的规模分布“极度脂肪尾巴”，即渐近的权力法，对风险管理产生重要影响。重新分析了这些数据，我们发现，尽管死亡分布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。例如，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。还讨论了当前数据中的幂律尾巴以及限制的理论原因。
The size that an epidemic can reach, measured in terms of the number of fatalities, is an extremely relevant quantity. It has been recently claimed [Cirillo & Taleb, Nature Physics 2020] that the size distribution of major epidemics in human history is "extremely fat-tailed", i.e., asymptotically a power law, which has important consequences for risk management. Reanalyzing this data, we find that, although the fatality distribution 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. As an example, simulation of a log-normally distributed random variable provides synthetic data whose statistics are undistinguishable from the statistics of the empirical data. Theoretical reasons justifying a power-law tail as well as limitations in the current data are also discussed.
