标题： 死亡尖峰与出生谷值之间的耦合。 第一部分：证据 显示英文标题

标题： Coupling between death spikes and birth troughs. Part 1: Evidence

摘要： 在1889-1890年流感大流行之后，医疗统计学先驱雅克·贝尔蒂隆注意到，在大规模死亡高峰之后，大约9个月后出生人数出现了一次下降，这次下降比由于超额死亡导致的人口变化所能解释的幅度要大得多。此外还可以注意到，这次下降随后几个月内出现了出生率的反弹。然而，尽管做出了这一观察，贝尔蒂隆并没有进一步探讨。从那时起，尽管在此期间发生了几次新的大规模死亡高峰，这一现象却没有被重新研究。本文的目的是分析这些新案例，以更好地理解这种死亡与出生的耦合现象。最大的死亡高峰发生在最近的流感大流行期间，即1918年和1920年，其他一些则是由1923年东京地震和2001年9月11日的双塔袭击引发的。我们将看到，这些事件中的第一个确实导致了出生率的额外下降，而9/11事件则没有。这种差异突显了附带受害者的关键作用。在最后一部分中展示了当前耦合如何导致预测；它能够以统一的方式解释迄今为止分别研究的效果，例如热浪对出生率的影响。因此，似乎在出生率波动的随机表现之下，实际上隐藏着解释性因素。 显示英文摘要

摘要： In the wake of the influenza pandemic of 1889-1890 Jacques Bertillon, a pioneer of medical statistics, noticed that after the massive death spike there was a dip in birth numbers around 9 months later which was significantly larger than that which could be explained by the population change as a result of excess deaths. In addition it can be noticed that this dip was followed by a birth rebound a few months later. However having made this observation, Bertillon did not explore it further. Since that time the phenomenon was not revisited in spite of the fact that in the meanwhile there have been several new cases of massive death spikes. The aim here is to analyze these new cases to get a better understanding of this death-birth coupling phenomenon. The largest death spikes occurred in the wake of more recent influenza pandemics in 1918 and 1920, others were triggered by the 1923 earthquakes in Tokyo and the Twin Tower attack on September 11, 2001. We shall see that the first of these events indeed produced an extra dip in births whereas the 9/11 event did not. This disparity highlights the pivotal role of collateral sufferers. In the last section it is shown how the present coupling leads to predictions; it can explain in a unified way effects which so far have been studied separately, as for instance the impact on birth rates of heat waves. Thus, it appears that behind the random appearance of birth rate fluctuations there are in fact hidden explanatory factors.