Most studies of seasonal variation in mortality rely on aggregated death counts at population level. In this paper, we use individual data to present a series of models for different aspects of seasonal variation. The models are fitted to a variety of international pensioner data sets and suggest a high degree of commonality across countries with different climates and different health systems. The power of individual life-history survival modelling allows the detection of seasonal patterns in even modest-sized portfolios. We measure the tendency for seasonal fluctuations to increase with age, and we again find strong similarities between geographically distinct populations. We further find that seasonal effects are generally uncorrelated with gender, but that low-income pensioners can suffer greater seasonal swings than high-income ones. Finally, we propose a single-parameter measure for the extent to which winter mortality is a spike and summer mortality is a shallower trough, and show results for a variety of data sets.

中文翻译：

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使用个人数据模拟季节性死亡率

大多数关于死亡率季节性变化的研究依赖于人口水平的汇总死亡人数。在本文中，我们使用单个数据针对季节性变化的不同方面提出了一系列模型。这些模型适用于各种国际养老金领取者数据集，并表明在不同气候和不同卫生系统的国家之间具有高度的共性。个人生活史生存建模的强大功能允许在即使是中等规模的投资组合中检测季节性模式。我们测量季节性波动随年龄增加的趋势，我们再次发现地理上不同的人群之间有很强的相似性。我们进一步发现季节性影响通常与性别无关，但低收入养老金领取者可能比高收入领取者遭受更大的季节性波动。最后，