Modelling seasonal mortality with individual data

Stephen J. Richards*, Stefan J. Ramonat, Gregory T. Vesper, Torsten Kleinow

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)864-878
Number of pages15
JournalScandinavian Actuarial Journal
Issue number10
Early online date16 Jun 2020
Publication statusPublished - 25 Nov 2020


  • excess winter mortality
  • Seasonal mortality
  • survival model

ASJC Scopus subject areas

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty


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