Beyond the sine wave: unveiling climate-driven baseline mortality cycles.

Abstract

The relationship between temperature and mortality is well-established, with higher mortality rates occurring in moderate climates during winter. Studies on COVID-19 and influenza-related excess deaths often assume a sine-like wave pattern for baseline mortality. This study aims to assess the accuracy of this approximation in capturing the observed mortality pattern and explore its linkage with climate. Weekly mortality data from European regions (2000-2019) were modeled using the seasonal-trend decomposition procedure based on Loess. Cycles were grouped into clusters, and underlying trends were extracted using principal component analysis. Generalized linear models assuming a sine-like pattern were used to test predictive value. Cluster analysis divided the regional cycles approximately into continental and temperate climate regions, further subdivided into oceanic and Mediterranean. While the continental region exhibited a sine-like mortality pattern, it displayed modest deviations that compounded further south. The period of elevated winter mortality became shorter but more intense, while decreased summer mortality became more pronounced yet delayed. This study improves weekly estimations of excess mortality models by providing enhanced baselines. The deviation from the sine-like approximation mirrors the idealized outbreak pattern from epidemiological models with sharper surges and more gradual declines. The results point to winter infections, impacted by acquired immunity and weather conditions, as the primary drivers of fluctuations in mortality. In warmer regions, there is an apparent shift toward a lower number of overall infections within a compressed time span.