Redefining Influenza Transmission Seasonality Using the Novel Seasonality Index

TL;DR

This study introduces a novel seasonality index to better understand influenza transmission patterns by integrating climate, behavioral, and epidemiological data, revealing strong correlations with infection rates and epidemic dynamics.

Contribution

The paper presents a new multidisciplinary seasonality index that captures complex interactions influencing influenza epidemics across different regions and climate zones.

Findings

Strong correlation between infection rates and the seasonality index.

Winter duration correlates with low-frequency epidemic peaks.

Enhanced characterization of influenza seasonality in relation to atmospheric conditions.

Abstract

The impact of climate conditions on influenza epidemiology has mostly been studied by addressing a singular aspect of transmission and a climate variable correlating to it. As climate change unfolds at an unprecedented rate, we urgently need new multidisciplinary approaches that can embrace complexity of disease transmission in the fast-changing environment and help us better understand the implications for health. In this study, we have implemented a novel seasonality index to capture a vast network of climate, infectious, and socio-behavioural mechanisms influencing a seasonal influenza epidemic. We hypothesize that intricate, region-specific behavioural patterns are cross regulating the influenza spreading and dynamics of epidemics with changes in meteorological conditions within a specific season. To better understand the phenomena, we analysed weekly surveillance data from temperate European countries and redefined seasonal transitions using the seasonality index. This approach allowed us to characterize influenza seasonality more accurately in relation to specific atmospheric conditions. Key findings include: i) a strong correlation between influenza infection rates and the seasonality index across different climate zones and social groups, and ii) a high linear correlation between winter duration, determined by the seasonality index, and the time scale of low-frequency peaks in the infection rates power spectral density.