Revisiting Influenza Transmission Patterns Through a Novel Seasonality Index

Modeling of influenza spreading and better assessment of transmission dynamics and factors that modulate it is of great importance to public health. However, the traditional way of studying the climate impact on the influenza dynamics is by focusing on a singular aspect of transmission mechanics and a specific climate attribute that correlates to it. Contrary to that, we hypothesize that season-specific shifts in meteorological conditions, coupled with changes in region-specific behavioral patterns, are cross regulating the dynamics of the influenza transmission. To gain understanding of these proposed mechanisms, we have used the novel seasonality index (DTRT) (Lalic et al., 2022), to design a better-defined transition of meteorological seasons.

To ensure climate and demographic diversity, we collected influenza and climate data from several European and Asian countries, including Albania, Bangladesh, Estonia, Latvia, Luxembourg, Serbia, Slovenia, and Singapore. Annual influenza virus dynamics were analyzed using country-level, open-access weekly data provided by the World Health Organization (WHO). The weekly influenza data included: i) number of individuals tested, ii) number of influenza-positive cases, iii) number of influenza-negative cases, and iv) breakdown by specific influenza virus types. Historical daily weather data for selected locations were retrieved from NOAA’s Integrated Surface Database (ISD).

Using the novel index, and weekly time-series for influenza surveillance data, we have characterized the influenza seasonality, in respect to atmospheric conditions more accurately. Our key findings include a strong correlation between the infection rates of influenza and the novel seasonality index across various climate zones and social groups, as well as a high linear correlation in for the duration of the winter season, as estimated using the novel seasonality index, and the time scale of the low-frequency peaks in the power spectral density of infection rates. These research findings will enhance our potential to assess the impact of accelerating climate change on the transmission of influenza and wider impacts on health. 

Literature

Lalić B, Fitzjarrald DR, Sremac AF, Marčić M, Petrić M (2022) Identifying crop and orchard growing stages using conventional temperature and humidity reports. Atmosphere 13(5):700. https://doi.org/10.3390/atmos13050700

Acknowledgements:
This research is supported by the Ministry of Science, Technological
Development and Innovation of the Republic of Serbia (Grants No.
‪451-03-137/2025-03/ 200125 & 451-03-136/2025-03/ 200125)