The association between weekly mean temperature and the epidemic of influenza across 122 countries/regions, 2014-2019

Abstract

The study examined the association between weekly mean temperature and influenza cases across 122 countries/regions (2014-2019) using a distributed lag non-linear model. We analyzed 3145206 cases of overall influenza (Flu-All), with influenza A (Flu-A) and influenza B (Flu-B) accounting for 73.49% and 26.51%, respectively. Within a lag of two weeks, Flu-All incidence demonstrated a bimodal temperature relationship, with peak relative risks (RR) of 6.02 (95% confidence interval [CI]: 1.92-20.77) at -8 ℃ and 3.08 (95% CI: 1.27-7.49) at 22 ℃. Flu-A exhibited a similar bimodal pattern, with RRs of 3.76 (95% CI: 2.39-5.91) at −8 ℃ and 2.08 (95% CI: 1.55-2.80) at 22 ℃. Flu-B demonstrated a single risk peak at 1 ℃ (RR = 4.48, 95% CI: 1.74-11.55). Subgroup analyses of climate zones revealed variations: tropical zones peaked at 12 ℃ (RR = 1.37, 95% CI: 1.08-1.74), while dry and temperate zones exhibited the highest risks at −5 ℃, with RRs of 4.49 (95% CI: 2.46-7.15) and 5.23 (95% CI: 3.17-8.64), respectively. Cold zones peaked at 1 ℃ (RR = 5.96, 95% CI: 3.76-9.43). Subgroup analyses of influenza transmission zones revealed variations: Africa showed a higher risk between 6 ℃ and 14 ℃, Asia showed a higher risk below 3 ℃, and Europe exhibited distinct risks of influenza peaks at −1 ℃ (Eastern Europe), 1 ℃ (Southwestern Europe), and −20 ℃ (Northern Europe). Elevated risks above 11 ℃ were identified in the Americas and Oceania. These findings establish a predictive framework for influenza outbreak preparedness by integrating regional temperature patterns with global climate variability.

Keywords

influenza / influenza subtype / temperature / climatic zones / influenza transmission zones

Fundings

This work was supported by the Nanjing Important Science & Technology Specific Projects (Grant No. 2021-11005 to P.H.).

Acknowledgments

We thank the virology laboratories that reported influenza results to FluNet and the World Health Organization for providing this critical information. The Global Historical Climatology Network database platform, which provides meteorological monitoring data to the public, is greatly appreciated. Our appreciation extends to the Our World In Data platform for providing global change data to the public.

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