Characterizing the seasonal influenza disease burden attributable to climate variability: A nationwide time-series modelling study in Japan, 2000-2019.

Environ Res

Department of Global Health, School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Published: December 2024

AI Article Synopsis

  • This study investigates how non-optimal ambient temperature and humidity affect influenza cases in Japan, emphasizing geographical differences in vulnerability.
  • The analysis utilized data from 2000-2019 across all 47 prefectures, using a sophisticated statistical model to establish exposure relationships and estimate disease burden.
  • Results revealed that cold and dry conditions significantly raise influenza risk, with specific cumulative relative risks identified, particularly in central and northern regions of Japan, while demographic and socioeconomic factors didn't show strong correlations.

Article Abstract

Background: Ambient temperature and humidity are established environmental stressors with regard to influenza infections; however, mapping disease burden is difficult owing to the complexities of the underlying associations and differences in vulnerable population distributions. In this study, we aimed to quantify the burden of influenza attributable to non-optimal ambient temperature and absolute humidity in Japan considering geographical differences in vulnerability.

Methods: The exposure-lag-response relationships between influenza incidence, ambient temperature, and absolute humidity in all 47 Japanese prefectures for 2000-2019 were quantified using a distributed lag non-linear model for each prefecture; the estimates from all the prefectures were then pooled using a multivariate mixed-effects meta-regression model to derive nationwide average associations. Association between prefecture-specific indicators and the risk were also examined. Attributable risks were estimated for non-optimal ambient temperature and absolute humidity according to the exposure-lag-response relationships obtained before.

Results: A total of 25,596,525 influenza cases were reported during the study period. Cold and dry conditions significantly increased influenza incidence risk. Compared with the minimum incidence weekly mean ambient temperature (29.8 °C) and the minimum incidence weekly mean absolute humidity (20.2 g/m), the cumulative relative risks (RRs) of influenza in cold (2.5 °C) and dry (3.6 g/m) conditions were 2.79 (95% confidence interval [CI]: 1.78-4.37) and 3.20 (95% CI: 2.37-4.31), respectively. The higher RRs for cold and dry conditions were associated with geographical and climatic indicators corresponding to the central and northern prefectures; demographic, socioeconomic, and health resources indicators showed no clear trends. Finally, 27.25% (95% empirical CI [eCI]: 5.54-36.35) and 32.35% (95% eCI: 22.39-37.87) of all cases were attributable to non-optimal ambient temperature and absolute humidity (6,976,300 [95% eCI: 1,420,068-9,306,128] and 8,280,981 [95% eCI: 8,280,981-9,693,532] cases), respectively.

Conclusions: These findings could help identify the most vulnerable populations in Japan and design adaptation policies to reduce the attributable burden of influenza due to climate variability.

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Source
http://dx.doi.org/10.1016/j.envres.2024.120065DOI Listing

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