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<p>This study examined the short-term association between the humidex—a composite index integrating ambient temperature and relative humidity—and the incidence of influenza A and B in Kawasaki City, Japan. Recognizing the limitations of analyzing temperature and humidity independently, we employed the humidex to better capture perceived environmental conditions. Daily influenza case data from March 2014 to December 2019 were sourced from the Kawasaki City Infectious Disease Surveillance System. A quasi-Poisson generalized linear model, combined with distributed lag non-linear models (DLNMs), was used to estimate exposure–response relationships, adjusting for multiple environmental confounders. A total of 181,895 influenza cases were reported during the study period, with influenza A accounting for 72.4% and influenza B for 27.6%. Compared to the median humidex (20.1), the cumulative relative risk (RR) for influenza A was significantly elevated at the 5th percentile (humidex: 3.0; RR: 4.91, 95% CI: 3.04–7.97) and moderately increased at the 95th percentile (humidex: 40.0; RR: 1.37, 95% CI: 0.59–3.22). Influenza B showed a similar but less pronounced pattern, with RRs of 3.79 (95% CI: 1.60–9.01) and 1.46 (95% CI: 0.93–2.28) at the respective percentiles. These findings indicate that low humidex values are associated with a heightened risk of influenza, particularly type A. Incorporating perceived humidity metrics into epidemiological models may enhance early warning systems and inform public health interventions during cold, dry conditions.</p>

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Association of humidex with influenza A and B incidence in Kawasaki City, Japan

  • 期刊论文

  • 发表日期：

    2025年11月10日

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  • Tri Bayu Purnama,
  • Keita Wagatsuma,
  • Reiko Saito

摘要

This study examined the short-term association between the humidex—a composite index integrating ambient temperature and relative humidity—and the incidence of influenza A and B in Kawasaki City, Japan. Recognizing the limitations of analyzing temperature and humidity independently, we employed the humidex to better capture perceived environmental conditions. Daily influenza case data from March 2014 to December 2019 were sourced from the Kawasaki City Infectious Disease Surveillance System. A quasi-Poisson generalized linear model, combined with distributed lag non-linear models (DLNMs), was used to estimate exposure–response relationships, adjusting for multiple environmental confounders. A total of 181,895 influenza cases were reported during the study period, with influenza A accounting for 72.4% and influenza B for 27.6%. Compared to the median humidex (20.1), the cumulative relative risk (RR) for influenza A was significantly elevated at the 5th percentile (humidex: 3.0; RR: 4.91, 95% CI: 3.04–7.97) and moderately increased at the 95th percentile (humidex: 40.0; RR: 1.37, 95% CI: 0.59–3.22). Influenza B showed a similar but less pronounced pattern, with RRs of 3.79 (95% CI: 1.60–9.01) and 1.46 (95% CI: 0.93–2.28) at the respective percentiles. These findings indicate that low humidex values are associated with a heightened risk of influenza, particularly type A. Incorporating perceived humidity metrics into epidemiological models may enhance early warning systems and inform public health interventions during cold, dry conditions.