医学
混淆
季节性流感
空气污染
人口
空气污染物
空气质量指数
相对湿度
环境卫生
免疫学
人口学
内科学
生物
地理
气象学
2019年冠状病毒病(COVID-19)
疾病
生态学
传染病(医学专业)
社会学
作者
Annabel Seah,Liat Hui Loo,Natasha Jamali,Matthias Maiwald,Joel Aik
标识
DOI:10.1016/j.envres.2022.114453
摘要
Influenza is an important cause of paediatric illness across the globe. However, information about the relationships between air pollution, meteorological variability and paediatric influenza A and B infections in tropical settings is limited.We analysed all daily reports of influenza A and B infections in children <5 years old obtained from the largest specialist women and children's hospital in Singapore. In separate negative binomial regression models, we assessed the dependence of paediatric influenza A and B infections on air quality and meteorological variability, using multivariable fractional polynomial modelling and adjusting for time-varying confounders.Approximately 80% of 7329 laboratory-confirmed reports were caused by influenza A. We observed positive associations between sulphur dioxide (SO2) exposure and the subsequent risk of infection with both influenza types. We observed evidence of a harvesting effect of SO2 on Influenza A but not Influenza B. Ambient temperature was associated with a decline in influenza A reports (Relative Risk at lag 5 [RRlag5]: 0.949, 95% CI: 0.916-0.983). Rainfall was positively associated with a subsequent increase in influenza A reports (RRlag3: 1.044, 95% CI: 1.017-1.071). Nitrogen dioxide (NO2) concentration was positively associated with influenza B reports (RRlag5: 1.015, 95% CI: 1.005-1.025). There was a non-linear association between CO and influenza B reports. Absolute humidity increased the ensuing risk of influenza B (RRlag5: 4.799, 95% CI: 2.277-10.118). Influenza A and B infections displayed dissimilar but predictable within-year seasonal patterns.We observed different independent associations between air quality and meteorological variability with paediatric influenza A and B infections. Anticipated seasonal infection peaks and variations in air quality and meteorological parameters can inform the timing of community measures aimed at reducing influenza infection risk.
科研通智能强力驱动
Strongly Powered by AbleSci AI