Abstract
At present, with increasing awareness of the relationship between respiratory disease and air pollution, it is critical to assess the environmental risk factors for influenza. This study aimed to estimate the associations between ambient air pollution and the number of influenza-like illness (ILI) cases in Hangzhou, China, from 2015 to 2021. Weekly meteorological data, including average ambient temperature and average relative humidity, from December 29, 2014 to January 2, 2022 were collected from the Hangzhou Meteorological Service Center, and air pollutants, including nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), ground-level ozone (O(3)), particulate matter (PM) with aerodynamic diameter ≤ 2.5 μm (PM(2.5)), and PM with aerodynamic diameter ≤ 10 μm (PM(10)), were collected from National Ambient Air Quality Automatic Monitoring Stations in Hangzhou. The number of weekly ILI cases was collected from 15 influenza surveillance sentinel hospitals in Hangzhou. A generalized linear model (GLM) with quasi-Poisson regression was adopted to estimate the association between air pollution and ILI. After adjusting for the effects of average temperature, relative humidity, and seasonal and long-term trends, PM(2.5), PM(10), NO(2), and SO(2) were found to be significantly associated with the number of ILI cases, with relative risk (RR) values of 1.018 (95% CI 1.001-1.036), 1.016 (1.005-1.028), 1.063 (1.067-1.364), and 1.207 (1.067-1.364), respectively. In the two-pollutant model, putting PM(2.5), PM(10), NO(2), or SO(2) into the model separately with O(3) produced results similar to those of the single-pollutant model. PM(2.5), PM(10), and NO(2) have statistical significance in cold seasons, with the RR values of 1.020 (95% CI 1.001-1.038), 1.012 (95% CI 1.000-1.024), and 1.060 (95% CI 1.031-1.090), respectively. In summary, our study found that most air pollutants (PM(10), PM(2.5), NO(2), and SO(2)) have a significant association with the risk of ILI cases in Hangzhou. These findings can serve as a reference for the formulation of effective protective measures.