Short-term effects of ambient air pollution on influenza incidence in Chongqing, China: a time-series analysis.

Abstract

This study investigated the relationship between air pollution and influenza incidence in Chongqing from 2013 to 2022 using a generalized additive model (GAM), analyzing 199,712 cases. Subgroup analyses were conducted to investigate the impact of age, gender, season, and the COVID-19. Influenza incidence was positively associated with PM_2.5, PM₁₀, SO₂, NO₂ and CO, but negatively with O₃. SO₂ had the most effect. In single-day lag models, the largest percentage changes in influenza incidence at lag0 for each pollutant were: 2.930% for SO₂, 1.552% for CO, -0.637% for O₃, 0.516% for PM_2.5, and 0.405% for PM₁₀. NO₂ showed the largest change at lag11 (1.376%). In multi-day lag models, changes peaked at lag011-014. Stratified analyses revealed children aged 0-14 years as particularly vulnerable during the cold season and COVID-19 period. The study demonstrates that short-term lags and cumulative effects of air pollution exposure increase influenza incidence, significant for establishing influenza response strategies.