Impact of meteorological factors on influenza incidence in Wuxi from 2014 to 2019: a time series and comprehensive analysis

Background Although the association between meteorological factors and influenza was numerously documented, it has not been comprehensively studied. A recent analysis of the association between influenza and meteorological factors was conducted in Wuxi, China. Methods Meteorological data and laboratory-confirmed influenza cases from 2014 to 2019 were collected in Wuxi. The exposure-response relationship was analyzed using a generalized additive model. Then we performed subgroup analysis based on age and gender. Finally, meta-analysis was utilized to aggregate the total influence of meteorological factors on influenza. Results A total of 5,306 laboratory-confirmed influenza cases were reported. Seven influenza peaks, which appeared every winter to spring and only one summer (2015), were observed during the study period. For a unit increase in weekly average pressure, temperature, wind speed, relative humidity, precipitation, and sunshine duration, the risk of influenza increased by 7.37%, decreased by 8.39%, decreased by 33.83%, increased by 6.44% when average relative humidity was > 68.86%, increased by 19.91% when precipitation was ≤ 6.13mm, and decreased by 11.41% when average sunshine duration was ≤ 6.30h, respectively. Additionally, no significant differences were observed in the effects of the six meteorological factors between different gender groups. The impacts of average air pressure, average temperature, precipitation, and sunshine duration on children aged 3 to 14 were greater than on other age groups. Compared with the meta-analysis, a pooled effect of ambient temperature was consistent. In the subgroup and meta-regression analysis, a significant difference was found in the children group. Conclusions The present study provides further insight into the effects of meteorological factors on influenza incidence, including age-specific impacts. Understanding these factors will be beneficial and crucial for the advancement of influenza monitoring and early warning systems.