Abstract:

Objective To analyze the surveillance data of influenza-like illness（ILI） in Zigong City from 2016 to 2024，investigate the correlation between ILI cases and meteorological factors，construct an influenza prediction model，and provide a reference point for influenza prevention and control. Methods ILI data and meteorological data reported by national influenza sentinel surveillance hospitals in Zigong City from 2016 to 2024 were analyzed. Spearman rank correlation was used to assess the relationship between ILI and the influenza-like illness percentage（ILI%）. The seasonal autoregressive integrated moving average（SARIMA） model was applied to predict ILI% in Zigong City. Results From 2016 to 2024，174 189 ILI cases were reported by national influenza surveillance sentinel hospitals in Zigong City，with an ILI% of 4.72%. Among 10 920 ILI specimens collected，the positive rate was 20.12%. Dominant strains varied annually（χ²=1 737.32，P<0.05）.A positive correlation was observed between ILI and ILI%（r=0.89，P<0.05）. ILI% was positively correlated with average temperature（r=0.136，P<0.05），and negatively correlated with average air pressure（r=-0.125，P<0.05） and relative humidity（r=-0.129，P<0.05）. The SARIMA model predicted a declining influenza trend in Zigong City during the first half of 2025，aligning with historical epidemic patterns. Conclusion From 2016 to 2024，ILI surveillance in Zigong City revealed a fluctuating upward trend，and dominant strains of influenza A（H1N1），H3N2，and influenza B（Victoria lineage） alternated in prevalence. Meteorological factors are associated with influenza incidence，and the SARIMA model demonstrates robust predictive capability for ILI.

Key words: Zigong, Influenza-like illness, Pathogen, Surveillance, Meteorological factors, Predictive analysis