Modeling the effects of meteorological factors and media-driven public awareness on seasonal influenza outbreaks.

Seasonal influenza remains a significant public health challenge in China, with its transmission dynamics influenced by both environmental conditions and media-driven public awareness. In this study, we developed a compartmental model that incorporates media-induced public awareness and meteorological factors to investigate the complex transmission mechanisms of influenza across different provinces in China. We conducted theoretical analyses to characterize the model's dynamical behavior, including conditions for disease eradication and persistence. Model parameters were estimated based on provincial data on influenza cases, Baidu search indices, and ERA5 reanalysis meteorological data through MCMC methods, providing province-specific parameters and corresponding time-varying effective reproduction numbers. Our results indicate that both low temperatures and reduced precipitation significantly facilitate influenza transmission, while media-driven public awareness plays a critical role in reducing transmission risk. A decline in media influence tends to increase the epidemic peak intensity. We observed considerable regional heterogeneity in the responses to media influence and climate variables: provinces like Zhejiang, Sichuan, Henan and Anhui are more sensitive to media influence, whereas regions like Xinjiang, Gansu, and Chongqing show limited responses. Overall, temperature was found to exert a stronger regulatory effect on influenza transmission than total precipitation. However, in northwestern provinces such as Gansu and Xinjiang, the influence of temperature on influenza transmission is relatively weaker during the winter season, while the effect of precipitation becomes more pronounced. Finally, we projected influenza trends for the first half of 2025. Forecasts show an increasing trend in influenza activity in most provinces, with model predictions closely matching observed data.