Influenza, an acute respiratory infectious disease caused by the influenza virus, exhibits distinct seasonal patterns in China, with peak activity occurring in winter and spring in northern regions, and in winter and summer in southern areas. The World Health Organization (WHO) emphasizes that early warning and epidemic intensity assessments are critical public health strategies for influenza prevention and control. Internet-based flu surveillance, with real-time data and low costs, effectively complements traditional methods. The Baidu Search Index, which reflects flu-related queries, strongly correlates with influenza trends, aiding in regional activity assessment and outbreak tracking.

In 2013, Vega et al. applied The Moving Epidemic Method (MEM) to establish influenza epidemic thresholds and assess epidemic intensity. The MEM relies solely on historical incidence data, demonstrating strong applicability. By updating thresholds in real time, the onset of an epidemic can be identified more accurately. The MEM has been widely and effectively used in temperate regions; however, its application in subtropical countries has rarely been reported. Hubei Province, located in Central China, has experienced a transient surge in influenza activity following the COVID-19 pandemic, necessitating the urgent development of early warning systems to monitor future influenza trends.

This study aims to apply the MEM to assess the intensity of influenza epidemics in Hubei Province during the 2023–2024 season, establish corresponding epidemic thresholds, and evaluate the performance of the MEM in this region. The findings will provide a reference for defining influenza epidemic thresholds and assessing epidemic intensity in Hubei Province, thereby offering a scientific basis for relevant health authorities to formulate effective prevention and control strategies, develop related policies, and allocate medical resources rationally.