Zhonghua Liu Xing Bing Xue Za Zhi. 2026 Aug 10;47(8):1464-1470. doi: 10.3760/cma.j.cn112338-20260415-00256.
ABSTRACT
Objective: To analyze the epidemic trends and spatiotemporal clustering characteristics of influenza in Shijiazhuang during the 2023-2026 surveillance years, and to provide evidence-based support for the precision prevention and control of influenza. Methods: Data on influenza cases from March 1, 2023 to March 31, 2026 were obtained from the Infectious Disease Reporting Information Management System of Chinese Information System for Disease Control and Prevention. Descriptive epidemiological methods were used to analyze the epidemic characteristics of influenza. Local indicators of spatial association and the SaTScan Poisson-based spatial scan statistic were used for spatial autocorrelation analysis. Results: During the 2023-2026 surveillance years, the annualized incidence rate of influenza in Shijiazhuang was 644.7 per 100 000 person- years, with rates of 370.0 per 100 000 person-years, 616.1 per 100 000 person-years, and 971.9 per 100 000 person-years in 2023, 2024, and 2025 surveillance years, respectively. Students accounted for the largest proportion of cases (30.9%). Three epidemic peaks were identified, occurring in the winters of 2023, 2024, and 2025, and the number of reported cases across these three winter peaks increased year by year. The 2025 influenza season began approximately 2-3 weeks earlier than in the previous two years. Spatial autocorrelation analysis showed a global Moran’s I of 0.375 for the surveillance period, with clusters concentrated in the five main urban districts. The global Moran’s I values of the second and third epidemic peaks were similar (0.360 and 0.359). Clustering began to stabilize from the second epidemic peak, showing a transmission trend of outward diffusion from the five main urban districts. Conclusions: After the gradual withdrawal of non-pharmaceutical interventions during the 2023-2026 surveillance years, influenza in Shijiazhuang showed a continuously expanding epidemic scale, with the three epidemic peaks increasing in size year by year; students were the most affected population. Spatially, influenza transmission showed a pattern of spreading from the five main urban districts to the near suburbs and spilling over to the outer suburbs, for which the transportation hub effect and regular cross-regional commuting may be the main driving factors. It is recommended to strengthen the promotion of influenza vaccination among school-age children before the start of the autumn semester and to enhance school-based influenza surveillance, and to strengthen influenza surveillance in key venues such as high-speed rail stations and airports and among key populations such as regular commuters.
PMID:42618482 | DOI:10.3760/cma.j.cn112338-20260415-00256
