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The epidemiological characteristics and spatiotemporal clustering of influenza in Fuyang District of Hangzhou from 2020 to 2024
XIA Zhengmei, JIN Xinwen, CHEN Ren, MAO Shenghua
Anhui Journal of Preventive Medicine ›› 2026, Vol. 32 ›› Issue (2) : 159-164.
PDF(5688 KB)
PDF(5688 KB)
The epidemiological characteristics and spatiotemporal clustering of influenza in Fuyang District of Hangzhou from 2020 to 2024
Objective To analyze the epidemiological characteristics and spatiotemporal clustering of influenza in Fuyang District of Hangzhou from 2020 to 2024, and to provide a basis for risk assessment, early warning and targeted prevention and control of influenza outbreaks. Methods Influenza case data in Fuyang District of Hangzhou from 2020 to 2024 were obtained from the Chinese Disease Prevention and Control Information System. The descriptive epidemiological methods were used to analyze the distribution characteristics in terms of person, place, and time. Spatial autocorrelation analysis was performed with ArcGIS 10.8, and spatiotemporal scan statistical analysis was conducted using SaTScan 10.2. Results From 2020 to 2024, a total of 59 222 influenza cases were reported in Fuyang District of Hangzhou, with no severe or fatal cases. The average annual incidence rate was 142.36/10 000. Students and kindergarten children accounted for 58.18% of cases. The epidemic peak mainly occurred from November to March of the following year, with an additional peak in the summer of 2022. The incidence rates of influenza in Fuyang District in 2020, 2022 and 2023 were spatially positively correlated (all Moran’s I>0, all P<0.05), and the high-high aggregation areas were mainly located in the central and western regions. Spatiotemporal scan analysis identified significant spatiotemporal clusters each year, with the primary clusters predominantly distributed in the northern and southwestern areas. Conclusion Influenza incidence in Fuyang District of Hangzhou from 2020 to 2024 showed significant spatiotemporal clustering. It is recommended to implement precise prevention and control strategies in high-incidence towns (streets) before the influenza epidemic season to improve the effectiveness of epidemic control.
Influenza / Epidemiological characteristics / Spatial autocorrelation / Spatiotemporal scan
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