tetano
Editor, Senior Moderator
BMC Infect Dis
. 2026 Jul 13.
doi: 10.1186/s12879-026-13938-8. Online ahead of print.
Spatiotemporal epidemiology of influenza in Fujian Province: an 18-year observational study
Minhua Li[SUP] #[/SUP][SUP] 1 [/SUP], Shaojian Cai[SUP] #[/SUP][SUP] 2 [/SUP], Jiake Chen[SUP] #[/SUP][SUP] 3 [/SUP], Lu Qin[SUP] 1 [/SUP], Meirong Zhan[SUP] 2 [/SUP], Jinzhang Wang[SUP] 2 [/SUP], Yu Jiang[SUP] 1 [/SUP], Chuancheng Wu[SUP] 4 [/SUP], Jianjun Xiang[SUP] 5 [/SUP]
Affiliations
Objective: To investigate the spatiotemporal epidemiological characteristics and temporal trends of influenza in Fujian Province, China, from 2005 to 2022.
Methods: Descriptive epidemiological methods were used to analyze the temporal, demographic, occupational, and regional distribution of influenza cases. Spatial autocorrelation analysis, trend surface analysis, and spatiotemporal scan statistics were applied to explore the spatial distribution and clustering characteristics of influenza.
Results: A total of 215,338 influenza cases were reported in Fujian Province during 2005-2022, with the incidence rate showing an overall fluctuating upward trend over time (Z = 4.394, P < 0.001). Children aged 0-5 years and students accounted for the largest proportions of reported cases. Influenza activity demonstrated marked temporal and seasonal variation, with relatively higher activity observed in summer and winter. Trend surface analysis indicated higher case concentrations in eastern and central regions of Fujian Province. Significant positive spatial autocorrelation was identified in multiple years, and six significant spatiotemporal clusters were detected, mainly distributed in southeastern Fujian.
Conclusion: Influenza in Fujian Province showed an increasing annual incidence trend, marked temporal fluctuation, and dynamic spatial clustering during 2005-2022. These findings may support more targeted influenza surveillance, prevention, and resource allocation in high-risk populations and areas.
Keywords: Influenza; Spatial autocorrelation; Spatiotemporal clustering; Trend analysis.
. 2026 Jul 13.
doi: 10.1186/s12879-026-13938-8. Online ahead of print.
Spatiotemporal epidemiology of influenza in Fujian Province: an 18-year observational study
Minhua Li[SUP] #[/SUP][SUP] 1 [/SUP], Shaojian Cai[SUP] #[/SUP][SUP] 2 [/SUP], Jiake Chen[SUP] #[/SUP][SUP] 3 [/SUP], Lu Qin[SUP] 1 [/SUP], Meirong Zhan[SUP] 2 [/SUP], Jinzhang Wang[SUP] 2 [/SUP], Yu Jiang[SUP] 1 [/SUP], Chuancheng Wu[SUP] 4 [/SUP], Jianjun Xiang[SUP] 5 [/SUP]
Affiliations
- PMID: 42443781
- DOI: 10.1186/s12879-026-13938-8
Objective: To investigate the spatiotemporal epidemiological characteristics and temporal trends of influenza in Fujian Province, China, from 2005 to 2022.
Methods: Descriptive epidemiological methods were used to analyze the temporal, demographic, occupational, and regional distribution of influenza cases. Spatial autocorrelation analysis, trend surface analysis, and spatiotemporal scan statistics were applied to explore the spatial distribution and clustering characteristics of influenza.
Results: A total of 215,338 influenza cases were reported in Fujian Province during 2005-2022, with the incidence rate showing an overall fluctuating upward trend over time (Z = 4.394, P < 0.001). Children aged 0-5 years and students accounted for the largest proportions of reported cases. Influenza activity demonstrated marked temporal and seasonal variation, with relatively higher activity observed in summer and winter. Trend surface analysis indicated higher case concentrations in eastern and central regions of Fujian Province. Significant positive spatial autocorrelation was identified in multiple years, and six significant spatiotemporal clusters were detected, mainly distributed in southeastern Fujian.
Conclusion: Influenza in Fujian Province showed an increasing annual incidence trend, marked temporal fluctuation, and dynamic spatial clustering during 2005-2022. These findings may support more targeted influenza surveillance, prevention, and resource allocation in high-risk populations and areas.
Keywords: Influenza; Spatial autocorrelation; Spatiotemporal clustering; Trend analysis.