Comparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaks
Abstract The aim of this study was to gain insights into the epidemiology, spatial trends, spatial structure evolution, and spatiotemporal aggregation characteristics of influenza epidemics during seasonal influenza and COVID-19 pandemic in Fuzhou from 2013 to 2022. Utilizing influenza case report d...
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Nature Portfolio
2025-03-01
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| Online Access: | https://doi.org/10.1038/s41598-025-93372-z |
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| author | Jingjing Yang Qingquan Chen Xiaoyan Zheng Ao Sun Mengcai Sun Quan Zhou Youqiong Xu Xiaoyang Zhang |
| author_facet | Jingjing Yang Qingquan Chen Xiaoyan Zheng Ao Sun Mengcai Sun Quan Zhou Youqiong Xu Xiaoyang Zhang |
| author_sort | Jingjing Yang |
| collection | DOAJ |
| description | Abstract The aim of this study was to gain insights into the epidemiology, spatial trends, spatial structure evolution, and spatiotemporal aggregation characteristics of influenza epidemics during seasonal influenza and COVID-19 pandemic in Fuzhou from 2013 to 2022. Utilizing influenza case report data from Fuzhou spanning 2013 to 2022, we applied descriptive epidemiological methods to analyze the epidemiological characteristics and distribution patterns of reported influenza cases across various time periods, populations, and regions. Furthermore, we employed trend-surface analysis, kernel density estimation, and space-time scanning statistics to investigate the evolution of spatial trends, changes in spatial structure, and the spatiotemporal aggregation characteristics of the reported influenza incidence rate at the county level. A total of 19,135 influenza cases were reported in Fuzhou during the period of 2013–2022. The male-to-female ratio of cases was 1.31:1. The age group most affected by influenza was 0–19 years, accounting for 13,600 cases (71.07%), and the occupations mostly affected were children in the diaspora (6,570 cases, 34.33%), students (4,402 cases, 23.00%), and preschool children (2,595 cases, 13.56%). Areas with a high number of reported influenza cases were mainly located in the central part of Fuzhou City. On the overall trend of Fuzhou, the reported incidence rate of influenza exhibits a spatial trend characterized by a “high in the middle” pattern. Its spatial structure has evolved from a “triple nucleus - double nucleus” configuration and demonstrates the contraction trend of “clustering in the central urban area”. Simultaneously, the spatial structure has transitioned from a “triple nucleus” to a “double nucleus” pattern, reflecting a trend of contraction towards “central city clustering.” The results of space-time scanning identified Class I clusters of influenza cases in the Gulou and Jinan districts (RR = 47.99, LLR = 6917.94, P < 0.01), predominantly occurring during June and July 2022. The average annual reported incidence of influenza in Fuzhou was notably higher during the COVID-19 pandemic than the levels recorded during seasonal influenza outbreaks. Additionally, the concentration of influenza cases in central Fuzhou reflects a significant degree of spatiotemporal clustering of the epidemic. |
| format | Article |
| id | doaj-art-d3cb0dfbf09a40d39d6dc1fa3ff0f7c8 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
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| spelling | doaj-art-d3cb0dfbf09a40d39d6dc1fa3ff0f7c82025-08-20T03:01:37ZengNature PortfolioScientific Reports2045-23222025-03-0115111410.1038/s41598-025-93372-zComparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaksJingjing Yang0Qingquan Chen1Xiaoyan Zheng2Ao Sun3Mengcai Sun4Quan Zhou5Youqiong Xu6Xiaoyang Zhang7The Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityThe Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityThe Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityThe Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityThe Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityThe Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityThe Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityThe Affiliated Fuzhou Center for Disease Control and Prevention of Fujian Medical UniversityAbstract The aim of this study was to gain insights into the epidemiology, spatial trends, spatial structure evolution, and spatiotemporal aggregation characteristics of influenza epidemics during seasonal influenza and COVID-19 pandemic in Fuzhou from 2013 to 2022. Utilizing influenza case report data from Fuzhou spanning 2013 to 2022, we applied descriptive epidemiological methods to analyze the epidemiological characteristics and distribution patterns of reported influenza cases across various time periods, populations, and regions. Furthermore, we employed trend-surface analysis, kernel density estimation, and space-time scanning statistics to investigate the evolution of spatial trends, changes in spatial structure, and the spatiotemporal aggregation characteristics of the reported influenza incidence rate at the county level. A total of 19,135 influenza cases were reported in Fuzhou during the period of 2013–2022. The male-to-female ratio of cases was 1.31:1. The age group most affected by influenza was 0–19 years, accounting for 13,600 cases (71.07%), and the occupations mostly affected were children in the diaspora (6,570 cases, 34.33%), students (4,402 cases, 23.00%), and preschool children (2,595 cases, 13.56%). Areas with a high number of reported influenza cases were mainly located in the central part of Fuzhou City. On the overall trend of Fuzhou, the reported incidence rate of influenza exhibits a spatial trend characterized by a “high in the middle” pattern. Its spatial structure has evolved from a “triple nucleus - double nucleus” configuration and demonstrates the contraction trend of “clustering in the central urban area”. Simultaneously, the spatial structure has transitioned from a “triple nucleus” to a “double nucleus” pattern, reflecting a trend of contraction towards “central city clustering.” The results of space-time scanning identified Class I clusters of influenza cases in the Gulou and Jinan districts (RR = 47.99, LLR = 6917.94, P < 0.01), predominantly occurring during June and July 2022. The average annual reported incidence of influenza in Fuzhou was notably higher during the COVID-19 pandemic than the levels recorded during seasonal influenza outbreaks. Additionally, the concentration of influenza cases in central Fuzhou reflects a significant degree of spatiotemporal clustering of the epidemic.https://doi.org/10.1038/s41598-025-93372-zInfluenzaEpidemiological characterizationTrend-surface analysisKernel density EstimationSpace-time scanningSeasonal influenza |
| spellingShingle | Jingjing Yang Qingquan Chen Xiaoyan Zheng Ao Sun Mengcai Sun Quan Zhou Youqiong Xu Xiaoyang Zhang Comparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaks Scientific Reports Influenza Epidemiological characterization Trend-surface analysis Kernel density Estimation Space-time scanning Seasonal influenza |
| title | Comparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaks |
| title_full | Comparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaks |
| title_fullStr | Comparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaks |
| title_full_unstemmed | Comparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaks |
| title_short | Comparative analysis of epidemiological and Spatiotemporal patterns in seasonal influenza and COVID-19 outbreaks |
| title_sort | comparative analysis of epidemiological and spatiotemporal patterns in seasonal influenza and covid 19 outbreaks |
| topic | Influenza Epidemiological characterization Trend-surface analysis Kernel density Estimation Space-time scanning Seasonal influenza |
| url | https://doi.org/10.1038/s41598-025-93372-z |
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