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预防医学  2023, Vol. 35 Issue (9): 741-745    DOI: 10.19485/j.cnki.issn2096-5087.2023.09.002
  论著 本期目录 | 过刊浏览 | 高级检索 |
2017—2021年鄞州区流行性感冒时空聚集性分析
奕天飞, 沈鹏, 平建明, 张俊锋, 孙烨祥
宁波市鄞州区疾病预防控制中心数据中心,浙江 宁波 315100
Spatial-temporal clustering analysis of influenza incidence in Yinzhou District from 2017 to 2021
YI Tianfei, SHEN Peng, PING Jianming, ZHANG Junfeng, SUN Yexiang
Data Center, Yinzhou District Centre for Disease Control and Prevention, Ningbo, Zhejiang 315100, China
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摘要 目的 了解2017—2021年浙江省宁波市鄞州区流行性感冒(流感)的时空聚集特征,为流感防控提供参考。方法 通过中国疾病预防控制信息系统收集2017—2021年鄞州区流感监测资料,采用ArcGIS 10.8软件进行空间自相关分析,采用SaTScan 10.1软件进行时空扫描,分析鄞州区流感发病的时空聚集特征。结果 2017—2021年鄞州区共报告流感60 543例,年均发病率为0.76%。2019年12月和2020年1月为发病高峰时段,发病率分别为9.35%和9.28%。空间自相关分析显示,2018—2021年鄞州区流感发病存在空间正相关(均P<0.05),2019年和2021年呈高发聚集性;其中,中河街道在2017—2020年呈低-高聚集;姜山镇在2017年和2020年呈低-高聚集,2019年和2021年呈高-高聚集;首南街道在2018—2020年呈高-高聚集;云龙镇在2021年呈高-高聚集。时空扫描结果显示,2017年8月一级聚集区位于以东钱湖镇为中心的中部地区;2018—2020年12月和1月一级聚集区位于西北部地区;2021年8月一级聚集区位于西部地区。结论 2017—2021年鄞州区流感发病存在时空聚集性,冬季和夏季为发病高峰,主要聚集于西北部地区。
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奕天飞
沈鹏
平建明
张俊锋
孙烨祥
关键词 流行性感冒时空聚集性空间自相关时空扫描    
AbstractObjective To investigate the spatio-temporal clustering characteristics of influenza in Yinzhou District, Ningbo City, Zhejiang Province from 2017 to 2021, so as to provide insights into prevention and control of influenza. Methods Data of influenza in Yinzhou District from 2017 to 2021 were collected from the Chinese Disease Prevention and Control Information System. The software ArcGIS 10.8 was employed for spatial autocorrelation analysis, and SaTScan 10.1 was employed for spatio-temporal scanning to analyze the temporal and spatial clustering characteristics of influenza incidence in Yinzhou District. Results Totally 60 543 influenza cases were reported in Yinzhou District from 2017 to 2021, with an incidence of 0.76%. The incidence of influenza peaked in December 2019 (9.35%) and January 2020 (9.28%) during the period between 2017 and 2021. Spatial autocorrelation analysis showed that there was a positive spatial correlation of influenza incidence in Yinzhou District from 2018 to 2021 (all P<0.05), and a high clustering in 2019 and 2021. Zhonghe Street showed a low-high clustering from 2017 to 2020; Jiangshan Town showed a low-high clustering in 2017 and 2020, and a high-high clustering in 2019 and 2021; Shounan Street showed a high-high clustering from 2018 to 2020; Yunlong Street showed a high-high clustering in 2021. Spatio-temporal scanning analysis showed that the class Ⅰ clusters were located in the central region which centered in Dongqianhu Town, with aggregation time in August 2017, in the northwest region with aggregation time in December and January from 2018 to 2020, and in the west region with aggregation time in August 2021. Conclusion The incidence of influenza in Yinzhou District from 2017 to 2021 showed a spatio-temporal clustering in the northwestern region in winter and summer.
Key wordsinfluenza    spatio-temporal aggregation    spatial autocorrelation    spatial-tempora scanning
收稿日期: 2023-05-25      修回日期: 2023-08-21      出版日期: 2023-09-10
中图分类号:  R511.7  
基金资助:宁波市鄞州区科技项目(2023AS031)
通信作者: 孙烨祥,E-mail:19464337@qq.com   
作者简介: 奕天飞,硕士,医师,主要从事流行病学数据研究工作
引用本文:   
奕天飞, 沈鹏, 平建明, 张俊锋, 孙烨祥. 2017—2021年鄞州区流行性感冒时空聚集性分析[J]. 预防医学, 2023, 35(9): 741-745.
YI Tianfei, SHEN Peng, PING Jianming, ZHANG Junfeng, SUN Yexiang. Spatial-temporal clustering analysis of influenza incidence in Yinzhou District from 2017 to 2021. Preventive Medicine, 2023, 35(9): 741-745.
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