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基于 GIS 的 2014 至 2023 年新疆地区流感发病率时空演变特征。

Spatial-temporal evolution patterns of influenza incidence in Xinjiang Prefecture from 2014 to 2023 based on GIS.

机构信息

Xinjiang Uygur Autonomous Region Center for Disease Control and Prevention, No. 380, Jianquan First Street, Tianshan District, Ürümqi, 830002, Xinjiang Uygur Autonomous Region, China.

出版信息

Sci Rep. 2024 Sep 14;14(1):21496. doi: 10.1038/s41598-024-72618-2.

Abstract

Using GIS technology, this study investigated the spatiotemporal distribution pattern of influenza incidence in Xinjiang from 2014 to 2023 based on influenza surveillance data. The study revealed a noticeable fluctuation trend in influenza incidence rates in Xinjiang, particularly notable spikes observed in 2019 and 2023. The results of the 3-year moving average showed a significant long-term upward trend in influenza incidence rates, confirmed by Theil-Sen method (MAD = 2.202, p < 0.01). Global spatial autocorrelation analysis indicated significant positive spatial autocorrelation in influenza incidence rates from 2016 and from 2018 to 2023 (Moran's I > 0, P < 0.05). Local spatial autocorrelation analysis further revealed clustering patterns in different regions, with high-high clustering and low-high clustering predominating in northern Xinjiang, and low-low clustering predominating in southern Xinjiang. Hotspot analysis indicated a progressive rise in the number of influenza incidence hotspots, primarily concentrated in northern Xinjiang, particularly in Urumqi, Ili Kazakh Autonomous Prefecture, and Hotan Prefecture. Standard deviation ellipse analysis and the trajectory of influenza incidence gravity center migration showed that the transmission range of influenza in Xinjiang has been expanding, with the epidemic center gradually moving northward. The spatiotemporal heterogeneity of influenza incidence in Xinjiang highlights the need for differentiated and precise influenza prevention and control strategies in different regions to address the changing trends in influenza prevalence.

摘要

利用 GIS 技术,本研究基于流感监测数据,调查了 2014 年至 2023 年新疆流感发病率的时空分布模式。研究揭示了新疆流感发病率的明显波动趋势,特别是在 2019 年和 2023 年观察到明显的高峰。3 年滑动平均结果表明流感发病率呈显著的长期上升趋势,Theil-Sen 方法证实了这一点(MAD=2.202,p<0.01)。全局空间自相关分析表明,2016 年和 2018 年至 2023 年的流感发病率存在显著的正空间自相关(Moran's I>0,P<0.05)。局部空间自相关分析进一步揭示了不同地区的聚类模式,高-高聚类和低-高聚类在新疆北部占主导地位,而低-低聚类在新疆南部占主导地位。热点分析表明,流感发病率热点的数量呈逐渐增加的趋势,主要集中在新疆北部,特别是乌鲁木齐、伊犁哈萨克自治州和和田地区。标准差椭圆分析和流感发病率重心迁移轨迹表明,新疆流感的传播范围不断扩大,疫情中心逐渐向北移动。新疆流感发病率的时空异质性突出表明,需要在不同地区采取差异化和精确的流感防控策略,以应对流感流行趋势的变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b209/11401927/f3c6d8cac48c/41598_2024_72618_Fig1_HTML.jpg

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