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2010-2015 年中国亚热带城市流感活动的季节性模式。

Seasonal pattern of influenza activity in a subtropical city, China, 2010-2015.

机构信息

Hefei Center for Disease Control and Prevention, Anhui, China.

Department of Biostatistics, School of Public Health and Key Laboratory of Public Health Safety, Fudan University, 200231 Xuhui District, Shanghai, China.

出版信息

Sci Rep. 2017 Dec 13;7(1):17534. doi: 10.1038/s41598-017-17806-z.

DOI:10.1038/s41598-017-17806-z
PMID:29235535
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5727502/
Abstract

Influenza seasonality study is critical for policy-makers to choose an optimal time for influenza vaccination campaign, especially for subtropical regions where influenza seasonality and periodicity are unclear. In this study, we explored the seasonality and periodicity of influenza in Hefei, China during 2010 to 2015 using five proxies originated from three data sources of clinical surveillance of influenza-like illness (ILI), laboratory surveillance of influenza and death registration of pneumonia and influenza. We combined both wavelets analysis and de-linear-trend regression with Fourier harmonic terms to estimate seasonal characteristics of epidemic phase, peak time, amplitude, ratio of dominant seasonality. We found both annual cycle of influenza epidemics peaking in December-February and semi-annual cycle peaking in December-February and June-July in subtropical city Hefei, China. Compared to proxies developed by ILI and death registration data separately, influenza proxies incorporated laboratory surveillance data performed better seasonality and periodicity, especially in semi-annual periodicity in Hefei. Proxy of ILI consultation rate showed more timeliness peak than other proxies, and could be useful in developing the early warning model for influenza epidemics. Our study suggests to integrate clinical and laboratory surveillance of influenza for future influenza seasonality studies in subtropical regions.

摘要

流感季节性研究对于决策者选择流感疫苗接种运动的最佳时间至关重要,特别是对于流感季节性和周期性不明确的亚热带地区。在这项研究中,我们使用来自流感样疾病(ILI)临床监测、流感实验室监测和肺炎和流感死亡登记的三个数据源的五个指标,探索了 2010 年至 2015 年期间中国合肥的流感季节性和周期性。我们结合了小波分析和去线性趋势回归与傅立叶谐波项来估计流行阶段的季节性特征、峰值时间、振幅、主导季节性的比率。我们发现,在中国亚热带城市合肥,流感流行的年度周期在 12 月至 2 月达到峰值,半年周期在 12 月至 2 月和 6 月至 7 月达到峰值。与分别由 ILI 和死亡登记数据开发的指标相比,包含实验室监测数据的流感指标在季节性和周期性方面表现更好,特别是在合肥的半年周期性方面。ILI 咨询率指标的峰值比其他指标更及时,可用于开发流感流行的预警模型。我们的研究表明,未来在亚热带地区进行流感季节性研究时,应整合临床和实验室监测的流感数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/ed7c25917716/41598_2017_17806_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/c1b6e245fc45/41598_2017_17806_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/353a257e1fab/41598_2017_17806_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/74272c0df4d5/41598_2017_17806_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/ed7c25917716/41598_2017_17806_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/c1b6e245fc45/41598_2017_17806_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/353a257e1fab/41598_2017_17806_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/74272c0df4d5/41598_2017_17806_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd31/5727502/ed7c25917716/41598_2017_17806_Fig4_HTML.jpg

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