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美国实验室确诊流感住院患者的时空聚集性。

Spatial and temporal clustering of patients hospitalized with laboratory-confirmed influenza in the United States.

机构信息

Brigham Young University, Provo, UT, USA.

New Mexico Department of Health, NM, USA.

出版信息

Epidemics. 2020 Jun;31:100387. doi: 10.1016/j.epidem.2020.100387. Epub 2020 Feb 10.

DOI:10.1016/j.epidem.2020.100387
PMID:32371346
Abstract

BACKGROUND

Timing of influenza spread across the United States is dependent on factors including local and national travel patterns and climate. Local epidemic intensity may be influenced by social, economic and demographic patterns. Data are needed to better explain how local socioeconomic factors influence both the timing and intensity of influenza seasons to result in national patterns.

METHODS

To determine the spatial and temporal impacts of socioeconomics on influenza hospitalization burden and timing, we used population-based laboratory-confirmed influenza hospitalization surveillance data from the CDC-sponsored Influenza Hospitalization Surveillance Network (FluSurv-NET) at up to 14 sites from the 2009/2010 through 2013/2014 seasons (n = 35,493 hospitalizations). We used a spatial scan statistic and spatiotemporal wavelet analysis, to compare temporal patterns of influenza spread between counties and across the country.

RESULTS

There were 56 spatial clusters identified in the unadjusted scan statistic analysis using data from the 2010/2011 through the 2013/2014 seasons, with relative risks (RRs) ranging from 0.09 to 4.20. After adjustment for socioeconomic factors, there were five clusters identified with RRs ranging from 0.21 to 1.20. In the wavelet analysis, most sites were in phase synchrony with one another for most years, except for the H1N1 pandemic year (2009-2010), wherein most sites had differential epidemic timing from the referent site in Georgia.

CONCLUSIONS

Socioeconomic factors strongly impact local influenza hospitalization burden. Influenza phase synchrony varies by year and by socioeconomics, but is less influenced by socioeconomics than is disease burden.

摘要

背景

美国流感传播的时间取决于包括当地和全国旅行模式和气候在内的因素。当地的流行强度可能受到社会、经济和人口统计模式的影响。需要数据来更好地解释当地社会经济因素如何影响流感季节的时间和强度,从而导致全国性模式。

方法

为了确定社会经济因素对流感住院负担和时间的空间和时间影响,我们使用了疾病预防控制中心赞助的流感住院监测网络(FluSurv-NET)的基于人群的实验室确诊流感住院监测数据,该网络在 2009/2010 至 2013/2014 季节期间在多达 14 个地点进行(n=35493 例住院)。我们使用空间扫描统计和时空小波分析来比较县际和全国流感传播的时间模式。

结果

在使用 2010/2011 至 2013/2014 季节的数据进行的未经调整的扫描统计分析中,共发现 56 个空间聚类,相对风险(RR)范围从 0.09 到 4.20。在调整社会经济因素后,发现有五个聚类,RR 范围从 0.21 到 1.20。在小波分析中,除了 H1N1 大流行年份(2009-2010 年)外,大多数站点在大多数年份与参考站点(佐治亚州)保持同步,在该年份中,大多数站点的流行时间与参考站点不同。

结论

社会经济因素强烈影响当地流感住院负担。流感的相位同步性因年份和社会经济因素而异,但受疾病负担的影响小于疾病负担。

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