Using Internet Searches for Influenza Surveillance
Using Internet Searches for Influenza Surveillance
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DOI：
10.1086/593098
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发表时间：
2008-12-01
影响因子：
11.8
通讯作者：
Nelson, Forrest D.
中科院分区：
文献类型：
--
作者：
Polgreen, Philip M.;Chen, Yiling;Nelson, Forrest D.
互联网是健康信息的重要来源。因此，互联网搜索的频率可以提供有关传染病活动的信息。作为一个例子，我们检查了流感搜索和实际流感发生之间的关系。使用来自雅虎的搜索查询搜索引擎(http://search.yahoo.com))从2004年3月到2008年5月，我们统计了来自美国的每日唯一查询，其中包含与流感相关的搜索词。计数除以总搜索量，得出一周内每日搜索量的平均值。我们估计了线性模型，使用以1-10周提前期为解释变量的搜索来预测美国流感培养阳性以及肺炎和流感死亡的百分比。随着搜索频率的使用，我们的模型预测流感培养阳性的人数比发生时提前1-3周(P<；.001)，类似的模型预测肺炎和流感的死亡率最多提前5 P<；.001周(P<；.001)。搜索词监测可能为疾病监测提供另一种工具。
The Internet is an important source of health information. Thus, the frequency of Internet searches may provide information regarding infectious disease activity. As an example, we examined the relationship between searches for influenza and actual influenza occurrence. Using search queries from the Yahoo! search engine (http://search.yahoo.com) from March 2004 through May 2008, we counted daily unique queries originating in the United States that contained influenza-related search terms. Counts were divided by the total number of searches, and the resulting daily fraction of searches was averaged over the week. We estimated linear models, using searches with 1-10-week lead times as explanatory variables to predict the percentage of cultures positive for influenza and deaths attributable to pneumonia and influenza in the United States. With use of the frequency of searches, our models predicted an increase in cultures positive for influenza 1-3 weeks in advance of when they occurred (P < .001), and similar models predicted an increase in mortality attributable to pneumonia and influenza up to 5 P < .001 weeks in advance (P < .001). Search-term surveillance may provide an additional tool for disease surveillance.