Detecting influenza epidemics using search engine query data
Detecting influenza epidemics using search engine query data
复制标题
DOI：
10.1038/nature07634
复制
发表时间：
2009-02-19
期刊：
影响因子：
64.8
通讯作者：
Brilliant, Larry
中科院分区：
文献类型：
--
作者：
Ginsberg, Jeremy;Mohebbi, Matthew H.;Brilliant, Larry
季节性流感流行是一个主要的公共卫生问题，每年在全球造成数千万例呼吸道疾病和 250,000 至 500,000 人死亡(1)。除了季节性流感之外，一种新的流感病毒株以前不存在免疫力，并且证明可以在人与人之间传播，可能会导致导致数百万人死亡的大流行(2)。及早发现疾病活动并随后做出快速反应，可以减少季节性流感和大流行性流感的影响(3,4)。改善早期检测的一种方法是以在线搜索引擎查询的形式监控寻求健康的行为，这些查询每天由世界各地数百万用户提交。在这里，我们提出了一种分析大量谷歌搜索查询的方法，以跟踪人群中的流感样疾病。由于某些查询的相对频率与患者出现流感样症状的就诊百分比高度相关，因此我们可以准确估计美国每个地区当前每周流感活动的水平，报告滞后约一天。这种方法可能使使用搜索查询来检测拥有大量网络搜索用户的地区的流感流行成为可能。
Seasonal influenza epidemics are a major public health concern, causing tens of millions of respiratory illnesses and 250,000 to 500,000 deaths worldwide each year(1). In addition to seasonal influenza, a new strain of influenza virus against which no previous immunity exists and that demonstrates human- to- human transmission could result in a pandemic with millions of fatalities(2). Early detection of disease activity, when followed by a rapid response, can reduce the impact of both seasonal and pandemic influenza(3,4). One way to improve early detection is to monitor health- seeking behaviour in the form of queries to online search engines, which are submitted by millions of users around the world each day. Here we present a method of analysing large numbers of Google search queries to track influenza- like illness in a population. Because the relative frequency of certain queries is highly correlated with the percentage of physician visits in which a patient presents with influenza- like symptoms, we can accurately estimate the current level of weekly influenza activity in each region of the United States, with a reporting lag of about one day. This approach may make it possible to use search queries to detect influenza epidemics in areas with a large population of web search users.