University of Washington, Seattle, Washington, United States of America.
PLoS One. 2011 Apr 27;6(4):e18687. doi: 10.1371/journal.pone.0018687.
Google Flu Trends was developed to estimate US influenza-like illness (ILI) rates from internet searches; however ILI does not necessarily correlate with actual influenza virus infections.
Influenza activity data from 2003-04 through 2007-08 were obtained from three US surveillance systems: Google Flu Trends, CDC Outpatient ILI Surveillance Network (CDC ILI Surveillance), and US Influenza Virologic Surveillance System (CDC Virus Surveillance). Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data. An analysis was performed to investigate outlier observations and determine the extent to which they affected the correlations between surveillance data. Pearson's correlation coefficient describing Google Flu Trends and CDC Virus Surveillance over the study period was 0.72 (95% CI: 0.64, 0.79). The correlation between CDC ILI Surveillance and CDC Virus Surveillance over the same period was 0.85 (95% CI: 0.81, 0.89). Most of the outlier observations in both comparisons were from the 2003-04 influenza season. Exclusion of the outlier observations did not substantially improve the correlation between Google Flu Trends and CDC Virus Surveillance (0.82; 95% CI: 0.76, 0.87) or CDC ILI Surveillance and CDC Virus Surveillance (0.86; 95%CI: 0.82, 0.90).
This analysis demonstrates that while Google Flu Trends is highly correlated with rates of ILI, it has a lower correlation with surveillance for laboratory-confirmed influenza. Most of the outlier observations occurred during the 2003-04 influenza season that was characterized by early and intense influenza activity, which potentially altered health care seeking behavior, physician testing practices, and internet search behavior.
Google Flu Trends 旨在通过互联网搜索来估计美国的流感样疾病 (ILI) 发病率；然而，ILI 并不一定与实际的流感病毒感染相关。
从三个美国监测系统获得了 2003-04 年至 2007-08 年的流感活动数据：Google Flu Trends、疾病预防控制中心门诊 ILI 监测网络（CDC ILI 监测）和美国流感病毒监测系统（CDC 病毒监测）。计算了 Pearson 相关系数及其 95%置信区间（95%CI），以比较监测数据。进行了一项分析以调查异常观测值，并确定它们对监测数据相关性的影响程度。在研究期间，描述 Google Flu Trends 和 CDC Virus Surveillance 之间关系的 Pearson 相关系数为 0.72（95%CI：0.64，0.79）。同一时期 CDC ILI 监测和 CDC Virus Surveillance 之间的相关性为 0.85（95%CI：0.81，0.89）。这两个比较中的大多数异常观测值都来自 2003-04 年的流感季节。排除异常观测值并没有显著改善 Google Flu Trends 和 CDC Virus Surveillance（0.82；95%CI：0.76，0.87）或 CDC ILI 监测和 CDC Virus Surveillance（0.86；95%CI：0.82，0.90）之间的相关性。
这项分析表明，尽管 Google Flu Trends 与 ILI 发病率高度相关，但与实验室确诊流感的监测相关性较低。大多数异常观测值发生在 2003-04 年的流感季节，该季节的流感活动早且强烈，这可能改变了寻求医疗保健的行为、医生的检测实践和互联网搜索行为。
