monitoring influenza activity in the united states a comparison of traditional surveillance systems with google flu trends监测流感活动在美国比较传统的监测系统与谷歌流感趋势.pdfVIP

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monitoring influenza activity in the united states a comparison of traditional surveillance systems with google flu trends监测流感活动在美国比较传统的监测系统与谷歌流感趋势.pdf

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monitoring influenza activity in the united states a comparison of traditional surveillance systems with google flu trends监测流感活动在美国比较传统的监测系统与谷歌流感趋势

Monitoring Influenza Activity in the United States: A Comparison of Traditional Surveillance Systems with Google Flu Trends 1 2,3 2 4 2 Justin R. Ortiz *, Hong Zhou , David K. Shay , Kathleen M. Neuzil , Ashley L. Fowlkes , Christopher H. Goss1 1 University of Washington, Seattle, Washington, United States of America, 2 Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America, 3 Atlanta Research and Education Foundation, Atlanta, Georgia, United States of America, 4 PATH, Seattle, Washington, United States of America Abstract Background: 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. Methods and Findings: 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)