Tags

Type your tag names separated by a space and hit enter

Monitoring influenza activity in the United States: a comparison of traditional surveillance systems with Google Flu Trends.
PLoS One. 2011 Apr 27; 6(4):e18687.Plos

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). 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).

CONCLUSIONS

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.

Authors+Show Affiliations

University of Washington, Seattle, Washington, United States of America. jrortiz@u.washington.eduNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

21556151

Citation

Ortiz, Justin R., et al. "Monitoring Influenza Activity in the United States: a Comparison of Traditional Surveillance Systems With Google Flu Trends." PloS One, vol. 6, no. 4, 2011, pp. e18687.
Ortiz JR, Zhou H, Shay DK, et al. Monitoring influenza activity in the United States: a comparison of traditional surveillance systems with Google Flu Trends. PLoS ONE. 2011;6(4):e18687.
Ortiz, J. R., Zhou, H., Shay, D. K., Neuzil, K. M., Fowlkes, A. L., & Goss, C. H. (2011). Monitoring influenza activity in the United States: a comparison of traditional surveillance systems with Google Flu Trends. PloS One, 6(4), e18687. https://doi.org/10.1371/journal.pone.0018687
Ortiz JR, et al. Monitoring Influenza Activity in the United States: a Comparison of Traditional Surveillance Systems With Google Flu Trends. PLoS ONE. 2011 Apr 27;6(4):e18687. PubMed PMID: 21556151.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Monitoring influenza activity in the United States: a comparison of traditional surveillance systems with Google Flu Trends. AU - Ortiz,Justin R, AU - Zhou,Hong, AU - Shay,David K, AU - Neuzil,Kathleen M, AU - Fowlkes,Ashley L, AU - Goss,Christopher H, Y1 - 2011/04/27/ PY - 2010/11/30/received PY - 2011/03/12/accepted PY - 2011/5/11/entrez PY - 2011/5/11/pubmed PY - 2011/9/29/medline SP - e18687 EP - e18687 JF - PloS one JO - PLoS ONE VL - 6 IS - 4 N2 - 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). 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). CONCLUSIONS: 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. SN - 1932-6203 UR - https://www.unboundmedicine.com/medline/citation/21556151/Monitoring_influenza_activity_in_the_United_States:_a_comparison_of_traditional_surveillance_systems_with_Google_Flu_Trends_ L2 - http://dx.plos.org/10.1371/journal.pone.0018687 DB - PRIME DP - Unbound Medicine ER -