title: Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits.
abstract: Influenza is a deadly and costly public health problem. Variations in its seasonal patterns cause dangerous surges in emergency department (ED) patient volume. Google Flu Trends (GFT) can provide faster influenza surveillance information than traditional CDC methods, potentially leading to improved public health preparedness. GFT has been found to correlate well with reported influenza and to improve influenza prediction models. However, previous validation studies have focused on isolated clinical locations.
  
  
  
  The purpose of the study was to measure GFT surveillance effectiveness by correlating GFT with influenza-related ED visits in 19 US cities across seven influenza seasons, and to explore which city characteristics lead to better or worse GFT effectiveness.
  
  
  
  Using Healthcare Cost and Utilization Project data, we collected weekly counts of ED visits for all patients with diagnosis (International Statistical Classification of Diseases 9) codes for influenza-related visits from 2005-2011 in 19 different US cities. We measured the correlation between weekly volume of GFT searches and influenza-related ED visits (ie, GFT ED surveillance effectiveness) per city. We evaluated the relationship between 15 publically available city indicators (11 sociodemographic, two health care utilization, and two climate) and GFT surveillance effectiveness using univariate linear regression.
  
  
  
  Correlation between city-level GFT and influenza-related ED visits had a median of .84, ranging from .67 to .93 across 19 cities. Temporal variability was observed, with median correlation ranging from .78 in 2009 to .94 in 2005. City indicators significantly associated (P<.10) with improved GFT surveillance include higher proportion of female population, higher proportion with Medicare coverage, higher ED visits per capita, and lower socioeconomic status.
  
  
  
  GFT is strongly correlated with ED influenza-related visits at the city level, but unexplained variation over geographic location and time limits its utility as standalone surveillance. GFT is likely most useful as an early signal used in conjunction with other more comprehensive surveillance techniques. City indicators associated with improved GFT surveillance provide some insight into the variability of GFT effectiveness. For example, populations with lower socioeconomic status may have a greater tendency to initially turn to the Internet for health questions, thus leading to increased GFT effectiveness. GFT has the potential to provide valuable information to ED providers for patient care and to administrators for ED surge preparedness.
authors.affiliation: Johns Hopkins University, School of Medicine, Hampstead, NC, United States. jjklem@gmail.com.
authors.forename: Joseph Jeffrey
authors.identifier: 0000-0001-7662-0458
authors.initials: JJ
authors.lastname: Klembczyk
authors.forename: Mehdi
authors.identifier: 0000-0002-7352-6244
authors.initials: M
authors.lastname: Jalalpour
authors.forename: Scott
authors.identifier: 0000-0002-7143-7635
authors.initials: S
authors.lastname: Levin
authors.forename: Raynard E
authors.identifier: 0000-0002-9204-1576
authors.initials: RE
authors.lastname: Washington
authors.forename: Jesse M
authors.identifier: 0000-0003-2292-3052
authors.initials: JM
authors.lastname: Pines
authors.forename: Richard E
authors.identifier: 0000-0002-5463-8283
authors.initials: RE
authors.lastname: Rothman
authors.forename: Andrea Freyer
authors.identifier: 0000-0002-7164-014X
authors.initials: AF
authors.lastname: Dugas
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D062665:Epidemiological Monitoring; D005260:Female; D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology*; D020407:Internet; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D057386:Search Engine / Q000639:trends*; D012621:Seasons; D062206:Spatial Analysis; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D055815:Young Adult
keywords: emergency department; google flu trends; influenza; infoveillance; surveillance