Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits

Abstract

BackgroundInfluenza 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.ObjectiveThe 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.MethodsUsing 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.ResultsCorrelation 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.ConclusionsGFT 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.

Can Google Trends data improve forecasting of Lyme disease incidence?

“…The online data search volumes showed a significant correlation with the observed weekly incidence. A temporal similarity has already been described in two previous studies (Pesala et al, 2017;Seifter et al, 2010) Cook, Conrad, Fowlkes, & Mohebbi, 2011;Dugas et al, 2012Dugas et al, , 2013Klembczyk et al, 2016;Ortiz et al, 2011), as already discussed in the Section 1. To avoid pitfalls that led to the failure of this application, we have used the results from Google searches to supplement the traditional method (instead of replacing it).…”

“…Google Trends, Twitter and other social media platform data offer an interesting tool to monitor public attention with regard to specific infectious diseases (Al‐Surimi, Khalifa, Bahkali, El‐Metwally, & Househ, ; Goff, Kullar, & Newland, ; Martin, Xu, & Yasui, ). Several studies have shown that this quantifiable attention is a good proxy for disease activity (Dugas et al, ; Klembczyk et al, ; Martin, Lee, & Yasui, ; Pollett et al, ; Strauss, Castro, Reintjes, & Torres, ; Thompson, Malik, Gumel, Strome, & Mahmud, ). Thus, these data can help to monitor and predict infectious diseases, especially in developing areas where traditional epidemiologic surveillance faces multiple challenges (Gluskin, Johansson, Santillana, & Brownstein, ; Strauss et al, ; Teng et al, ).…”

“…studies have shown that this quantifiable attention is a good proxy for disease activity (Dugas et al, 2012;Klembczyk et al, 2016;Martin, Lee, & Yasui, 2016;Pollett et al, 2017;Strauss, Castro, Reintjes, & Torres, 2017;Thompson, Malik, Gumel, Strome, & Mahmud, 2014). Thus, these data can help to monitor and predict infectious diseases, especially in developing areas where traditional epidemiologic surveillance faces multiple challenges (Gluskin, Johansson, Santillana, & Brownstein, 2014;Strauss et al, 2017;Teng et al, 2017).…”

Using Search Engines to Investigate Shared Migraine Experiences

“…Google Flu Trends, which employed the service to provide information about flu activity in many countries, is perhaps the most well-known use of Google Trends data. [11][12][13] Other areas where Google Trends has been used are foot and ankle pain, 14 bariatric surgery, 15 and Lyme disease. 16 Tracking searches for disease terms can provide insight into possible reasons for searches of those terms.…”

Recent trends in oropharyngeal cancer funding and public interest

“…Studying Internet search patterns has facilitated opportunities for evaluating public interest encompassing a variety of topics. Extrapolating data from a portion of 3 billion searches daily, Google Trends represents a powerful tool for gauging public interest and has demonstrated its unique value in numerous analyses . Upon comparison of search volume trends with other common cancers, OPC demonstrated a notable increase over the 11‐year period available, suggesting growing public interest (Fig.…”