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The potential threat of bioterrorism along with the emergence of new or existing drug resistant strains of influenza virus, added to expanded global travel, have increased vulnerability to epidemics or pandemics and their aftermath. The same factors have also precipitated urgency for having better, faster, sensitive, and reliable syndromic surveillance systems. Prescription sales data can provide surrogate information about the development of infectious diseases and therefore serve as a useful tool in syndromic surveillance. This study compared prescription sales data from a large drug retailing pharmacy chain in the United States with Google Flu trends surveillance system data as a flu activity indicator. It was found that the two were highly correlated. The correlation coefficient (Pearson ‘r’) for five years' aggregate data (2007–2011) was 0.92 (95% CI, 0.90–0.94). The correlation coefficients for each of the five years between 2007 and 2011 were 0.85, 0.92, 0.91, 0.88, and 0.87 respectively. Additionally, prescription sales data from the same large drug retailing pharmacy chain in the United States were also compared with US Outpatient Influenza-like Illness Surveillance Network (ILINet) data for 2007 by Centers for Disease Control and Prevention (CDC). The correlation coefficient (Pearson ‘r’) was 0.97 (95% CI, 0.95–0.98).

Comparison: Flu Prescription Sales Data from a Retail Pharmacy in the US with Google Flu Trends and US ILINet (CDC) Data as Flu Activity Indicator