title: Google unveils a glimpse of allergic rhinitis in the real world.
abstract: Google Trends (GT) is a Web-based surveillance tool used to explore the searching trends of specific queries on Google. Recent studies have suggested the utility of GT in predicting outbreaks of influenza and other diseases. However, this utility has not been thoroughly evaluated for allergic diseases. Therefore, we investigated the utility of GT for predicting the epidemiology of allergic rhinitis. In the USA, GT for allergic rhinitis showed repetitive seasonality that peaked in late April and early May and then rapidly decreased, and a second small peak occurred in September. These trends are highly correlated with the searching trends for other queries such as 'pollen count', antihistamines such as loratadine and cetirizine (all r > 0.88 and all P < 0.001), and even the total pollen count collected from 21 pollen counters across the USA (r = 0.928, P < 0.001). Google Trends for allergic rhinitis was similar to the monthly changes in rhinitis symptoms according to the US National Health and Nutrition Examination Survey III, sales for Claritin(®) and all over-the-counter antihistamines, and the number of monthly page views of 'claritin.com'. In conclusion, GT closely reflects the real-world epidemiology of allergic rhinitis in the USA and could potentially be used as a monitoring tool for allergic rhinitis.
authors.affiliation: Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea; Institute of Allergy and Clinical Immunology, Seoul National University Medical Research Center, Seoul, Korea; Division of Allergy and Clinical Immunology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do, Korea.
authors.forename: M-G
authors.initials: MG
authors.lastname: Kang
authors.forename: W-J
authors.initials: WJ
authors.lastname: Song
authors.forename: S
authors.initials: S
authors.lastname: Choi
authors.forename: H
authors.initials: H
authors.lastname: Kim
authors.forename: H
authors.initials: H
authors.lastname: Ha
authors.forename: S-H
authors.initials: SH
authors.lastname: Kim
authors.forename: S-H
authors.initials: SH
authors.lastname: Cho
authors.forename: K-U
authors.initials: KU
authors.lastname: Min
authors.forename: S
authors.initials: S
authors.lastname: Yoon
authors.forename: Y-S
authors.initials: YS
authors.lastname: Chang
mesh_terms: D001315:Australia / Q000453:epidemiology; D006801:Humans; D011159:Population Surveillance / Q000379:methods; D065631:Rhinitis, Allergic / Q000453:epidemiology*; D061108:Social Media; D006113:United Kingdom / Q000453:epidemiology; D014481:United States / Q000453:epidemiology
keywords: Google; allergic rhinitis; allergy; epidemiology; pollen count