title: Surveillance Tools Emerging From Search Engines and Social Media Data for Determining Eye Disease Patterns.
abstract: OBJECTIVE
  Internet-based search engine and social media data may provide a novel complementary source for better understanding the epidemiologic factors of infectious eye diseases, which could better inform eye health care and disease prevention.
  
  
  OBJECTIVE
  To assess whether data from internet-based social media and search engines are associated with objective clinic-based diagnoses of conjunctivitis.
  
  
  METHODS
  Data from encounters of 4143 patients diagnosed with conjunctivitis from June 3, 2012, to April 26, 2014, at the University of California San Francisco (UCSF) Medical Center, were analyzed using Spearman rank correlation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivitis with allergic conjunctivitis. Data for patient encounters with diagnoses for glaucoma and influenza were also obtained for the same period and compared with conjunctivitis. Temporal patterns of Twitter and Google web search data, geolocated to the United States and associated with these clinical diagnoses, were compared with the clinical encounters. The a priori hypothesis was that weekly internet-based searches and social media posts about conjunctivitis may reflect the true weekly clinical occurrence of conjunctivitis.
  
  
  METHODS
  Weekly total clinical diagnoses at UCSF of nonallergic conjunctivitis, allergic conjunctivitis, glaucoma, and influenza were compared using Spearman rank correlation with equivalent weekly data on Tweets related to disease or disease-related keyword searches obtained from Google Trends.
  
  
  RESULTS
  Seasonality of clinical diagnoses of nonallergic conjunctivitis among the 4143 patients (2364 females [57.1%] and 1776 males [42.9%]) with 5816 conjunctivitis encounters at UCSF correlated strongly with results of Google searches in the United States for the term pink eye (ρ, 0.68 [95% CI, 0.52 to 0.78]; P < .001) and correlated moderately with Twitter results about pink eye (ρ, 0.38 [95% CI, 0.16 to 0.56]; P < .001) and with clinical diagnosis of influenza (ρ, 0.33 [95% CI, 0.12 to 0.49]; P < .001), but did not significantly correlate with seasonality of clinical diagnoses of allergic conjunctivitis diagnosis at UCSF (ρ, 0.21 [95% CI, -0.02 to 0.42]; P = .06) or with results of Google searches in the United States for the term eye allergy (ρ, 0.13 [95% CI, -0.06 to 0.32]; P = .19). Seasonality of clinical diagnoses of allergic conjunctivitis at UCSF correlated strongly with results of Google searches in the United States for the term eye allergy (ρ, 0.44 [95% CI, 0.24 to 0.60]; P < .001) and eye drops (ρ, 0.47 [95% CI, 0.27 to 0.62]; P < .001).
  
  
  CONCLUSIONS
  Internet-based search engine and social media data may reflect the occurrence of clinically diagnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the epidemiologic factors of conjunctivitis.
authors.affiliation: Department of Ophthalmology, University of California San Francisco.
authors.forename: Michael S
authors.initials: MS
authors.lastname: Deiner
authors.affiliation: Department of Ophthalmology, University of California San Francisco2F. I. Proctor Foundation, University of California San Francisco3Department of Epidemiology and Biostatistics, University of California San Francisco4Global Health Sciences, University of California San Francisco.
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Lietman
authors.affiliation: Department of Ophthalmology, University of California San Francisco2F. I. Proctor Foundation, University of California San Francisco.
authors.forename: Stephen D
authors.initials: SD
authors.lastname: McLeod
authors.affiliation: Massachusetts Eye and Ear Infirmary, Department of Ophthalmology, Harvard Medical School, Boston.
authors.forename: James
authors.initials: J
authors.lastname: Chodosh
authors.affiliation: Department of Ophthalmology, University of California San Francisco2F. I. Proctor Foundation, University of California San Francisco3Department of Epidemiology and Biostatistics, University of California San Francisco.
authors.forename: Travis C
authors.initials: TC
authors.lastname: Porco
mesh_terms: D000328:Adult; D005128:Eye Diseases / Q000453:epidemiology*; D005260:Female; D006801:Humans; D020407:Internet / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009017:Morbidity / Q000639:trends; D009885:Ophthalmology / Q000706:statistics & numerical data*; D011159:Population Surveillance / Q000379:methods*; D057386:Search Engine / Q000706:statistics & numerical data*; D012621:Seasons; D061108:Social Media; D014481:United States / Q000453:epidemiology