title: Scoping review on search queries and social media for disease surveillance: a chronology of innovation.
abstract: BACKGROUND
  The threat of a global pandemic posed by outbreaks of influenza H5N1 (1997) and Severe Acute Respiratory Syndrome (SARS, 2002), both diseases of zoonotic origin, provoked interest in improving early warning systems and reinforced the need for combining data from different sources. It led to the use of search query data from search engines such as Google and Yahoo! as an indicator of when and where influenza was occurring. This methodology has subsequently been extended to other diseases and has led to experimentation with new types of social media for disease surveillance.
  
  
  OBJECTIVE
  The objective of this scoping review was to formally assess the current state of knowledge regarding the use of search queries and social media for disease surveillance in order to inform future work on early detection and more effective mitigation of the effects of foodborne illness.
  
  
  METHODS
  Structured scoping review methods were used to identify, characterize, and evaluate all published primary research, expert review, and commentary articles regarding the use of social media in surveillance of infectious diseases from 2002-2011.
  
  
  RESULTS
  Thirty-two primary research articles and 19 reviews and case studies were identified as relevant. Most relevant citations were peer-reviewed journal articles (29/32, 91%) published in 2010-11 (28/32, 88%) and reported use of a Google program for surveillance of influenza. Only four primary research articles investigated social media in the context of foodborne disease or gastroenteritis. Most authors (21/32 articles, 66%) reported that social media-based surveillance had comparable performance when compared to an existing surveillance program. The most commonly reported strengths of social media surveillance programs included their effectiveness (21/32, 66%) and rapid detection of disease (21/32, 66%). The most commonly reported weaknesses were the potential for false positive (16/32, 50%) and false negative (11/32, 34%) results. Most authors (24/32, 75%) recommended that social media programs should primarily be used to support existing surveillance programs.
  
  
  CONCLUSIONS
  The use of search queries and social media for disease surveillance are relatively recent phenomena (first reported in 2006). Both the tools themselves and the methodologies for exploiting them are evolving over time. While their accuracy, speed, and cost compare favorably with existing surveillance systems, the primary challenge is to refine the data signal by reducing surrounding noise. Further developments in digital disease surveillance have the potential to improve sensitivity and specificity, passively through advances in machine learning and actively through engagement of users. Adoption, even as supporting systems for existing surveillance, will entail a high level of familiarity with the tools and collaboration across jurisdictions.
authors.affiliation: College of Veterinary Medicine, Michigan State University, East Lansing, MI, United States. TheresaBernardo@gmail.com
authors.forename: Theresa Marie
authors.identifier: 0000-0002-1330-3284
authors.initials: TM
authors.lastname: Bernardo
authors.forename: Andrijana
authors.initials: A
authors.lastname: Rajic
authors.forename: Ian
authors.initials: I
authors.lastname: Young
authors.forename: Katie
authors.initials: K
authors.lastname: Robiadek
authors.forename: Mai T
authors.identifier: 0000-0002-0213-4278
authors.initials: MT
authors.lastname: Pham
authors.forename: Julie A
authors.initials: JA
authors.lastname: Funk
mesh_terms: D004196:Disease Outbreaks; D006801:Humans; D009936:Organizational Innovation; D011159:Population Surveillance; D061108:Social Media
keywords: disease; review; social media; surveillance
references.citation: Online J Public Health Inform. 2011;3(1):
references.pmid: 23569598
references.citation: Zoonoses Public Health. 2009 Nov;56(9-10):477-89
references.pmid: 19175572
references.citation: J Health Serv Res Policy. 2005 Jan;10(1):45-53
references.pmid: 15667704
references.citation: Int J Nurs Stud. 2009 Oct;46(10):1386-400
references.pmid: 19328488
references.citation: Clin Infect Dis. 2008 Dec 1;47(11):1443-8
references.pmid: 18954267
references.citation: Stud Health Technol Inform. 2011;169:639-43
references.pmid: 21893826
references.citation: Emerg Infect Dis. 2010 Oct;16(10):1647-9
references.pmid: 20875307
references.citation: J Dent Res. 2011 Sep;90(9):1045-6
references.pmid: 21768305
references.citation: J Med Internet Res. 2012 Nov 15;14(6):e156
references.pmid: 23154246
references.citation: Clin Infect Dis. 2009 Nov 15;49(10):1557-64
references.pmid: 19845471
references.citation: J Med Internet Res. 2009 Mar 27;11(1):e11
references.pmid: 19329408
references.citation: PLoS One. 2011 May 04;6(5):e19467
references.pmid: 21573238
references.citation: N Engl J Med. 2009 May 21;360(21):2153-5, 2157
references.pmid: 19423867
references.citation: PLoS One. 2010 Nov 29;5(11):e14118
references.pmid: 21124761
references.citation: Foodborne Pathog Dis. 2012 Jun;9(6):487-97
references.pmid: 22571642
references.citation: Am J Public Health. 2010 Jul;100(7):1237-42
references.pmid: 20530760
references.citation: Foodborne Pathog Dis. 2012 Feb;9(2):120-4
references.pmid: 22217109
references.citation: Foodborne Pathog Dis. 2006 Winter;3(4):447-56
references.pmid: 17199527
references.citation: PLoS Negl Trop Dis. 2011 May;5(5):e1215
references.pmid: 21647309
references.citation: Bioinformatics. 2008 Dec 15;24(24):2940-1
references.pmid: 18922806
references.citation: Emerg Infect Dis. 2009 Aug;15(8):1327-8
references.pmid: 19751610
references.citation: AMIA Annu Symp Proc. 2006;:244-8
references.pmid: 17238340
references.citation: PLoS Med. 2008 Jul 8;5(7):e151
references.pmid: 18613747
references.citation: Comput Methods Programs Biomed. 2010 Oct;100(1):16-23
references.pmid: 20236725
references.citation: Nature. 2009 Feb 19;457(7232):1012-4
references.pmid: 19020500