title: Using internet search queries for infectious disease surveillance: screening diseases for suitability.
abstract: BACKGROUND
  Internet-based surveillance systems provide a novel approach to monitoring infectious diseases. Surveillance systems built on internet data are economically, logistically and epidemiologically appealing and have shown significant promise. The potential for these systems has increased with increased internet availability and shifts in health-related information seeking behaviour. This approach to monitoring infectious diseases has, however, only been applied to single or small groups of select diseases. This study aims to systematically investigate the potential for developing surveillance and early warning systems using internet search data, for a wide range of infectious diseases.
  
  
  METHODS
  Official notifications for 64 infectious diseases in Australia were downloaded and correlated with frequencies for 164 internet search terms for the period 2009-13 using Spearman's rank correlations. Time series cross correlations were performed to assess the potential for search terms to be used in construction of early warning systems.
  
  
  RESULTS
  Notifications for 17 infectious diseases (26.6%) were found to be significantly correlated with a selected search term. The use of internet metrics as a means of surveillance has not previously been described for 12 (70.6%) of these diseases. The majority of diseases identified were vaccine-preventable, vector-borne or sexually transmissible; cross correlations, however, indicated that vector-borne and vaccine preventable diseases are best suited for development of early warning systems.
  
  
  CONCLUSIONS
  The findings of this study suggest that internet-based surveillance systems have broader applicability to monitoring infectious diseases than has previously been recognised. Furthermore, internet-based surveillance systems have a potential role in forecasting emerging infectious disease events, especially for vaccine-preventable and vector-borne diseases.
authors.affiliation: School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia. gabriel.milinovich@qut.edu.au.|Infectious Disease Epidemiology Unit, School of Population Health, The University of Queensland, Brisbane, Australia. gabriel.milinovich@qut.edu.au.
authors.forename: Gabriel J
authors.initials: GJ
authors.lastname: Milinovich
authors.affiliation: Freelance developer, Bundaberg, Australia. simon.m.r.avril@gmail.com.
authors.forename: Simon M R
authors.initials: SM
authors.lastname: Avril
authors.affiliation: Research School of Population Health, ANU College of Medicine, Biology and Environment, The Australian National University, Canberra, Australia. director.rsph@anu.edu.au.
authors.forename: Archie C A
authors.initials: AC
authors.lastname: Clements
authors.affiliation: Department of Pediatrics, Harvard Medical School and Children's Hospital Informatics Program, Boston Children's Hospital, Boston, USA. john.brownstein@childrens.harvard.edu.
authors.forename: John S
authors.initials: JS
authors.lastname: Brownstein
authors.affiliation: School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia. s.tong@qut.edu.au.
authors.forename: Shilu
authors.initials: S
authors.lastname: Tong
authors.affiliation: School of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia. w2.hu@qut.edu.au.
authors.forename: Wenbiao
authors.initials: W
authors.lastname: Hu
mesh_terms: D001315:Australia / Q000453:epidemiology; D003141:Communicable Diseases / Q000453:epidemiology*; D016208:Databases, Factual / Q000592:standards / Q000639:trends; D018563:Disease Notification / Q000592:standards*; D062665:Epidemiological Monitoring; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet / Q000706:statistics & numerical data*; D057386:Search Engine / Q000592:standards / Q000639:trends