title: Estimating the secondary attack rate and serial interval of influenza-like illnesses using social media.
abstract: OBJECTIVE
  Knowledge of the secondary attack rate (SAR) and serial interval (SI) of influenza is important for assessing the severity of seasonal epidemics of the virus. To date, such estimates have required extensive surveys of target populations. Here, we propose a method for estimating the intrafamily SAR and SI from postings on the Twitter social network. This estimate is derived from a large number of people reporting ILI symptoms in them and\or their immediate family members.
  
  
  METHODS
  We analyze data from the 2012-2013 and the 2013-2014 influenza seasons in England and find that increases in the estimated SAR precede increases in ILI rates reported by physicians.
  
  
  RESULTS
  We hypothesize that observed variations in the peak value of SAR are related to the appearance of specific strains of the virus and demonstrate this by comparing the changes in SAR values over time in relation to known virology. In addition, we estimate SI (the average time between cases) as 2·41 days for 2012 and 2·48 days for 2013.
  
  
  CONCLUSIONS
  The proposed method can assist health authorities by providing near-real-time estimation of SAR and SI, and especially in alerting to sudden increases thereof.
authors.affiliation: Microsoft Research, Herzeliya, Israel.
authors.forename: Elad
authors.initials: E
authors.lastname: Yom-Tov
authors.affiliation: Department of Computer Science, University College London, London, UK.|Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Ingemar
authors.initials: I
authors.lastname: Johansson-Cox
authors.affiliation: Department of Computer Science, University College London, London, UK.
authors.forename: Vasileios
authors.initials: V
authors.lastname: Lampos
authors.affiliation: Farr Institute of Health Informatics Research, University College London, London, UK.
authors.forename: Andrew C
authors.initials: AC
authors.lastname: Hayward
mesh_terms: D004739:England / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D007251:Influenza, Human / Q000453:epidemiology*; D012621:Seasons; D061108:Social Media; D012944:Social Support
keywords: Influenza-like illness; secondary attack rate; social media