Internet2 and Public Health Surveillance

Internet2 and Public Health Surveillance

• 1.
  Office of Surveillance,Epidemiology, and Laboratory Services Public Health Surveillance Program Office Digital Disease Detection: Novel Approaches in Public Health Surveillance Taha A. Kass-Hout, MD, MS Deputy Director for Information Science and BioSense Program Manager Division of Healthcare Information (DHI) Public Health Surveillance Program Office (PHSPO) Office of Surveillance, Epidemiology, and Laboratory Services (OSELS) Centers for Disease Control & Prevention (CDC) Any views or opinions expressed here do not necessarily represent the views of the CDC, HHS, or any other entity of the United States government. Furthermore, the use of any product names, trade names, images, or commercial sources is for identification purposes only, and does not imply endorsement or government sanction by the U.S. Department of Health and Human Services. The International meeting of Internet2 Renaissance Waverly Hotel Sunday October 30th, 2010: 13:30–14:15 Atlanta, GA (USA)
• 2.
    The PublicHealth Surveillance Challenge   Public Health Surveillance and the Internet– the State of the Art   The Possibilities for Internet2
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    Surveillance isa global challenge that knows no borders   The importance of timely detection   Limitations of traditional reporting systems   Hierarchical lines of reporting   Variance across different countries   Multitude of potential data sources   Real-world lessons from SARS and H1N1
• 4.
  WHO reported outbreaks,1996-2009 n=398  
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    Median of12 [95% CI, 9 —18] days between suspected and confirmed reports   Countries with a high GDP tended to have shorter lags (Pearson correlation -0.4; 95% CI, -0.6 — -0.2) Brownstein JS, Freifeld CC, Chan EH, Keller M, Sonricker AL, Mekaru SR, Buckeridge DL. Information Technology and Global Surveillance of Cases of 2009 H1N1 Influenza. New England Journal of Medicine 2010;362(18):1731-1735.
• 6.
    Event-based   ad-hocunstructured reports issued by formal or informal sources…   Indicator-based   number of cases, rates, proportion of strains… Adapted from T. Kass-Hout, 2009
• 7.
    Waiting forconfirmed laboratory results is potentially hazardous   Surveillance is increasingly relying on informal sources of data   This creates a data deluge with lots of noise   Fusion of multiple channels of data which varying levels of confidence   Collaboration and expert opinion is as important as “pure” data   Existing tools may generate “false alarms”Adapted from J. Brownstein, 2010
• 8.
  J. Brownstein etal. 2010. New England Journal of Medicine.
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    Professional Social Networks  GPHIN   ProMed   Geo-Sentinel   Mechanical Turk   Crawling, Aggregation, Crowd Sourcing and Networking   HealthMap   Ushahidi   Facebook   Mobile Applications   EpiSurveyor   Frontline SMS   Geo Alerting   Outbreak MD
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  Automated  Extrac.on  Automated  Feed   Community  Input     Added Value (1) Discovery of new content (2) Two-way contextualization (3) Validation studies
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  www.healthmap.org
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  www.flu.gov
• 13.
  Adapted from Dzenowagi,WHO, 2005 and T. Kass-Hout, 2009 |   ITU estimates two billion people online by end 2010   Access to mobile networks available to over 90% of world population   143 countries offer 3G services http://www.itu.int/net/pressoffice/press_releases/2010/39.aspx
• 14.
  http://www.mission4636.org
• 15.
  www.frontlinesms.com Outbreaks Near MeApp: H1N1: iPhone submissions vs CDC sentinel surveillance
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    Can’t mine  all possible sources   in all languages   all data types   Delay required for searching, curating and processing   Massive bandwidth and processing requirements   Resource limited process (both machine and human)
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  Automated healthcare data (laboratory,immunization, notifiable conditions, syndromic, personal health records, …)
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    Enlisting currentInternet2 partners to collaborate on surveillance efforts   Explore new data types and analytical methods enabled by Internet2   Use Internet2 Infrastructure to increase   Bandwidth and processing capabilities   Performance and Operational Reliability   Support collaborative Public Health Surveillance Research   Increase the power of existing public health networks
• 20.
    John Brownstein,PhD   Clark Freifeld, MS   Seth Foldy, MD, MPH   Sam Groseclose, DVM, MPH   James Buehler, MD   Walton (John) Page, BS, BA
• 21.
  Taha A. Kass-Hout,MD, MS Deputy Director for Information Science and BioSense Program Manager Division of Healthcare Information (DHI) Public Health Surveillance Program Office (PHSPO) Office of Surveillance, Epidemiology, and Laboratory Services (OSELS) Centers for Disease Control & Prevention (CDC) Any views or opinions expressed here do not necessarily represent the views of the CDC, HHS, or any other entity of the United States government. Furthermore, the use of any product names, trade names, images, or commercial sources is for identification purposes only, and does not imply endorsement or government sanction by the U.S. Department of Health and Human Services. Thank You!