International Partnerships and Public Health update to the Internet2 Fall Member meeting, Atlanta, GA USA on Sunday October 31st, 2010.

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 Public Health
Surveillance Challenge
 Public Health
Surveillance and the
Internet– the State of
the Art
 The Possibilities for
Internet2

3.  Surveillance is a 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

5.  Median of 12 [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-hoc unstructured
reports issued by formal or
informal sources…
 Indicator-based
 number of cases, rates,
proportion of strains…
Adapted from T. Kass-Hout, 2009

7.  Waiting for confirmed
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 et al. 2010. New England Journal of Medicine.

9.  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

10. Automated
Extrac.on
Automated
Feed
Community
Input
Added Value
(1) Discovery of new content
(2) Two-way contextualization
(3) Validation studies

11. www.healthmap.org

12. 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 Me App: H1N1: iPhone submissions vs CDC
sentinel surveillance

17.  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)

18. Automated healthcare data
(laboratory, immunization,
notifiable conditions, syndromic,
personal health records, …)

19.  Enlisting current Internet2 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!