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EVOLVE:  INTEGRATED   GLOBAL   EARLY WARNING   AND   RESPONSE   SYSTEM Innovative Support to Emergencies, Diseases, and Disasters Photo credit: IRMA (Integrated Risk Management for Africa) AMIA Spring Congress  Walt Disney World Swan May 28 th –30 th , 2009, Orlando, Florida, USA Taha Kass-Hout, MD, MS Director, Global Public Health and Informatics
Overview ,[object Object]
Late Detection –  Response DAY CASES Opportunity  for control
Early Detection and Response DAY CASES Opportunity  for control
Public Health Measures 1000  Malaria  infections (100%) 50  Malaria  notifications (5%) Specificity / Reliability Sensitivity / Timeliness ,[object Object],[object Object],[object Object],[object Object],Get as close to the bottom of the pyramid as possible Urge frequent reporting:  Weekly    daily    immediately
Public Health Measures Time ,[object Object],[object Object],Health care hotline Signal as early  as possible
[object Object],[object Object],Making Mobile Tech Work for Health  Photo Source: UN Foundation
Making Mobile Tech Work for Health  Avian Influenza Exercise: Stung Treng Province, Cambodia, October 13-15, 2008 SE Asia Region (Source: Wikipedia) The Komphun rural Health Center serves over 7000 population in the Stung Treng and neighboring provinces.  Cell phone use during the Avian Influenza Exercise: Stung Treng Province, Cambodia, October 13-15, 2008
Growth of Mobile Technologies Adapted from Dzenowagi, WHO, 2005
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Internet Penetration in Asia Pacific Nigel Collier, BioCaster:  http://biocaster.nii.ac.jp   Data Source:  http://www.internetworldstats.com/stats3.htm#asia
Urban – Rural Population, SE Asia UNCTAD Handbook of  Statistics 2004 Adapted from Dzenowagi, WHO, 2005 Year: 2002
Our Approach ,[object Object],[object Object],[object Object]
Information Sources ,[object Object],[object Object],Timeliness, Representativeness, Completeness, Predictive Value, Quality, …
Evolve Architecture and Processes Best Poster Award for Improving Public Health Investigation and Response at the Seventh Annual ISDS Conference, 2008 http://kasshout.blogspot.com/2008/12/best-poster-award-for-improving-public.html
Evolve Architecture and Processes Feature extraction, reference and baseline information Tags Multiple Data Streams User-Generated and Machine Learning Metadata Comments Spatio-temporal Flags/Alerts/Bookmarks Evolve Bot Event Classification, Characterization  and Detection Previous Event Training Data Previous Event Control Data Metadata extraction Machine learning Social network Professional feedback Anomaly detection Collaborative Spaces Hypotheses generationesting
Evolve Related items (e.g., News articles) are grouped into a thread. Threads are later associated with events (hypothesized or confirmed). Collaborative-centric  semantic tags Expert-generated  semantic tags Publish and Share Information Create a filter (by keyword, tag, topic, location, or time) and subscription (email, GeoRSS, SMS Text Messaging, Twitter, etc.) An event is monitored through a thread of items Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS   List view Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
Evolve Expert-centric  auto-generated (machine-learning) semantic tags and related items Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS   Tags are semantically ranked (a statistical  possibility  match). Users can further train the classifier by  rejecting  a  suggestion.  Users can also train the geo-locator by  rejecting or updating  a  location . Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
Evolve Map view Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS   Semantic map to monitor  topic rise or decay over time Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
Evolve Filter feature which automatically filters content by topic of interest Filter content by radius Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS   Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
Automatic Classification ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Indicators and Insights ,[object Object],[object Object],[object Object],[object Object],[object Object]
Snapshot: SE Asia, 2008-2009 ,[object Object],[object Object],[object Object],[object Object],[object Object],Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS
Snapshot: SE Asia, 2008-2009 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS
Influenza A(H1N1), 2009  Data source: Google Insights for Search http://www.google.com/insights/search/#q=%22swine%20flu%22%2C%22avian%20flu%22&cmpt=q   avian flu swine flu
Influenza A(H1N1), 2009  Data source: HashTags.org monitoring Twitter http://hashtags.org/tag/swineflu/messages
Influenza A(H1N1), 2009  Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu   Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
Influenza A(H1N1), 2009  Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu   Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD Mid-March 2009 thru May 19 th  2009
Influenza A(H1N1), 2009  Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu   Mid-March 2009 thru May 19 th  2009 Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
Influenza A(H1N1), 2009  Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu   Mid-March 2009 thru May 19 th  2009 Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
Avian Influenza: Egypt, 2009 Tracking the recent Avian Influenza Outbreak in Egypt (reports started to appear late January 2009). Data source: Africa Evolve Collaborative Workspace http://riff.instedd.org/space/AfricaAlerts
Worldwide Health Events, 2008 Data source: Early Detection and Response Evolve Collaborative Workspace http://riff.instedd.org/space/DEMOEventDetection
Acknowledgment
Through Funding from…
Thank You! In STEDD 400 Hamilton Avenue, Suite 120 Palo Alto, CA 94301, USA +1.650.353.4440 +1.877.650.4440 (toll-free in the US) [email_address] Cambodia, Photo taken by Taha Kass-Hout, October 2008  “ this pic says it all- our kids are all the same- they deserve the same ”,  Comment by Robert Gregg on Facebook, October 2008

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Evolve: InSTEDD's Global Early Warning and Response System

  • 1. EVOLVE: INTEGRATED GLOBAL EARLY WARNING AND RESPONSE SYSTEM Innovative Support to Emergencies, Diseases, and Disasters Photo credit: IRMA (Integrated Risk Management for Africa) AMIA Spring Congress Walt Disney World Swan May 28 th –30 th , 2009, Orlando, Florida, USA Taha Kass-Hout, MD, MS Director, Global Public Health and Informatics
  • 2.
  • 3. Late Detection – Response DAY CASES Opportunity for control
  • 4. Early Detection and Response DAY CASES Opportunity for control
  • 5.
  • 6.
  • 7.
  • 8. Making Mobile Tech Work for Health Avian Influenza Exercise: Stung Treng Province, Cambodia, October 13-15, 2008 SE Asia Region (Source: Wikipedia) The Komphun rural Health Center serves over 7000 population in the Stung Treng and neighboring provinces. Cell phone use during the Avian Influenza Exercise: Stung Treng Province, Cambodia, October 13-15, 2008
  • 9. Growth of Mobile Technologies Adapted from Dzenowagi, WHO, 2005
  • 10.
  • 11. Urban – Rural Population, SE Asia UNCTAD Handbook of Statistics 2004 Adapted from Dzenowagi, WHO, 2005 Year: 2002
  • 12.
  • 13.
  • 14. Evolve Architecture and Processes Best Poster Award for Improving Public Health Investigation and Response at the Seventh Annual ISDS Conference, 2008 http://kasshout.blogspot.com/2008/12/best-poster-award-for-improving-public.html
  • 15. Evolve Architecture and Processes Feature extraction, reference and baseline information Tags Multiple Data Streams User-Generated and Machine Learning Metadata Comments Spatio-temporal Flags/Alerts/Bookmarks Evolve Bot Event Classification, Characterization and Detection Previous Event Training Data Previous Event Control Data Metadata extraction Machine learning Social network Professional feedback Anomaly detection Collaborative Spaces Hypotheses generationesting
  • 16. Evolve Related items (e.g., News articles) are grouped into a thread. Threads are later associated with events (hypothesized or confirmed). Collaborative-centric semantic tags Expert-generated semantic tags Publish and Share Information Create a filter (by keyword, tag, topic, location, or time) and subscription (email, GeoRSS, SMS Text Messaging, Twitter, etc.) An event is monitored through a thread of items Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS List view Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
  • 17. Evolve Expert-centric auto-generated (machine-learning) semantic tags and related items Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS Tags are semantically ranked (a statistical possibility match). Users can further train the classifier by rejecting a suggestion. Users can also train the geo-locator by rejecting or updating a location . Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
  • 18. Evolve Map view Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS Semantic map to monitor topic rise or decay over time Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
  • 19. Evolve Filter feature which automatically filters content by topic of interest Filter content by radius Data source: SE Asia Evolve Collaborative Workspace http://riff.instedd.org/space/ProMed-MBDS Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
  • 20.
  • 21.
  • 22.
  • 23.
  • 24. Influenza A(H1N1), 2009 Data source: Google Insights for Search http://www.google.com/insights/search/#q=%22swine%20flu%22%2C%22avian%20flu%22&cmpt=q avian flu swine flu
  • 25. Influenza A(H1N1), 2009 Data source: HashTags.org monitoring Twitter http://hashtags.org/tag/swineflu/messages
  • 26. Influenza A(H1N1), 2009 Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
  • 27. Influenza A(H1N1), 2009 Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD Mid-March 2009 thru May 19 th 2009
  • 28. Influenza A(H1N1), 2009 Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu Mid-March 2009 thru May 19 th 2009 Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
  • 29. Influenza A(H1N1), 2009 Data source: A(H1N1) Evolve Collaborative Workspace http://riff.instedd.org/space/SwineFlu Mid-March 2009 thru May 19 th 2009 Yin Myo Aye, MD: ProMED MBDS Taha Kass-Hout, MD, MS: InSTEDD
  • 30. Avian Influenza: Egypt, 2009 Tracking the recent Avian Influenza Outbreak in Egypt (reports started to appear late January 2009). Data source: Africa Evolve Collaborative Workspace http://riff.instedd.org/space/AfricaAlerts
  • 31. Worldwide Health Events, 2008 Data source: Early Detection and Response Evolve Collaborative Workspace http://riff.instedd.org/space/DEMOEventDetection
  • 34. Thank You! In STEDD 400 Hamilton Avenue, Suite 120 Palo Alto, CA 94301, USA +1.650.353.4440 +1.877.650.4440 (toll-free in the US) [email_address] Cambodia, Photo taken by Taha Kass-Hout, October 2008 “ this pic says it all- our kids are all the same- they deserve the same ”, Comment by Robert Gregg on Facebook, October 2008