HealthMap.org: Aggregation of Online Media Reports for Global Infectious Disease Intelligence / Forum One Web Executive Seminar

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    Surveillance sans frontières: Internet-based emerging infectious disease intelligence

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    HealthMap.org: Aggregation of Online Media Reports for Global Infectious Disease Intelligence / Forum One Web Executive Seminar - Presentation Transcript

    1. Aggregation of online media reports for global infectious disease intelligence Clark Freifeld Research Software Developer Harvard Medical School Children’s Hospital Informatics Program Harvard-MIT Division of Health Sciences and Technology
    2. Early reporting of SARS Nov 2002 Mar 2003 Progression of outbreak Electronic Surveillance Cases of atypical pneumonia Foshan Nov 16th Infected Chinese Doctor Hong Kong hotel Feb 21st 305 Cases of acute resp Guangdong Province Feb 11th Pharma report Guangdong Province November 27 Media reports Guangdong Province Feb 10 Astute physician on ProMED Feb 10 Initial WHO Report Feb 25 Official WHO Report March 10
      • Traditional Surveillance
      • Lack of infrastructure
      • Low level training
      • Gaps in coverage
      • Poor information flow
      • Internet-based Surveillance
      • Abundant cheap/free resource
      • Detailed local information
      • Near real-time reporting
      • Less susceptible to political pressure
    3. Source of outbreak news verified by WHO Adapted from Heymann 2001
    4. Limitations of Web-based surveillance
      • Abundance of resources but none comprehensive
      • Information is unstructured -- free text
      • Each has geographic, expertise, population gaps
      • Lack of integration between tools and information sources
      • No synthesized view of the current state of global health
      Brownstein et al. Institute of Medicine. 2007.
    5. www.healthmap.org
    6. HealthMap Objectives
      • Automated, real-time, multi-stream
      • Supplement existing clinical and public health systems
      • Free and open resource
      • Serve the public as well as professionals
    7. HealthMap Article Processing EXTRACTION 8 Feeds;>10,000 sites Every hour; 24/7 TEXT MINING 1500 disease patterns 4000 location patterns BAYES FILTERING >5 million phrases 90-94% accuracy DUPLICATE ID Text Matching Similarity Score
    8.  
    9.  
    10.  
    11.  
    12. Emerging Disease Surveillance Current Lyme disease (Brownstein et. al. Env Health Perspectives) 2020 2050 2080 West Nile virus (Brownstein et. al. Emerging Infectious Diseases)
    13.  
    14. Implementation Background
      • Came about as a combination of new software tools and existing epidemiology challenges
      • Linux, Apache, MySQL, PHP
        • All free, open source tools, widely available
      • Prototype early
        • Start simple, think big
    15. Evolving Systems and Datasets - Challenges
      • Until now, focus has been knowledge management
      • Methods for analyzing news are currently under-developed
      • Unknown data characteristics: geographic, population, availability
      • Little assessment – sensitivity, specificity, signal:noise, timeliness
       Evaluating statistical characteristics of data is a first step
    16. Data Quality
      • News Sources
        • Local
        • National
        • International
      Specificity Reliability Timeliness
    17. Data Quality
      • News Sources
        • Local
        • National
        • International
      Timeliness Specificity Reliability
    18. Data Quality
      • News Sources
        • Local
        • National
        • International
      • Mailing lists (ProMED)
      • Multi-national surveillance (Eurosurveillance)
      • Validated official global alerts (WHO)
      Timeliness Specificity Reliability
    19. Data Quality
      • Clickstream/Keyword Searching
      • Blogs/Chatrooms
      • News Sources
        • Local
        • National
        • International
      • Mailing lists (ProMED)
      • Multi-national surveillance (Eurosurveillance)
      • Validated official global alerts (WHO)
      Timeliness Specificity Reliability
    20. Alert Volume by Source
      • Google News: 3194 (22.8 per day)
      • ProMED: 985 (7.0 per day)
      • WHO: 45 (0.32 per day)
    21. Multi-Stream Alarming: Heat Index
      • Meta-alert composite score, based on
        • Number of sources providing information at a particular location
        • Recentness of alert
      • Marker algorithm
        • Exponentially weighted alerts
        • Increase heat (redness) for more recent event and higher impact
      low high
    22. www.healthmap.org
    23. Geographic Representation
      • Alerts by country
        • 1-USA: 4351
        • 2-UK: 1018
        • 3-Canada: 880
        • 4-China:737
    24. Multi-lingual Surveillance
    25.  
    26. Coverage Comparison: Argentina
      • English News
        • Bovine Anthrax
        • Citrus Canker
    27. Coverage Comparison: Argentina
      • Spanish News
        • Trichinosis
        • Bronchiolitis
        • Rotavirus
        • Influenza
    28. Case Study: Legionnaire’s in Spain June 30th Google (ES) Alert Alert #1 July 2nd ProMED-mail Alert Alert #2 July 4th Google (EN) Alert Alert #3
    29. Early Stats
      • 150 alerts per day
      • > 34,000 alerts so far
      • Alerts in 201 countries
      • 169 disease categories
    30. Usage
      • 500-600 visits per day
      • 80,000 unique visitors since 9/06 launch
      • Top visitors:
        • dhs.gov
        • cdc.gov
        • state.fl.us
        • reinhartfoodservice.com
        • state.id.us
    31. Public Health Resource
    32. Various implementations International Society for Infectious Disease Liberty Science Museum, NYC HHS Command Center
    33. Tool for general population
    34. Future Directions
      • Improve existing filtering algorithms
      • More sensitive, noisy sources
      • More filters: number of cases, species affected
      • More languages
      • Other areas:
        • Environmental health
        • Chronic disease
        • Violence, conflict zones
        • Pharmaceuticals
      • Your ideas
    35. Acknowledgments
      • Children’s Hospital Informatics Program
      • @ Harvard-MIT HST
      • John Brownstein, PhD
      • Ken Mandl, MD MPH
      • Ben Reis, PhD
      • Mikaela Keller, PhD
      • Isaac Kohane, MD PhD
      • Carlo Venis (Wabash)
      • Roger Araujo (Peru NMRCD)
      • David Blazes (Peru NMRCD)
      • Aranka Anema (UBC)
      • Larry Madoff (ProMED)
      • Funding
      • Google Foundation
      • National Library of Medicine (NLM)
      • Centers for Disease Control and Prevention
      • Canadian Institutes of Health Research (CIHR)
    36. Contact
      • [email_address]
      • www.healthmap.org
      • www.chip.org

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