Technologies for Pandemic Influenza Surveillance and Response

1. Technologies for Pandemic InfluenzaSurveillance and Response • John PageResearch EngineerNorthrop Grumman Corporation • John.page@ngc.com

2. Types of Applicable Technologies • Geospatial Visualization • Biosurveillance • Disease Spread Modeling • Predictive (and Risk) Modeling • Natural Language Processing • Resource Allocation/Supply Chain Management • Outbreak Management • Collaboration • Situation Awareness and Decision Support

3. Geospatial Visualization • Correlation of events and environmental factors • Accurate and timely Geocoding of events is crucial Avian H5N1 Outbreaks Domestic Poultry Density Migratory Bird Paths

4. Use automation to provide early warning Numerous Systems have been demonstrated Variety of potential data sources Variety of algorithms National, State and local levels Common Issues They require a lot of care and feeding Calibration, false alarms They require training and control data Algorithms vary in effectiveness for different threats They are no better than the data fed to them Emerging trend is a system of systems approach Common infrastructure Multiple detection algorithms in parallel Biosurveillance Systems

5. Transportation Models (Air and Land) Vector Models (West Nile, etc) Socially Based Models Micro Models model single individuals and communities Complex and time consuming to run Useful for determing local response policies Not readily scaled up for global predictions Macro Models model flow among populations Coarse-grained predictions but less computationally expensive MIDAS and Imperial College of London Models support what-if’s and other responses Disease Spread Modeling

6. Predictive and Risk Modeling • Combine Linear Regression analysis and geospatial reasoning • Use a set of training data to determine which factorsare positively and negatively correlated with events • We developed a risk model based on reported avianoutbreaks in Thailand using: • Domestic Poultry Density • Population Density • Wildfowl Migration Routes • Proximity to Wetlands • Model effectively predicted the first avian outbreak in the UK. • Next step is to apply approach to Avian-Humantransmissions (Particularly in Turkey, Indonesia) Thai Training Data UK Risk Model NE US Risk Model

7. Natural Language Processing (NLP) • Finding the “needle in the haystack” of unstructured data • WHO, OIE, pandemicflu.gov, etc. • Intelligence community has had this problem for years • NLP can: • Help Identify data of interest • Assist in georeferencing and • time-stamping • Web-scraping applicationscan extract data into computableformats • Web-crawlers can increase timelyidentification

8. Resource Allocation/Supply Chain Management • Planning and Distributing limited supplies of vaccine will be very problematic. • Site Selection • Workload Balancing • Vaccine Transport andSecurity • Supply Chain Management for Stockpiles

9. Outbreak Management • Support initial containment and management of outbreaks • Coordinate agencies and experts • Identify and isolate potential exposures • CDC’s Outbreak ManagementSystem is a good example: • http://www.cdc.gov/phin/software-solutions/oms/index.html

10. Collaboration • Humans solve problems– technology is only a tool • Notification services allows experts to receive customized alerts • Communities of interest can be created dynamically • Workflow can support sophisticated interactions between users

11. Situation Awareness: What is the Big Picture? ?

12. Global Disease Surveillance Platform™ • A situation awareness platform for pandemic surveillance and response • Developed as an Independent Research and Development project by Northrop Grumman in 2006 • Dr. Taha Kass-Hout is the lead investigator • Supported the SARS response for CDC • Taha.kass-hout@ngc.com • Our aim is not to duplicate existing work, but to integrate it • Open J2EE architecture

13. GDSP™ Architecture • Ingests multiple sources of structured and unstructured data • Alert and notification features for collaboration • Incorporates feeds from biosurveillance systems and simulations • Thin (web) and thick (touch table) display options.

14. GDSP Partners and Capabilities • Free Text Searching • Google • NStein • Northrop Grumman’s Text Trainer • Biosurveillance • RODS– a Mature system that also supports over the counter sales as an indicator • GIS and Visualization • ESRI • Google Maps • Applied Minds, Inc. • Disease Modeling • Imperial College of London • We are ALWAYS looking for more partners!

15. Platform Portal Application Prototype RSS Feeds ProMed Mail User Alerts OTC Data from RODS

16. Platform Portal Application Prototype Responder Readiness Local Outbreak Management Global Status

17. Questions? • Taha A. Kass-Hout, MD, MS • Chief Scientist • Northrop Grumman Corporation • 3375 NE Expressway, Koger Center/Harvard Building • Atlanta, GA 30341 • 678-530-3568 • Taha.Kass-Hout@ngc.com • Walton “John” Page, BS, BA • Senior Health Research Engineer • Northrop Grumman Corporation • 3975 Virginia Mallory Drive • Chantilly, VA 20151 • (703) 272-5901 • John.Page@ngc.com