Biosurveillance

A digitally colorized scanning electron micrograph depicts numerous filamentous Ebola virus particles in green, budding from a chronically infected VERO E6 cell in orange at 25,000X magnification. (Courtesy of National Institute of Allergy and Infectious Diseases/Released)
A digitally colorized scanning electron micrograph depicts numerous filamentous Ebola virus particles in green, budding from a chronically infected VERO E6 cell in orange at 25,000X magnification. (Courtesy of National Institute of Allergy and Infectious Diseases/Released)

Presented: October 29, 2015 2:00 pm
Presented by: Dr. Tim Karpetsky

This webinar focuses on available biosurveillance data and data sources, preparation, and attributes. The recent Ebola outbreak in West Africa is one example of using biosurveillance data and the limitations of consequence acceptance and management in resource-limited locations.

While early warning and situational awareness are important, that importance is lost without rapid, decisive, and appropriate actions. Further, the One World Health paradigm and the key role of animals in certain human disease outbreaks is stressed.

Which data streams or, more likely which combination of data streams, will best serve various biosurveillance goals is largely unknown. Cloud computing, High-Performance Computing, and Advanced Predictive Analytics/Machine Learning are being applied to streaming biosurveillance data to clarify the practical significance of multiple data stream analysis in identifying and predicting disease outbreaks. Tactical biosurveillance is also considered in terms of data generation by a number of sensors to provide warfighters immediate situational awareness.

The lack of a globally linked, interoperable system to prevent infectious disease threats, detect outbreaks in real-time, and respond effectively before they become epidemics is discussed, along with technical challenges and progress being made.

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