Breakout Sessions
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Interactive and discussion-oriented
Six major topic areas
Sign up sheets
Moderator designated for each session
Recorder needed
Discussion points presented to large
group tomorrow
TM
Common Issues
• Coordination and communication
among jurisdictions and at different
levels of public health
• Time and resource constraints
• Role of social networking
• Lessons learned
TM
Detection and Analysis
• What detection and analysis methods are
available and how are they similar or
different?
• What types of events might they detect and
why?
• What do monitors need to maintain a working
knowledge about statistical algorithms?
• What epidemiologic analyses can or should
follow the initial statistically significant
anomaly notification?
• What is the appropriate geographic unit of
analysis?
TM
System Visualizations and
Functionalities
• What system visualizations,
functionalities, and tools are most
useful in monitoring and analyzing
biosurveillance data?
• What needs are systems currently
meeting/not meeting?
• What improvements can be made to
improve utility?
TM
Monitoring and Anomaly
Characterization
• What are the protocols for monitoring
biosurveillance data?
• What information is necessary to
characterize anomalies and what specific
aspects indicate an anomaly is of potential
importance?
• What information is needed beyond what the
system can provide, and how can this
information be obtained?
TM
Follow-up, Reporting, and
Communication Protocols
• When it is determined that an
escalation or follow up investigation is
appropriate, what are the appropriate
protocols?
• What information is needed for
escalation reporting?
• What information and in what format
should reports include?
TM
Consolidating Information
• How do we address/resolve the use of
multiple systems?
• How do we consolidate information,
coordinate, and communicate across
jurisdictions, systems, and analytical
results?
TM
Situational Awareness
• How do we define situational awareness?
• How can biosurveillance systems meet the
need for situational awareness (in addition to
early detection of events)?
• What types of scenarios would require
situational awareness, and what data
analyses, system functionalities, and data
visualizations would provide the needed
information?
TM