Advancing a framework to enable characterization and evaluation of data streams useful for biosurveillance

Area of Science:

• Public Health
• One Health
• Biothreat Detection

Background:

• Biosurveillance integrates diverse ideas for detecting and mitigating biological threats.
• Global and interdisciplinary biosurveillance requires cross-domain information and resources.
• Current biosurveillance systems and tools have varying, often unknown, effectiveness.

Purpose of the Study:

• To present a novel approach for conceptualizing biosurveillance based on fundamental data streams.
• To systematically structure a universally applicable framework for evaluating biosurveillance activities.
• To propose the Biosurveillance Data Stream Framework as a starting point for a standardized biosurveillance lexicon.

Main Methods:

• Examined literature on biosurveillance and infectious disease surveillance systems.
• Analyzed information from operational biosurveillance systems.
• Consulted with experts in the field of biosurveillance.
• Developed criteria for the data stream framework.

Main Results:

• A novel Biosurveillance Data Stream Framework and associated definitions were developed.
• The framework facilitates the characterization of existing and emerging data streams.
• The framework was used to design a relational database schema and a decision support tool.

Conclusions:

• The proposed framework offers a standardized approach to understanding and evaluating biosurveillance.
• This systematic structuring aids in assessing the impact and utility of biosurveillance activities.
• The framework supports the development of a common language for biosurveillance research and practice.