Enhancing disease surveillance with novel data streams: challenges and opportunities

Area of Science:

• Public Health
• Data Science
• Epidemiology

Background:

• Novel data streams (NDS), including web search and social media data, offer potential for public health surveillance.
• Current integration of NDS into public health surveillance systems is limited and lacks standardized evaluation methods.

Purpose of the Study:

• To propose a conceptual framework for integrating NDS into public health surveillance.
• To identify opportunities and essential validity/utility tests for using NDS in public health.
• To address the need for systematic evaluation and comparison of NDS against traditional surveillance data.

Main Methods:

• Conceptual framework development.
• Identification of opportunities for NDS integration across diverse public health agencies.
• Definition of minimal validity and utility testing protocols for NDS.
• Emphasis on articulating surveillance objectives and systematic NDS evaluation.

Main Results:

• A framework is presented for leveraging NDS in public health surveillance.
• Key questions regarding opportunities and necessary validity/utility tests for NDS are addressed.
• The importance of involving public health authorities and considering agency-specific objectives is highlighted.

Conclusions:

• Systematic evaluation and clear articulation of objectives are critical for effective NDS integration in public health surveillance.
• Current literature often overlooks rigorous assessment of NDS performance compared to existing methods.
• Further research and standardized practices are needed to fully realize the potential of NDS in public health.