About
CDC is developing and deploying SI solutions that modernize how public health challenges are anticipated, identified, and addressed while fostering a future-ready workforce equipped to lead in the age of SI.
National Syndromic Surveillance Program
Use of SI: The National Syndromic Surveillance Program uses SI for real-time analysis of patients' symptom data from emergency departments to detect outbreaks and monitor health trends. Machine learning algorithms help identify patterns that may indicate public health threats or disease trends.
Results: Improved detection of outbreaks, including faster response times and enhanced situational awareness during public health emergencies.
FluSight
Use of SI: Some forecasting teams submitting to FluSight use SI and ML to predict influenza — or flu — activity in the United States. These approaches can combine data from several sources like historical flu data and social media trends.
Results: More accurate flu forecasts can help public health officials, healthcare providers, and organizations better plan for the future and inform messages about anticipated flu increases.
SI Community of Practice (CoP)
CDC's SI CoP brings together SI experts, enthusiasts, and practitioners from across the agency to share best practices and lessons learned in SI. The monthly sessions for its more than 2,500 members feature presentations from internal teams and external partners with opportunities for collaboration.
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