What if public health could predict outbreaks the way we predict the weather? In this episode, Jason Asher, Director of the Center for Forecasting and Outbreak Analytics at the CDC, joins us to explain how a new generation of data tools is transforming how we detect and respond to infectious diseases. For decades, public health has relied on lagging data telling us what already happened. Asher and his team are working to change that, building systems that turn real-time data streams into actionable forecasts, simulations, and decision-making tools for health departments across the country. We dive into how these tools are already being used, from measles outbreak modeling in South Carolina to national “nowcasting” systems that fill in data gaps in real time.

Behind the Model: How Scenario Modeling Can Inform Public Health Decision-Making | CFA: Behind the Model | CDC

Modeling Handbook | CFA: Modeling and Forecasting | CDC

Learning Resources | CFA | CDC

epiENGAGE Measles Outbreak Simulator v-2.6.0

Current Epidemic Trends (Based on Rt) for States | CFA: Modeling and Forecasting | CDC

Respiratory Virus Hospitalization Surveillance Network (RESP-NET) | RESP-NET | CDC

Measles Outbreak Simulator | CFA: Modeling and Forecasting | CDC

Scenario assessment: 2025-2026 Measles Outbreak in South Carolina | CFA: Qualitative Assessments | CDC

2025-2026 Respiratory Disease Season Outlook - December Update | CFA: Qualitative Assessments | CDC

Past, Present, and Future: Reflections from a Radiation Readiness Professional

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