Anticipating risk before it happens

Transforming surveillance data into forecasts using geospatial, statistical, and machine learning approaches.

Focus areas:

• Development of spatial and statistical risk models to map transmission patterns and identify hotspots
• Climate-informed and multi-disease forecasting to anticipate changes in risk over time
• Early warning and predictive intelligence tools to support timely and targeted public health action