Context:
A healthcare organization wanted to monitor influenza like illness trends across multiple regions to detect outbreaks at an early stage. The goal was to use R for time series modeling and real-time visualization to support rapid public health response and resource planning.

Resolution:
Our team developed an interactive Shiny dashboard that displayed real-time incidence trends, predictive forecasts, and automated outbreak alerts. Time series models were applied to identify patterns and anticipate spikes in reported cases. To streamline reporting, we automated weekly surveillance reports for the client, ensuring consistent and timely communication of insights.

Result:
Forecasting enabled advance preparation for hospital surge capacity, reducing strain on the healthcare system during peak influenza periods. The improved surveillance approach strengthened outbreak response planning and enhanced overall public health readiness.