Context:
The client wanted to study the spread of COVID-19 across different regions, identify key risk factors, and forecast case trends to guide timely public health interventions and healthcare resource planning.

Resolution:
Our team used Python’s ecosystem to develop clinical and epidemiological analysis models using historical case and patient data. The analysis showed that older age and comorbidities were strong predictors of hospitalization.

Result:
Forecasting identified case surges about two weeks in advance, helping policymakers prepare hospital capacity. Combining clinical risk factors with epidemiological trends provided actionable insights for intervention planning and response strategies.