Analyzed multi-source public health datasets to identify infection trends across regions and time using exploratory data analysis techniques. Cleaned and prepared raw datasets by handling missing values, normalizing data types, and detecting outliers to ensure data quality for analysis. Used R and dplyr to perform data wrangling and develop visualizations that highlighted infection patterns and potential policy-related shifts in case trends. The analysis focused on extracting meaningful insights from both aggregated and raw datasets to better understand how public health interventions influenced the spread of COVID-19 across different regions and demographics.