cjana1702 / Covid19_Analysis_PySpark

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COVID-19 Impact Analysis: Unveiling High-Risk Zones Through Advanced Data Techniques on AWS EMR

Project Vision

This project delves into COVID-19's impact in the USA, aiming to pinpoint and mitigate high-risk zones for the outbreak. Utilizing the power of PySpark and Spark SQL on AWS EMR, and Docker for development, the analysis focuses on discerning crucial patterns in mask usage, vaccination trends, and state-wise risk assessment.

Objective Highlights:

-Detect and lessen the impact in COVID-19 high-risk states. -Evaluate mask usage effectiveness in these areas. -Scrutinize state-specific vaccination trends. -Data Foundation -The analysis rests on rich datasets from Kaggle and GitHub, ensuring current and comprehensive data for insightful outcomes.

Analytical Insights and Strategic Recommendations:

-Correlation between higher vaccination rates and reduced COVID-19 risk. -Necessity for focused action in densely populated regions. -Observation: Lower mask usage correlates with increased death rates. -Mask adherence significantly cuts down transmission risk. -States with a propensity for mask-wearing often exhibit higher vaccination rates.

Transformative Impact:

These findings are pivotal for shaping public health policies and reinforcing the need for vaccination and mask adherence to combat COVID-19 effectively.

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