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SAS Basics Bootcamp

COVID-19 Data Analysis (Final Project) Instructions (35 points)

As the culminating assignment for this course, students will complete a data analysis using real-world COVID-19 data. This assignment has been structured to closely resemble the format of case study questions and assignments typically encountered in data analyst job interviews. This assignment provides an excellent opportunity for you to showcase your skills in analytical thinking, research, data analysis, and effective communication.

Case Study

As a data analyst for the Department of Public Health in the state of [DESIGNATED STATE], you are tasked with assessing the impact of COVID-19 to guide resource allocation effectively. Using state-level data from the Johns Hopkins University's Center for Systems Science and Engineering (CSSE), your analysis will focus on one specific COVID-19 outcome (e.g., tests, confirmed cases, hospitalizations, or deaths). The Governor is particularly interested in understanding how [DESIGNATED STATE] compares to neighboring states in managing the COVID-19 pandemic. Your role involves analyzing the data to uncover trends, highlight disparities, and identify areas needing intervention or support. This analysis is vital for informing decisions made by policymakers, healthcare providers, and the public to allocate resources effectively.

Project Goals

1. Provide Context and Data Overview

o Offer a clear description of the Johns Hopkins CSSE data as the source.

o Explain the purpose of the analysis and its significance for public health and policymaking.

2. Analyze Daily Trends

o Focus on daily trends for the selected COVID-19 outcome in [DESIGNATED STATE] and the regional average during the study period (June 1–7, 2020).

o Present data clearly using graphs or tables.

o Summarize findings, emphasizing key observations and disparities between your state and the regional average.

3. Recommend Strategies for Resource Allocation

o Based on findings, provide actionable recommendations to help the Governor optimize resources and policy decisions.

o Align recommendations with observed trends and disparities.

About the data:

The “study period” is from June 1 to June 7, 2020.

● COVID-19 data comes from the Center for Systems Science and Engineering at Johns Hopkins (https://github.com/CSSEGISandData).

○ Eight (8) SAS datasets with daily COVID-19 information for the study period (“cd0601”- “cd0607”) and for the day prior to the start of the study period (“cd0531”)

● Region data comes from U.S. Census (https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf)

○ One (1) SAS dataset indicating region for each U.S. state/territory, based on U.S. Census classification (“region”)

Information should be presented as short paragraphs (occasional bullet points are acceptable) and data visualizations to illustrate key information clearly and concisely to stakeholders potentially unfamiliar with epidemiologic and statistical language.

Grading Rubrics

Section 1: Data Source and Analysis Purpose (2 points)

· Clearly describe the data source (Johns Hopkins CSSE) and its relevance to the analysis.

· Explain how the analysis aligns with public health policy and resource allocation goals.

Section 2: Data Preparation (9 points total)

· Compute daily new cases (or the chosen outcome) for [DESIGNATED STATE] (3 points).

· Compute the regional average for the same metric (3 points).

· Integrate data by merging COVID-19 data with Census region data (3 points).

Section 3: Daily Trends Analysis (10 points total)

· Clearly analyze and describe trends for [DESIGNATED STATE] during June 1–7, 2020 (5 points).

· Highlight notable disparities between your state and the regional average (5 points).

Section 4: Recommendations for Resource Allocation (4 points)

· Provide actionable, evidence-based recommendations.

· Ensure recommendations address disparities and observed trends.

Additional Grading Criteria

· Clarity and Coherence (2 points): Write clearly, logically, and professionally.

· Data Visualization (3 points): Use effective graphs and tables to present data.

· SAS Code Quality (5 points): Write well-documented, readable SAS code with appropriate comments.

Formatting requirements:

- The document should be single-spaced with 0.5-inch margins and should not exceed two pages, including visualizations. Submit the document as a Word document (.doc or .docx)

- Please do not include questions. Do not write it in a Q&A format. Write the analysis report for the stakeholders and the public (Remember that you are a government employee, which means that most of your communications are public record: source 1, 2, 3).

- Submit SAS code in either a separate document or as an appendix page below the write-up.