View the full interactive dashboard of the COVID-19 Vaccination Analysis for Latin America on Tableau using the link below:
Interactive Dashboard
The project aims to analyze the efficiency of COVID-19 vaccination campaigns in select Latin American countries by examining their impact on COVID-19 deaths and new cases. Using SQL to extract relevant data and Tableau for visualization, we strive to answer key questions about the effectiveness of the vaccines.
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Identifying Key Questions and Goals
- The main question: "Are COVID-19 vaccines effective?"
- Breaking down this overarching question into smaller, more specific ones:
- Do COVID-19 vaccines reduce the number of COVID-related deaths?
- Do they reduce the number of new COVID-19 cases?
- Do they provide immunity against COVID-19?
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Dataset Selection and Filtering
- Focused on select Latin American countries: Mexico, Chile, Ecuador, Brazil, Peru, and Argentina.
- Data extracted from the World Health Organization (WHO) database, focusing on two tables:
- vaccination_data: Includes details like the country name, ISO code, and the date the first vaccine was administered.
- who_covid_global_data: Contains daily data on new and cumulative COVID-19 cases and deaths by country and region.
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Data Preparation
- Filter data to include only the selected Latin American countries.
- Create two new columns to track vaccination progress:
- days_since_vaccine: Displays a countdown to the first vaccine and a count-up thereafter.
- vaccination_started: Indicates whether vaccinations had started (Yes/No).
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Calculating Death Rates
- Analyzed death rates against population size to determine "Deaths per Million" for each country.
- This metric was derived by summing all deaths and dividing by the population, then multiplying by one million for clarity.
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Building Visualizations
- Constructed charts to visualize pre- and post-vaccination death rates to assess the impact of vaccines on mortality.
- Built a dashboard in Tableau to provide a comprehensive overview of the data, displaying trends in COVID-19 cases, deaths, and vaccination rates over time.
- SQL: For extracting data from the WHO database.
- Tableau: For visualizations, including maps, line charts, and dashboards to track trends over time.
- Data Analysis Techniques:
- Time series analysis for tracking daily changes in COVID-19 cases and vaccination progress.
- Calculations of mortality rates before and after vaccine introduction.
- Statistical Analysis: To compare pre- and post-vaccine mortality and case rates.
1. Analyzing COVID-19 Mortality Trends
- Created visualizations to track death rates before and after the start of vaccination campaigns.
- Results:
- A general downward trend in death rates over time, suggesting a potential reduction in COVID-related mortality with increasing vaccination rates.
- Some countries, like Brazil, showed resilience despite challenges with lockdown policies.
2. Impact of Vaccination on New COVID-19 Cases
- Visualized the rate of new cases before and after vaccination campaigns began.
- Findings:
- Initially, an increase in new COVID-19 cases was observed as vaccination campaigns commenced.
- Following a peak, there was a significant reduction in new cases, indicating the effectiveness of the vaccination campaigns in curbing the spread of the virus.
3. Country-Specific Patterns
- Brazil: Despite criticisms over relaxed lockdown measures, the country never exceeded a 7% mortality rate, demonstrating a significant effort to manage COVID-19's impact.
- Other Countries: Each country displayed unique patterns influenced by local policies and behaviors.
4. Limitations and Additional Observations
- While the dashboards show clear trends, the analysis was not fully conclusive about the direct impact of vaccines on mortality and case reduction.
- Other factors like government policies, public health campaigns, and behavioral changes likely played a role in the observed trends.
- Data Visualization Skills: Developed the ability to create clear, comprehensive dashboards in Tableau for visual storytelling.
- Statistical Insight: Enhanced my understanding of how to calculate mortality rates and analyze their relationship with vaccination campaigns.
- Critical Analysis: Improved my ability to critically assess the data, identify patterns, and draw insights from complex datasets.
- Storytelling with Data: Learned how to structure a compelling narrative around vaccination efficiency using both qualitative and quantitative data.
To answer our initial questions:
- Do COVID-19 vaccines reduce mortality? The data shows a general downward trend in death rates post-vaccination, but further analysis is needed for conclusive results.
- Do vaccines reduce new COVID-19 cases? There was a notable reduction in new cases after an initial spike during vaccination rollouts.
- Do vaccines provide immunity against COVID-19? The reduction in cases post-vaccination suggests increased resistance, but definitive conclusions require further exploration.
As Plato once said, "The only thing I know is that I know nothing." Our analysis has not reached definitive conclusions, but it provides a strong foundation for understanding the impacts of COVID-19 vaccination campaigns across different countries. By visualizing and interpreting these data trends, we hope to contribute meaningfully to the ongoing discourse on vaccine efficiency.
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Clone the repository
https://github.com/realdanizilla/COVID19-LATAM.git -
Run the Jupyter Notebook
- Execute the
.ipynbnotebook to see data preprocessing steps - Review SQL scripts used for data extraction and analysis from datasets on COVID-19 vaccination and cases.
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View Tableau Visualizations
Open the Tableau workbook (.twb) to see dashboards and visual insights on vaccination impact or access the publick link -
Run Your Analysis
Use the provided data and scripts to replicate or further explore trends in COVID-19 vaccination efficiency.