covid 19 in africa case study

Covid-19 in Africa: A Data Analytics Case Study (SQL,Tableau)

As the world grapples with the devastating impact of the Covid-19 pandemic, one region that has drawn significant attention is Africa.

As an African myself, I remember how much media coverage was being pushed in continents like Europe, North America, and Asia.

However, Africa was left far behind and almost forgotten.

The narrative surrounding the virus’s impact on this vast and diverse continent has been multifaceted, often shrouded in misconceptions and assumptions.

In this case study, we delve into the trajectory of Covid-19 deaths in Africa. Beyond statistics and headlines, we will uncover how, despite heavy misconceptions about the continent, Africa was actually thriving during the pandemic.

Join us in exploring the story behind the numbers, as we seek a deeper understanding of Africa’s experience with Covid-19.

Ask: Finding The Right Questions

The main goal of this case study was to clear the misconceptions about the African continent and the impact that the virus was believed to have on it.

The few news outlets that did talk about African all had one thing to say: Africa is doomed.

The common belief was that Africa would have some of the world’s highest mortality and infection rates during this period.

The wrote that the “virus outbreak poses great danger to African countries that do not have robust health system.”

The UN put out a brief discussing how “Early estimates were pessimistic regarding the pandemic’s impact on the continent.”

Reports upon reports of how Africa would not be able to handle the pandemic keep pouring in.

Until the numbers started to drop.

From those numbers, we can answer the following question: How much was the actual death toll in Africa compared to other continents?

Prepare: Prepping the Data

In order to get started, it was very important that I find viable, non-biased data. The most trustworthy place to get it from is from WHO (World Health Organization). Thankfully, the data is available for downloading via the WHO Covid 19 Dashboard.

Once the data was downloaded, I had to make a few decisions as to where and how I wanted to store the data.

I decided to use both BigQuery and MySQL for this case.

Both are very easy to use and can handle millions of rows of data. Which is almost exactly what we got with the data on Covid.

BigQuery SQL

Process: Cleaning the Data

The data from WHO was very clean and minimal data cleaning involved.

The only thing that I did was make sure that the data types for the columns were correct.

I also had to gather the data and group it per country so that I would be easily able to visualize the data afterward.

The majority of this work was done in BigQuery.

However, I did also export it into Excel and double check to make sure that everything looked okay. You always have to make sure that the numbers are correctly formatted so that the visualization tool will read them correctly.

Analyse: Organizing and Preparing Data for Analysis

In order to see how the virus had an effect on the countries in Africa, I had to make sure that the Data was separated by country.

I decided to keep the data in Excel and make sure that each country had it’s own row.

If any of the countries had multiple rows, I made sure that I combined the data and the put them into a single row.

This is easily achieved using the SUM function.

Excel African Countries

Share: Visualizing Your Data

My visualization tool of choice was Tableau.

After importing my data, the first chart I decided to create was a pie chart that would be separated by country. This would give the viewer a very clear visual of the countries that had the most amount of deaths due to Covid.

The next chart I created was a bar chart that would compare all of the countries to each other. I arranged it from lowest to highest death count. This was a great way to show a stark contrast between the countries.

The final chart that I added to the dashboard was a map chart. This gives countries with the higher death tolls a darker color on the map.

You can view the interactive dashboard below or you can CLICK HERE to view it on Tableau.

Act: Drawing Conclusions and Making Decisions

From the data and the visualizations there are some very clear conclusions that can be drawn:

  • South Africa has by far the highest Covid death toll on the African continent with over 100,000 deaths.
  • Tunisia had the second-highest death toll with a little under 30,000 deaths.
  • The country with the least deaths was Burundi with only 15
  • The entire African continent had a total of 257,761 deaths from Covid. According to WHO, the total death count in the World is 6,958,499. This means that Africa only accounted for 0.03% of the Covid deaths in the world.

These numbers show that despite what many people believed in the beginning of the pandemic, Africa managed to come out on top with not only the least amount of infections but also the least amount of deaths from Covid.

Now, there are still some unanswered questions:

Is this Data biased?

Most likely it is. It is impossible to know if 100% of the deaths have been registered. However, even with a margin of error of 2%-5%, Africa still has some of the lowest numbers. This is despite the fact that most African cities have a higher population density as well. Meaning, more people live closer together.

According to scientists, this is the main reason why Africa was expected to have such high infection and death rates. Clearly, this was not the case.

From these numbers, we should ask why South Africa had such a high death rate compared to the rest of the African continent. Tunisia was second on the list, yet, South Africa had almost 30% more cases.

These are some very important questions. However, this is also where the work of a Data Analyst stops. These findings can be brought to the right department for further analysis.

I hope that these findings were insightful for anyone who wanted to know more about the effects of Covid on the African continent.