Purpose
The purpose of this project was to examine the trends and reasons behind differing COVID vaccination rates in the world.
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Findings and Suggestions - Part 1
Cleaning the data by separating non-relevant and null values led me to to focus on three main themes which were rates over time, income group and location. The element of location showed perhaps the most obvious insight, as the rates generally coincide with population levels in any particular region.
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Nevertheless, the most revealing insights were gained from Income Group and Development Metrics.
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Here we are able to see that those in middle income groups have the highest rates of vaccination, while those with high and low income have the smallest. On a socioeconomic and political level, this brings forth questions such as access to and necessity of vaccinations, since it may be that high net worth individuals have other sources of income and less need for vaccinations to keep employment, and also the perception of vaccination among social classes which could be investigated further.
Findings and Suggestions - Part 2
Besides that were the Development Metrics:
In order to gain further insight into the causation behind vaccination rates, I considered country development metrics in Europe to see if that was an influencing factor. I compared rates to life expectancy and human development index.
I found that while the people vaccinated varies greatly, it does not correspond to the metrics selected. As such levels of higher development do not equate to high levels of vaccination.
We can also see that it doesn't directly correlate to population, since Russia with the largest population in Europe, doesn't have the highest vaccination rate.
So here further investigation is required, such as access to vaccination centers, government enforcement of vaccinations, and public perception of vaccinations.
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