Inspiration

Last year was very challenging with the pandemic claiming more lives than any other disease in the modern era. The inspiration behind this project is to study the relationship between diet and how susceptible a person can be in acquiring the disease.

What it does

In the first part of the tutorial I performed data analysis and visualization part; I noticed that countries in which people consume more vegetables and less animal products and dairy, indeed have the lowest COVID-19 cases and deaths. In the second part of the tutorial I employed machine learning algorithms to predict the number of COVID-19 cases based on the diet and physiological state (obesity) of the inhabitants of a country. I used several linear regression models for this. To conclude, even if diet alone cannot be used to fight with the coronavirus, I think that we should pay more attention on the things that we eat:

How I built it

Built in Python, using the following libraries pandas 1.1.5, matplotlib 3.3.3 and seaborn, numpy 1.19.5, scikit-learn 0.24.1.

Challenges I ran into

Finding a way to retrieve and display user data was difficult. Finding the right algorithm to work with was also especially challenging. I also ran into problems with creating an efficient algorithm in a short span of time.

Accomplishments that I'm proud of

Being able to come up with a real-life analysis of how the diet of a country is effecting it covid-19 case rises, is itself a huge achievement, as it can provide some vital insight - organizing, cleaning and visualizing the data makes it easy to connect the dots and get a clear idea of the bigger picture. My analysis has made it really effective to look at the distribution of cases around the globe, in regions and specific countries and how it co-relates to the diet.

What I learned

I learned the different stages of project development and how to work under time pressure. Developing solutions for real world problems.

What's next for Covid-19 and Diet

The next steps would be fine tuning my model and including other parameters asides diet that might effect covid-19 spread and deaths.

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