Not only do we use data influenced by human actions, like population, isolation rate, and the number of available ICU beds, but also, our application is capable of predicting the severity of Covid-19 in countries. Therefore, our mission is to identify at-risk regions and predict the condition at different places.
As IT students we were very interested in analysing and forecasting data related to COVID-19. We believe information about diseases should be shared easily to everyone and, with this mindset, we developed our project about it. We did not participate with winning in mind. Instead, we were all in this for the experience and the challenge.
In order to develop this project, we separated our team in three duos. The first was responsible for the front-end development, the second developed the back-end and a third with focused on acquiring, using and interpreting data. By the end, we broke the pairs to DESPERATELY finalize the development.
We used data from reliable sources, including some recommended by NASA (such as John Hopkins’ University). However, we didn’t use space agency data directly.
We used HTML, CSS and JavaScript for front-end. As for back-end, we used a Python webservice with Flask, as well as libraries associated with statistics, such as pandas, matplotlib and seaborn. The webservice was hosted in Amazon (AWS), and the website was hosted in Firebase. Visual Studio Code and Jupyter were very useful when coding.
We had a hard time finding data related to our objectives(geographic data like demographic density, Covid-19 cases and deaths) and APIs to manage this archives. Although, after a lot of effort we were capable of acquiring data and using it to predict possible problems around the world.
https://youtu.be/ZU4UpMRkkXE