Inspiration
The inspiration came in regards to the level of uncertainty this pandemic has instilled in everyone. I figured to keep everyone educated as much as possible about COVID-19 and become more aware of the subtle and direct factors involved, it would be a great indicator of whether or not one will be infected with COVID or not.
What it does
What the app will do is take into account the following factors...
- Your location (your town of residence, your county, your state; the scope can be adjusted)
- Your overall health (any underlying conditions, any habits, etc.; mark all that apply)
- Who you've interacted with
- How long you've been outside
- Sanitization habits (gloves, masks, disinfecting surfaces, etc.)
Upon filling out the following information, you will be given a percentage that determines your likelihood of being infected by COVID-19. The mathematics involved is based on independent event probability.
How I built it
Actually, Tobi and Anish helped build the app (Anish will explain in the video demonstration). I just provided a theoretical mathematics-based framework from which the app is based on.
Challenges I ran into
One particular challenge was getting Python and HTML to interface with one another so that should data be input and output, it will display itself (sounds useful as a mobile app). But it was thanks to Anish that we decided to use Flask to get it to run since it runs on Python and operates for a web framework. Also, Tobi had provided a general HTML template with which to work from.
Another challenge is fleshing out the mathematics of the probability the user would be infected by COVID-19. After some scouring on the internet, I realized it would take too long to research and test out. Hopefully, someone can take the app's mathematics and continue where I started.
Accomplishments that I'm proud of
I'm proud of having encountered this team and being able to learn at least a little bit of what they have done so that I may implement it into my own skillset as well.
What's next for COVID-19 Tracker 2.0
What's next for COVID-19 Tracker 2.0 is that it would be run on a server, not locally (not like as shown in the video demo). Furthermore, the mathematics I proposed should be used (mostly probability) would be fleshed out so that way Anish and Tobi's respective Python and HTML work can be complete.
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