There are plenty of websites that have compiled the various test sites around the world, that help people get tested if they need to. However, we have noticed that many of these websites, due to the manual nature of how they are updated, are not complete nor do they give up to date information.
What it does
Our website used crowd sourced data sourced from places such as newspaper articles to compile a thorough list of all COVID-19 testing sites set up and their details, included estimated waiting time and business hours. We reward volunteers(targeted mainly towards those whose jobs have been greatly disrupted due to the pandemic) with small cash rewards, funded by researchers and organizations who find value in the data of testing sites, and also media organizations looking to find the most accurate information they can. We have two main goals: 1) After compiling all of the data, we identify areas lacking testing sites, and thus inform those looking to establish new testing sites the areas in which they could create the most impact. 2) Allow people to get the most accurate information possible about where they can get tested.
How I built it
We used MapHub as a map on which we store the data. We used Materialize on the frontend, and Python/Flask on the backend, with Google Cloud Firestore as the database for the project.
Challenges I ran into
Lack of sufficient APIs for the maps mostly, particularly the lack of any at all for the first map service tried, or lack of one that cost money in particular. Additionally, choosing keywords/options to make it most likely to find relevant articles. Also, the ability to modify maps programmatically, which wasn't in any APIs.
What I learned
I learned a considerable amount about web development, as the backend was relatively simple. I also delved deeply into OpenStreetMap and the large community/web of different derivatives when trying to find a map service that actually worked when embedded for our purposes.
What's next for CrowdCOVID
Getting the word out about the project so that we can get participants, to actually kickstart the effort. Also, adding databases and other things in as data sources. Finally, using the data to determine which places could really use a testing center, to help those who want to establish them, and creating a view in which one can scroll through time to see centers pop up and/or close.
Try It out
flask, maphub, materialize, python, python-package-index