Inspiration
Although social distancing is one of the most effective ways to limit the spread of the coronavirus, it is not always possible. The next best strategy to utilize would be careful contact tracing, as well as being generally cautious about avoiding coronavirus hotspots. Although information about numerical case counts is readily available, one thing that we felt was lacking was information about the geospatial distribution of these cases. For this reason, we wanted to create a community-sourced service for people to report cases of the virus, or report spaces where they may have spread the disease, as well as just view where cases are concentrated in general.
What it does
When you enter the site, you are presented with a set of questions on the left and a map on the right. The map automatically presents you with the current coronavirus situation in the area, however, it cannot be added to by the user unless the answers to the questions on the left suggest that you may have been spreading the virus. Adding markers on the map adds them to our server’s database, making them accessible for future users of the site to view. We added cluster markers to make large concentrations of cases more visible, as well as provide a numerical count when there are multiple cases in close proximity. The markers automatically disappear after a week of being on the map to represent the recovery of COVID patients and only keep the relevant data on the map.
How we built it
We started by learning the basics of the HTML language and building a primitive home screen with that knowledge. We began accessing different libraries, which allowed us to embed a Google Maps API widget (using JavaScript) within the home screen. After creating this widget we implemented functions which we could create and store markers within the website using cookies. We realized that this program would be more efficient if we hosted it, allowing us to store information from multiple users within a single Firebase Cloud database without the use of cookies, which limits the scope of the program to a single computer.
Challenges we ran into
All of them. We started this project having no experience with HTML, javascript, google maps API or hack-a-thons in general, but we learned to use each of them successfully and manage the stresses of TAMUHack with the help of mentors and documentation. Our biggest challenges were saving markers locally, toggle the ability to use markers, and moving our project into the cloud. We originally wanted to use the python extension Flask to host a server but found that to not be feasible shortly after diving into the package. We conquered all of these issues, however, and learned tons from this project.
Accomplishments that we're proud of
This was our first hackathon so we weren’t really sure what to expect in terms of a finished product. We are all proud of the fact that we started this project knowing nearly nothing and made exactly what we wanted to by the end of it. We learned how to implement a google map and make great use of the google map API by placing markers, saving marker locations, and implementing cluster markers. After multiple attempts at hosting a server, we successfully implemented firebase to host a cloud database and store the data from the markers. We also learned how to implement an aesthetically pleasing front-end using HTML.
What we learned
Though each of us came in with adequate python knowledge and limited experience in other languages, we all found ways to learn about languages we’d never before used. We all gained experience with coding in HTML and javascript languages as well as implementing Google APIs within those programs. Additionally, we gained knowledge about the process by which backend web development is used.
What's next for COVID Map Tracker
Although our current version of the project is specialized for the College Station/Bryan Area, the nature of the Google Maps API means that we can easily adapt our service for any other area just by adjusting the coordinates and the zoom level. It would be amazing to adapt this idea for other college campuses or high population density areas. Since this project does rely very much on community involvement, it would really benefit from being supported or promoted by institutions such as universities, companies with many employees, or even directly from testing sites.
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