Retroactive Location Tracking for Contact Tracing

Why Retroactive Contact Tracing?

People who contract coronavirus are often unaware of the places they have been, making it difficult to "flatten the curve” (https://www.nytimes.com/article/flatten-curve-coronavirus.html).

As of 3/29, there have been over 660,000 cases of people contracting the coronavirus (COVID-19).

For those who have tested positive for the coronavirus, tracking those in close and recent contact limits the spread of the virus. Contact tracing is a practice recommended by the World Health Organization (https://www.who.int/features/qa/contact-tracing/en/). This program is designed to safely and securely guide people in retroactively assessing areas of exposure to COVID-19. Preemptive action against the spread of the virus is the best of combatting Coronavirus and this code sets a fundamental precedent.

What The Code Does

This Jupyter notebook walks through how to download important data that will help you track where you were the past 30 days based on your past logins, helping with the recommended contact tracing.

All data is not collected or stored in any way by the developers of this program. Moreover, since we are using Selenium, you can view all the interactions that occur within your browser.

All you need to do is to run every code block in the Jupyter Notebook to download the necessary data and visualize where you were the past 30 days!

Then you can download the data and share it with others if you want.

How I Built It

1) Mimicked steps that users would have to do to retrieve location data via Selenium 2) Collect data 3) Processed data for easy plotting and visualization later on 4) Calculate Location based on IP Address 3) Plot data

Challenges

I ran into a lot of issues with the frontend parts of the project, specifically with plotting the points accurately on the map.

What's next for Retroactive Location Tracking

This proof of concept can be applied to a variety of websites that users use such as Facebook, Netflix, etc. to get a better sense of where they were the days before contracting coronavirus.