Anonymous Local Contact Tracing has been developed to reduce the spread of the virus by our team as part of an initiative taken by our partners The Soteria Institute (soteriainstitute.org) and Enduring Net (enduringnet.org). LCT is designed to be deployed with minimal time and financial resources.
LCT is a grassroots initiative adopted and used inside narrow local confines (from small town communities to large organizations) based on the concept of “Visitors” and “Rooms”. Visitors log visits to Rooms (Public Places). Visitors warn Rooms when Visitor goes into quarantine. Rooms alert other contemporaneous Visitors of their exposure to the virus and trigger further COVID-19 tests. If positive, those visitors can in turn warn other Rooms of exposure. The process continues instantaneously across the locale minimizing the time to intervene and maximizing the time unexposed people can go about their lives and livelihoods.
Right now, LCT is an open source project found on GitHub at github.com/mcorning/lct-c and represents a robust protocol that any community can fork and use, after adjusting the application data such as city (community) name, the list of buildings and rooms comprised in a JSON file inside the codebase, the Redis Graph instance used as the database and the Google Maps API settings accordingly. These being said, we have implemented our own version of LCT to suit the needs that our Manchester University Campus has in order to achieve our goal of crushing the virus, and we are now at the stage of promoting the app – LCT is powerless without a strong community of users.
One of the main advantages of LCT is the complete anonymity aspect. With regards to the Data Policy, it stands out that users nicknames are not visible among each other being strictly stored locally. Their randomized ID’s are the only ones sent to the server alongside with their visits data (Visitors pass a Cypher query to Redis Graph to link a socket ID to a public space node). In addition, GPS is not being used, but instead a system of spaces that can be picked from the app’s interface – meaning there is no personally identifying data used. More technically, LCT uses Socket.io V3 and RedisGraph to handle a new Covid-19 alert protocol. The protocol does a search of the graph for any other Visitor nodes that shared space with Visitor sending the warning, search which repeats for each exposed Visitor until the graph is completely searched.
But enough technicality! If you want to see how LCT works in practice, our live version deployed through Heroku can be found at lct-uom.herokuapp.com.
Stay safe out there!