Getting enough real-life data on disease spreading is a difficult task. The lack of information regarding the health status of an individual as well as its GPS trace makes it quite impossible to get enough data to model an optimal test setup to limit the virus spreading. We, therefore, modeled the spatial spreading of the virus with an agent-based SIR model to generate the required data to run data analysis algorithms afterward.
What it does
Model the spacial disease spreading based on the infection parameters (infection rate, recovery rate) and generate optimal test settings to limit the disease spreading.
How we built it
To run the data analysis, we currently use python and evaluate different algorithms to find the right corona test distribution mechanism. The SIR model is currently implemented in Matlab, however, we'll port it towards python, to eventually test our system in a live environment.
Challenges we ran into
Create a realistic SIR model, code optimization, prove that our system works in a real-life setting.
What's next for Corona Contact Tracing
Implement our optimal testing algorithm in a mobile application.