The goal of this project is to understand how enforcing various social distancing policies changes the contact network of people. To do this, we collect and analyze interaction networks obtained using the Bluetooth technology. In particular, our preliminary analysis focuses on a dataset of interactions of more than 700 students from Denmark over the course of 4 weeks. We use graph analysis techniques to understand the effects of the following social distancing policies:
This policy prohibits the concentration of people in groups more than N people. We aim to investigate how this policy affects the contact network by constructing contact networks after the application of this policy for varying N and by comparing it to the contact network without any policy enforced.
This policy aim to reduce contacts between people by limiting the time that specific people can move. One example of such policy is that people with odd street numbers can move during the beginning of the week, while people with even street numbers can move during the end of the week.
This policy allows people to move in specific times or dates in an attempt to reduce contacts between people, and therefore the spread of the virus.
Superspreaders are people that have a lot of contacts throughout their daily activities, therefore, they are more likely to spread the virus. In this work, we want to investigate how limiting superspreaders affects the overall contact network.