AIMS Cameroon student network epidemic model
To understand how influenza might spread through a social network, let’s return to our AIMS Cameroon student network. Recall that we used survey data about interactions to create connections between students. This allowed us to connect students who interacted regularly. However, consider the case where survey data about interactions did not exist. How might we infer possible connections between students?
We have information such as country of origin, field of study, and age of the students. Students from the same countries likely share a common culture—perhaps the same local language, the same favorite comfort foods, or the same favorite musicians.
Similarly, students in the same field of study are likely to spend time together in and out of class, given their shared courseload and career interests. Study groups, group projects, and professional events in their fields likely bring students together on a regular basis...
