I had the great experience of being a guest lecturer for Dr. Melissa Clark‘s Introduction to Public Health course last Friday. The course has about 200 Brown University undergraduate students enrolled, and was the largest group I have ever spoken to.
My goals were to introduce social network concepts and to show how they relate to 1.) an individual’s risk of contracting a disease and 2.) how diseases are spread on a population level. I also wanted to encourage the class to start thinking of systems as networks and to spark interest in networks.
Dr. Clark gave me several tips for how to work with such a large and diverse group of students. In order to engage such a large group I first asked them to think of five of their friends at Brown, and to write down their initials. Next I gave them 2 hypothetical situations and asked them to decide which friend best fit that scenario. Here are the two situations I posed to the class:
- There is a new contagious virus, which is spread like the flu. The virus has yet to come to Brown University. If this person was the only person at Brown to have the virus, there probably would not be a large outbreak.
- Brown Health Services is starting a new health intervention, and plans to recruit peer educators to spread the message across campus. Which of your friends would be most successful at spreading the message?
Next I asked the class what made them think about the friend they chose in the first hypothetical situation. One student said that their friend is a Computer Science major and doesn’t leave their room. Another said that their friend is obsessive about washing their hands. We also discussed what qualities led them to think about the friend in the second situation. The classes responses related mainly to individual level factors, which are necessary to understand infectious disease, but individual factors may not tell the full story.
I used this network as a motivating example to define different network concepts and terminology including, nodes, edges, paths, geodesic distance, network diameter, degree distributions, centrality, and homophily.
In the end of my lecture, I asked the class to think about the same hypothetical situations, now applied to this fictitious close contact network. We talked about how one member of the network had low centrality and low degree, and therefore they might not spread a disease to the rest of the network.
I was really pleased with how the lecture went. The students were very willing to participate and had great intuition and reasoning about networks. There seemed to be a lot of interest in networks. In fact, one student approached me after lecture to ask if there was an introduction to networks class at Brown!
Overall, this was a wonderful experience!