Modelling the spread of H1N1 as a network
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317584/
Modelling and analysis of influenza A (H1N1) on networks by Zhen Jin, Juping Zhang, Li-Peng Song, Gui-Quan Sun, Jianli Kan, and Huaiping Zhu.
As I was searching for things to talk about in my blog post I happened upon this academic paper. The authors found a way to model the spread of H1N1 in China as a network. Most of the paper talks about the parameters used in making the network. Justification, notation, mathematical formulas, etc take up a large portion of the paper. What I found interesting was how they chose to represent key information in their network. So the flow of transmission is represented as a directed graph, with one node pointing to another node. So this would be one individual’s potential to infect another. The nodes themselves are marked with different letters, S indicating susceptible, E indicating Exposed, I indicating Infected, A indicating Asymptomatic and R indicating Recovered.
They concluded that within a closed community vaccinations have a huge effect on the number of recovered individuals. Just vaccinating some key individuals that have a large number of friends in the community (outgoing edges) effects the spread of the disease. So if someone who has been infected gets the vaccine (who has a lot of outgoing edges), the potential for further spread decreases substantially. I was wondering how they were able to get the number of people in China who had the disease and spread it to other people. They used information from hospitals in different towns in China. They probably could only get very little information (privacy concerns), so the rest they had to figure out on their own.