"Building age-structured network models from interaction data"
Many methods exists for generating networks with certain pre-specified properties. However, there are network properties that arise in certain applications for which we don't have standard methods. For example, age or sub-population structure in biological applications can be a very important determinant of node connectivity, but methods for constructing networks with a given structure are still being developed. In this talk, I will discuss a method we developed for generating an age-structured human interaction network using survey data that summarizes the number of interactions between individuals within and between different age groups. We do this using the well-known POLYMOD dataset to construct an age-structured infectious disease transmission network.