  This paper introduces a new approach to describe the spread of research
topics across disciplines using epidemic models. The approach is based on
applying individual-based models from mathematical epidemiology to the
diffusion of a research topic over a contact network that represents knowledge
flows over the map of science -as obtained from citations between ISI Subject
Categories. Using research publications on the protein class kinesin as a case
study, we report a better fit between model and empirical data when using the
citation-based contact network. Incubation periods on the order of 4 to 15.5
years support the view that, whilst research topics may grow very quickly, they
face difficulties to overcome disciplinary boundaries.
