  Modelling diffusion processes on dynamic contact networks is an important
research area for epidemiology, marketing, cybersecurity, and ecology. However,
current diffusion models cannot capture transmissions occurring for indirect
interactions. For example, an airborne infected individual releases infectious
particles at locations that can suspend in the air and infect susceptible
individuals arriving even after the infected individual left. Thus, current
diffusion models miss transmissions during indirect interactions. In this
thesis, a novel diffusion model called the same place different time
transmission based diffusion (SPDT) is introduced to take into account the
transmissions through indirect interactions. The behaviour of SPDT diffusion is
analysed on real dynamic contact networks and a significant amplification in
diffusion dynamics is observed. The SPDT model also introduces some novel
behaviours different from current diffusion models. In this work, a new SPDT
graph model is also developed to generate synthetic traces to explore SPDT
diffusion in several scenarios. The analysis shows that the emergence of new
diffusion becomes common thanks to the inclusion of indirect transmissions
within the SPDT model. This work finally investigates how diffusion can be
controlled and develops new methods to hinder diffusion.
