Cyber-Physical-Human Systems (CPHS) combine sensing, communication and control to obtain desirable outcomes in physical environments for human beings, such as buildings or vehicles. A particularly important application area is emergency management. While recent work on the design and optimisation of emergency management schemes has relied essentially on discrete event simulation, which is challenged by the substantial amount of programming or reprogramming of the simulation tools and by the scalability and the computing time needed to obtain useful performance estimates, this paper proposes an approach that offers fast estimates based on graph models and probability models. We show that graph models can offer insight into the critical areas in an emergency evacuation and that they can suggest locations where sensor systems are particularly important and may require hardening. On the other hand, we also show that analytical models based on queueing theory can provide useful estimates of evacuation times and for routing optimisation. The results are illustrated with regard to the evacuation of a real-life building.