> What I just described just involves composition of deterministic networks. But to what is to extent is stochasticity fundamental to the evolution of a pandemic. E.g. a super-spreader went to a funeral and started a huge wave of disease in one region. To that extent, perhaps it makes sense to retain a stochastic Petri net framework. This could also on a regional basis, and the local networks composed into a global network. Or one could imagine hybrid models that use deterministic nets for the well mixed populations, but have stochastic regions as well. Certain parts of the network may be more critical and sensitive, and may deserve to be modeled at a more fine-grained, stochastic level. I’m thinking of individuals who have many connections. Whether or not a key politician practices social distancing could have a big ripple effect, due to the large number of social connections – and that a stochastic, individual consideration.