Nonprogressive diffusion describes the spread of behavior on a social network, where agents are allowed to reverse their decisions as time evolves. It has a wide variety of applications in service adoption, opinion formation, epidemiology, etc. Two common approaches to analyzing network diffusion are: microfounded methods, which capture the detailed network topology and the stochastic evolution of agent states but often lead to computational challenges, and macroscopic methods, which simplify the diffusion process.