  In this paper, I study epidemic diffusion in a generalized spatial SEIRD
model, where individuals are initially connected in a social or geographical
network. As the virus spreads in the network, the structure of interactions
between people may endogenously change over time, due to quarantining measures
and/or spatial-distancing policies. I explore via simulations the dynamic
properties of the co-evolutionary process dynamically linking disease diffusion
and network properties. Results suggest that, in order to predict how epidemic
phenomena evolve in networked populations, it is not enough to focus on the
properties of initial interaction structures. Indeed, the co-evolution of
network structures and compartment shares strongly shape the process of
epidemic diffusion, especially in terms of its speed. Furthermore, I show that
the timing and features of spatial-distancing policies may dramatically
influence their effectiveness.
