We perform 100 simulations for each of five generic network ensembles each with 25 populations and a connectedness of approximately 0.15. Specifically, we examine Erdős-Rényi (links randomly assigned between populations), stochastic block (a metapopulation consisting of two groups of populations which have high migration within the group, but low migration to populations in the other group), tree-like (where there are many chains of populations and no potential for cycles), Barabasi-Albert (a scale-free network in which there tends to be a few populations with very many links, and many populations with few links), and Watts-Strogatz (a small-world network structure which is produced by partially re-wiring a spatially connected grid of populations) network structures. To generate these networks, we utilize functions from the tidygraph R package \cite{pedersen2019}, except in the case of the tree and Watts-Strogatz configuration for which we use custom algorithms. Note that we use a parameter of attachment of 4 for the Barabasi-Albert random graphs. This allows for comparable connectences to the other random graphs as well as distinguishing these randomizations from trees (as would result from a default parameter of attachment of 1). In all cases, each migration strength is set to a constant δ = 0.01, only the pattern of connections varies. Each population is assigned a random β value corresponding to a \(\tilde{R_0}\) between [1, 6]. These results are qualitatively similar if instead every population is assigned the same value of β.