Science Daily  January 5, 2023 Simulating large-scale epidemics requires substantial computational resources and in many cases is practically infeasible. One way to reduce the computational cost of simulating epidemics on the networks derived from modern datasets is sparsification, where a representative subset of edges is selected based on some measure of their importance. Researchers at Santa Fe Institute used the effective resistance, which takes both local and global connectivity into account. They tested their method in simulations on a U.S.-wide mobility network and fond that it preserved epidemic dynamics with high fidelity. According to the researchers combined with efficient epidemic […]