Figure 1

Schematic illustration of our approach to obtain human-network regions through network partitioning. Each network-partitioning method has an input of (A) a network of movement flows or social-media connections between U.S. counties. We apply a community-detection algorithm to determine (B) a set of distinct regions. We use (C) a network \(G_{a}\) of county adjacencies and (D) distinguish edges between regions (\(E_{b}\), in yellow) from edges within regions (\(E_{w}\), in black). (E) We then weight all edges by COVID-19 case counts, mutual case rates, and case-rate differences. (F) We measure these values both between regions (in yellow) and within regions