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Abstract Susceptibility to infectious diseases such as COVID-19 depends on how those diseases spread. Many studies have examined the decrease in COVID-19 spread due to reduction in travel. However, less is known about how much functional geographic regions, which capture natural movements and social interactions, limit the spread of COVID-19. To determine boundaries between functional regions, we apply community-detection algorithms to large networks of mobility and social-media connections to construct geographic regions that reflect natural human movement and relationships at the county level in the coterminous United States. We measure COVID-19 case counts, case rates, and case-rate variations across adjacent counties and examine how often COVID-19 crosses the boundaries of these functional regions. We find that regions that we construct using GPS-trace networks and especially commute networks have the lowest COVID-19 case rates along the boundaries, so these regions may reflect natural partitions in COVID-19 transmission. Conversely, regions that we construct from geolocated Facebook friendships and Twitter connections yield less effective partitions. Our analysis reveals that regions that are derived from movement flows are more appropriate geographic units than states for making policy decisions about opening areas for activity, assessing vulnerability of populations, and allocating resources. Our insights are also relevant for policy decisions and public messaging in future emergency situations.
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Collaborative diffusion: The dynamics of policy output in COVID ‐19 interstate compacts
Abstract Interstate compacts are formal structures through which multiple states work together towards a common goal or shared agenda. Previous research on compacts focuses almost exclusively on the decision to join the compact, leaving questions on post‐formation diffusion patterns unexplored. We use a unique case of three interstate compacts that form simultaneously around the same issue—the COVID‐19 pandemic—to test how policy diffuses within compacts. We employ a novel diffusion methodology, network event history analysis (NEHA), to determine the role of compact membership in policy activity. We find that compact member states are no more active in adopting policy than non‐members, but that non‐member states use compacts to free ride when making their own adoption choices. We find that compacts serve to establish members as leaders, as non‐members' policy adoptions are strongly driven by the adoptions of compact members. We also find COVID‐19 policy diffusion to be strongly driven by state ideology.
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- PAR ID:
- 10581440
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Policy Studies Journal
- ISSN:
- 0190-292X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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