https://doi.org/10.1140/epjds/s13688-023-00426-1
Regular Article
Human-network regions as effective geographic units for disease mitigation
1
School of City & Regional Planning, Georgia Institute of Technology, Atlanta, GA, USA
2
School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA
3
Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA, USA
4
Department of Mathematics, University of California, Los Angeles, Los Angeles, CA, USA
5
Department of Sociology, University of California, Los Angeles, Los Angeles, CA, USA
6
Santa Fe Institute, Santa Fe, NM, USA
Received:
3
August
2022
Accepted:
26
October
2023
Published online:
18
December
2023
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.
Key words: COVID-19 / Network modularity / Geographic regions / Social networks
© The Author(s) 2023
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