Human-network regions as effective geographic units for disease mitigation

Clio Andris; Caglar Koylu; Mason A. Porter

doi:10.1140/epjds/s13688-023-00426-1

Back

Human-network regions as effective geographic units for disease mitigation

Journal article

Open access

Peer reviewed

Human-network regions as effective geographic units for disease mitigation

Clio Andris, Caglar Koylu and Mason A. Porter

EPJ data science, Vol.12(1), 60

12/18/2023

DOI: 10.1140/epjds/s13688-023-00426-1

Files and links (1)

url

https://doi.org/10.1140/epjds/s13688-023-00426-1View

Published (Version of record) Open Access

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.

Computer Science

Complexity

Computer Appl. in Social and Behavioral Sciences

Data-driven Science

Modeling and Theory Building

Regular Article

Details

Title: Subtitle: Human-network regions as effective geographic units for disease mitigation
Creators: Clio Andris - Georgia Institute of Technology
Caglar Koylu - University of Iowa
Mason A. Porter - Department of Mathematics, University of California, Los Angeles, Department of Sociology, University of California, Los Angeles, Santa Fe Institute
Resource Type: Journal article
Publication Details: EPJ data science, Vol.12(1), 60
DOI: 10.1140/epjds/s13688-023-00426-1
eISSN: 2193-1127
Publisher: Springer Berlin Heidelberg
Grant note: DMS-2027438; HNDS-R-2045271 / National Science Foundation (http://dx.doi.org/10.13039/100000001)
Language: English
Date published: 12/18/2023
Academic Unit: Center for Social Science Innovation; Geographical and Sustainability Sciences
Record Identifier: 9984532053802771

Metrics

15 Record Views

See more details