A Location-Centric Network Approach to Analyzing Epidemic Dynamics

Datos Bibliográficos

ID3775652
AutoresShiran Zhong (0000-0001-7616-0797, University at Buffalo, State University of New York), Ling Bian (University at Buffalo, State University of New York)
Año2016
Volumen106
Número2
Páginas1-9
Fecha de publicación2016-01-12
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaAnnals of the American Association of Geographers (JOURNAL)
Identificadores de la revistaISSN: 2469-4452 • E-ISSN: 2469-4460
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/00045608.2015.1113113
PMID27493998
OpenAlexW2290079757
IdiomaEN
Citas recibidas9
Referencias citadas20

Recent health threats, such as the SARS, H1N1, and Ebola pandemics, have stimulated great interest in network models to study the transmission of communicable diseases through human interaction and mobility. Most current network models have focused on an individual-centric perspective where individuals are represented as nodes, and the interactions among them as edges. Few of these models are concerned with the discovery of the spatial patterns and dynamics of epidemics. We propose a location-centric, transmission network approach, in which nodes denote locations and edges denote possible disease transmissions between locations. We then identify the dynamics of transmission flows, the dynamics of critical locations, and the spatial-temporal extent of transmission pathways to assess the impact of these spatial dynamics on the evolution of an epidemic. Results show that transmission flows shift from elementary schools to middle schools and finally universities and professional schools at different phases of an epidemic. Critical locations, identified using network analysis, are responsible for the upsurge in transmission flows during the peaks of the epidemic. The length of transmission pathways shows a power law distribution and their spatial extent is rather small. Insights gained from this study will help devise spatially sensitive strategies to control communicable diseases

Coronavirus disease 2019 (COVID-19 · Disease · Economic geography · Geography · Pandemic · Telecommunications · Transmission (telecommunications · Complex Network Analysis Techniques · Computer Science · COVID-19 epidemiological studies · Human Mobility and Location-Based Analysis · Medicine