About: Epidemic Wave Dynamics Attributable to Urban Community Structure: A Theoretical Characterization of Disease Transmission in a Large Network

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Epidemic Wave Dynamics Attributable to Urban Community Structure: A Theoretical Characterization of Disease Transmission in a Large Network
Creator	Brownstein, John Lenczner, Michael Eysenbach, Gunther Eggo, Rosalind Lau, Eric Meyers, Lauren Hladish, Thomas Hoen, Anne Hyder, Ayaz
source	PMC
abstract	BACKGROUND: Multiple waves of transmission during infectious disease epidemics represent a major public health challenge, but the ecological and behavioral drivers of epidemic resurgence are poorly understood. In theory, community structure—aggregation into highly intraconnected and loosely interconnected social groups—within human populations may lead to punctuated outbreaks as diseases progress from one community to the next. However, this explanation has been largely overlooked in favor of temporal shifts in environmental conditions and human behavior and because of the difficulties associated with estimating large-scale contact patterns. OBJECTIVE: The aim was to characterize naturally arising patterns of human contact that are capable of producing simulated epidemics with multiple wave structures. METHODS: We used an extensive dataset of proximal physical contacts between users of a public Wi-Fi Internet system to evaluate the epidemiological implications of an empirical urban contact network. We characterized the modularity (community structure) of the network and then estimated epidemic dynamics under a percolation-based model of infectious disease spread on the network. We classified simulated epidemics as multiwave using a novel metric and we identified network structures that were critical to the network’s ability to produce multiwave epidemics. RESULTS: We identified robust community structure in a large, empirical urban contact network from which multiwave epidemics may emerge naturally. This pattern was fueled by a special kind of insularity in which locally popular individuals were not the ones forging contacts with more distant social groups. CONCLUSIONS: Our results suggest that ordinary contact patterns can produce multiwave epidemics at the scale of a single urban area without the temporal shifts that are usually assumed to be responsible. Understanding the role of community structure in epidemic dynamics allows officials to anticipate epidemic resurgence without having to forecast future changes in hosts, pathogens, or the environment.
has issue date	2015-07-08(xsd:dateTime)
bibo:doi	10.2196/jmir.3720
bibo:pmid	26156032
has license	cc-by
schema:url	https://doi.org/10.2196/jmir.3720
resource representing a document's title	Epidemic Wave Dynamics Attributable to Urban Community Structure: A Theoretical Characterization of Disease Transmission in a Large Network
has PubMed Central identifier	PMC4526984
has PubMed identifier	26156032
schema:publication	J Med Internet Res
resource representing a document's body	covid:PMC4526984#body_text
is schema:about of	named entity 'Disease' named entity 'CHARACTERIZATION' named entity 'NETWORK' named entity 'THEORETICAL' named entity 'ATTRIBUTABLE' named entity 'DYNAMICS' named entity 'WAVE' named entity 'URBAN COMMUNITY' named entity 'LARGE' named entity 'COMMUNITY STRUCTURE' named entity 'OF DISEASE TRANSMISSION' named entity 'EPIDEMIC' named entity 'Structure' named entity 'Network' named entity 'Disease Transmission' named entity 'social distancing' named entity 'physical contact' named entity '1918 influenza pandemic' named entity 'pathogen' named entity 'randomly selected' named entity 'probability' named entity 'disease transmission' named entity 'ÎSF' named entity 'pandemics' named entity 'environmental conditions' named entity 'Montreal' named entity 'wireless device' named entity 'test the hypothesis' named entity 'reproduction number' named entity 'algorithm' named entity 'pandemic influenza' named entity 'Internet' named entity 'probability' named entity 'influenza' named entity 'epidemic' named entity 'ÎSF' named entity 'Downtown Montreal' named entity 'epidemic' named entity 'cell phones' named entity 'pandemics' named entity 'assortativity' named entity 'probability' named entity 'SD 7' named entity 'epidemic' named entity 'disease transmission' named entity 'Canada' named entity 'influenza' named entity 'population structure' named entity 'influenza' named entity 'theoretical framework' named entity 'expected number' named entity 'Quebec' named entity 'pathogen' named entity 'infectious diseases' named entity 'epidemic' named entity 'heterogeneity' named entity 'temporal resolution' named entity 'epidemiological' named entity 'attack rate' named entity 'Internet hotspots' named entity 'stochastic' named entity 'North American' named entity 'public health' named entity 'ÎSF' named entity 'epidemiological' named entity 'pandemics' named entity 'Sensitivity analysis' named entity 'epidemiological' named entity 'user ID' named entity 'superspreaders' named entity 'heuristic' named entity 'pathogen' named entity 'Montreal' named entity 'contagious diseases'

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