About: A large-scale location-based social network to understanding the impact of human geo-social interaction patterns on vaccination strategies in an urbanized area

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About: A large-scale location-based social network to understanding the impact of human geo-social interaction patterns on vaccination strategies in an urbanized area Goto Sponge NotDistinct Permalink

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	A large-scale location-based social network to understanding the impact of human geo-social interaction patterns on vaccination strategies in an urbanized area
Creator	Cassels, Susan Gao, Peng Luo, Wei
source	Elsevier; Medline; PMC
abstract	Abstract Cities play an important role in fostering and amplifying the transmission of airborne diseases (e.g., influenza) because of dense human contacts. Before an outbreak of airborne diseases within a city, how to determine an appropriate containment area for effective vaccination strategies is unknown. This research treats airborne disease spreads as geo-social interaction patterns, because viruses transmit among different groups of people over geographical locations through human interactions and population movement. Previous research argued that an appropriate scale identified through human geo-social interaction patterns can provide great potential for effective vaccination. However, little work has been done to examine the effectiveness of such vaccination at large scales (e.g., city) that are characterized by spatially heterogeneous population distribution and movement. This article therefore aims to understand the impact of geo-social interaction patterns on effective vaccination in the urbanized area of Portland, Oregon. To achieve this goal, we simulate influenza transmission on a large-scale location-based social network to 1) identify human geo-social interaction patterns for designing effective vaccination strategies, and 2) and evaluate the efficacy of different vaccination strategies according to the identified geo-social patterns. The simulation results illustrate the effectiveness of vaccination strategies based on geo-social interaction patterns in containing the epidemic outbreak at the source. This research can provide evidence to inform public health approaches to determine effective scales in the design of disease control strategies.
has issue date	2018-11-30(xsd:dateTime)
bibo:doi	10.1016/j.compenvurbsys.2018.06.008
bibo:pmid	30983651
has license	els-covid
sha1sum (hex)	a78ff7b94d33ade83cbd46f338837ab3c1f9906a
schema:url	https://doi.org/10.1016/j.compenvurbsys.2018.06.008
resource representing a document's title	A large-scale location-based social network to understanding the impact of human geo-social interaction patterns on vaccination strategies in an urbanized area
has PubMed Central identifier	PMC6457472
has PubMed identifier	30983651
schema:publication	Computers, Environment and Urban Systems
resource representing a document's body	covid:a78ff7b94d33ade83cbd46f338837ab3c1f9906a#body_text
is schema:about of	named entity 'GEO' named entity 'R T' named entity 'LARGE' named entity 'VACCINATION' named entity 'SCALE' »more»

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