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2021-10-19Zeitschriftenartikel DOI: 10.18452/24540
Finding disease outbreak locations from human mobility data
dc.contributor.authorSchlosser, Frank
dc.contributor.authorBrockmann, Dirk
dc.date.accessioned2022-04-26T09:10:56Z
dc.date.available2022-04-26T09:10:56Z
dc.date.issued2021-10-19none
dc.identifier.urihttp://edoc.hu-berlin.de/18452/25211
dc.descriptionThis article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin.none
dc.description.abstractFinding the origin location of an infectious disease outbreak quickly is crucial in mitigating its further dissemination. Current methods to identify outbreak locations early on rely on interviewing affected individuals and correlating their movements, which is a manual, time-consuming, and error-prone process. Other methods such as contact tracing, genomic sequencing or theoretical models of epidemic spread offer help, but they are not applicable at the onset of an outbreak as they require highly processed information or established transmission chains. Digital data sources such as mobile phones offer new ways to find outbreak sources in an automated way. Here, we propose a novel method to determine outbreak origins from geolocated movement data of individuals affected by the outbreak. Our algorithm scans movement trajectories for shared locations and identifies the outbreak origin as the most dominant among them. We test the method using various empirical and synthetic datasets, and demonstrate that it is able to single out the true outbreak location with high accuracy, requiring only data of N=4 individuals. The method can be applied to scenarios with multiple outbreak locations, and is even able to estimate the number of outbreak sources if unknown, while being robust to noise. Our method is the first to offer a reliable, accurate out-of-the-box approach to identify outbreak locations in the initial phase of an outbreak. It can be easily and quickly applied in a crisis situation, improving on previous manual approaches. The method is not only applicable in the context of disease outbreaks, but can be used to find shared locations in movement data in other contexts as well.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectHuman mobilityeng
dc.subjectMobile phoneseng
dc.subjectEpidemic spreadingeng
dc.subjectOutbreak detectioneng
dc.subject.ddc540 Chemie und zugeordnete Wissenschaftennone
dc.titleFinding disease outbreak locations from human mobility datanone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/25211-0
dc.identifier.doihttp://dx.doi.org/10.18452/24540
dc.type.versionpublishedVersionnone
local.edoc.pages17none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
dc.description.versionPeer Reviewednone
dc.identifier.eissn2193-1127
dcterms.bibliographicCitation.doi10.1140/epjds/s13688-021-00306-6
dcterms.bibliographicCitation.journaltitleEPJ Data Sciencenone
dcterms.bibliographicCitation.volume10none
dcterms.bibliographicCitation.issue1none
dcterms.bibliographicCitation.articlenumber52none
dcterms.bibliographicCitation.originalpublishernameSpringerOpennone
dcterms.bibliographicCitation.originalpublisherplaceBerlin ; Heidelberg [u.a.]none
bua.departmentMathematisch-Naturwissenschaftliche Fakultätnone

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