GEOFIL: A spatially-explicit agent-based modelling framework for predicting the long-term transmission dynamics of lymphatic filariasis in American Samoa

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dc.contributor.authorXu, Zhijing
dc.contributor.authorGraves, Patricia
dc.contributor.authorLau, Colleen
dc.contributor.authorClements, Archie
dc.contributor.authorGeard, Nicholas
dc.contributor.authorGlass, Kathryn
dc.date.accessioned2021-11-02T00:55:57Z
dc.date.available2021-11-02T00:55:57Z
dc.date.issued2018
dc.date.updated2020-11-23T11:42:27Z
dc.description.abstractIn this study, a spatially-explicit agent-based modelling framework GEOFIL was developed to predict lymphatic filariasis (LF) transmission dynamics in American Samoa. GEOFIL included individual-level information on age, gender, disease status, household location, household members, workplace/school location and colleagues/schoolmates at each time step during the simulation. In American Samoa, annual mass drug administration from 2000 to 2006 successfully reduced LF prevalence dramatically. However, GEOFIL predicted continual increase in microfilaraemia prevalence in the absence of further intervention.en_AU
dc.description.sponsorshipZX is funded by a NHMRC Centre of Research Excellence. CLL was supported by an Australian National Health and Medical Research Council (NHMRC) Fellowship (1109035).en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1755-4365en_AU
dc.identifier.urihttp://hdl.handle.net/1885/251391
dc.language.isoen_AUen_AU
dc.provenanceThis is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).en_AU
dc.publisherElsevieren_AU
dc.relationhttp://purl.org/au-research/grants/nhmrc/1109035en_AU
dc.rights© 2019 The Authors. Published by Elsevier B.V.en_AU
dc.rights.licenseCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_AU
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_AU
dc.sourceEpidemics: the journal of infectious disease dynamicsen_AU
dc.subjectLymphatic filariasisen_AU
dc.subjectAgent-based modellingen_AU
dc.subjectCommuting networksen_AU
dc.subjectSpatial heterogeneityen_AU
dc.subjectDisease dynamicsen_AU
dc.subjectVector-borne diseasesen_AU
dc.titleGEOFIL: A spatially-explicit agent-based modelling framework for predicting the long-term transmission dynamics of lymphatic filariasis in American Samoaen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.lastpage27en_AU
local.bibliographicCitation.startpage19en_AU
local.contributor.affiliationXu, Zhijing, College of Health and Medicine, ANUen_AU
local.contributor.affiliationGraves, Patricia, James Cook Universityen_AU
local.contributor.affiliationLau, Colleen, College of Health and Medicine, ANUen_AU
local.contributor.affiliationClements, Archie, Curtin Universityen_AU
local.contributor.affiliationGeard, Nicholas, University of Melbourneen_AU
local.contributor.affiliationGlass, Katie, College of Health and Medicine, ANUen_AU
local.contributor.authoruidXu, Zhijing, u1035031en_AU
local.contributor.authoruidLau, Colleen, u5651486en_AU
local.contributor.authoruidGlass, Katie, u4053649en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor111706 - Epidemiologyen_AU
local.identifier.absfor111715 - Pacific Peoples Healthen_AU
local.identifier.absfor110309 - Infectious Diseasesen_AU
local.identifier.absseo920503 - Health Related to Specific Ethnic Groupsen_AU
local.identifier.absseo920109 - Infectious Diseasesen_AU
local.identifier.absseo920404 - Disease Distribution and Transmission (incl. Surveillance and Response)en_AU
local.identifier.ariespublicationU1070655xPUB49en_AU
local.identifier.citationvolume27en_AU
local.identifier.doi10.1016/j.epidem.2018.12.003en_AU
local.identifier.scopusID2-s2.0-85059316550
local.publisher.urlhttps://www.elsevier.com/en-auen_AU
local.type.statusPublished Versionen_AU

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