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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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Xu, Zhijing; Graves, Patricia; Lau, Colleen; Clements, Archie; Geard, Nicholas; Glass, Kathryn

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In 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....[Show more]

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.identifier.issn1755-4365
dc.identifier.urihttp://hdl.handle.net/1885/251391
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.
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).
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherElsevier
dc.rights© 2019 The Authors. Published by Elsevier B.V.
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceEpidemics: the journal of infectious disease dynamics
dc.subjectLymphatic filariasis
dc.subjectAgent-based modelling
dc.subjectCommuting networks
dc.subjectSpatial heterogeneity
dc.subjectDisease dynamics
dc.subjectVector-borne diseases
dc.titleGEOFIL: A spatially-explicit agent-based modelling framework for predicting the long-term transmission dynamics of lymphatic filariasis in American Samoa
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume27
dc.date.issued2018
local.identifier.absfor111706 - Epidemiology
local.identifier.absfor111715 - Pacific Peoples Health
local.identifier.absfor110309 - Infectious Diseases
local.identifier.ariespublicationU1070655xPUB49
local.publisher.urlhttps://www.elsevier.com/en-au
local.type.statusPublished Version
local.contributor.affiliationXu, Zhijing, College of Health and Medicine, ANU
local.contributor.affiliationGraves, Patricia, James Cook University
local.contributor.affiliationLau, Colleen, College of Health and Medicine, ANU
local.contributor.affiliationClements, Archie, Curtin University
local.contributor.affiliationGeard, Nicholas, University of Melbourne
local.contributor.affiliationGlass, Katie, College of Health and Medicine, ANU
dc.relationhttp://purl.org/au-research/grants/nhmrc/1109035
local.bibliographicCitation.startpage19
local.bibliographicCitation.lastpage27
local.identifier.doi10.1016/j.epidem.2018.12.003
local.identifier.absseo920503 - Health Related to Specific Ethnic Groups
local.identifier.absseo920109 - Infectious Diseases
local.identifier.absseo920404 - Disease Distribution and Transmission (incl. Surveillance and Response)
dc.date.updated2020-11-23T11:42:27Z
local.identifier.scopusID2-s2.0-85059316550
dcterms.accessRightsOpen Access
dc.provenanceThis is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
dc.rights.licenseCreative Commons Attribution-NonCommercial-NoDerivs License
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