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Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning

Pfeiffer, Dirk U.; Clements, Archie

Description

Spatial epidemiological tools are increasingly being applied to emerging viral zoonoses (EVZ), partly because of improving analytical methods and technologies for data capture and management, and partly because the demand is growing for more objective ways of allocating limited resources in the face of the emerging threat posed by these diseases. This review documents applications of geographical information systems (GIS), remote sensing (RS) and spatially-explicit statistical and mathematical...[Show more]

dc.contributor.authorPfeiffer, Dirk U.
dc.contributor.authorClements, Archie
dc.date.accessioned2015-12-13T22:29:12Z
dc.identifier.issn1090-0233
dc.identifier.urihttp://hdl.handle.net/1885/74578
dc.description.abstractSpatial epidemiological tools are increasingly being applied to emerging viral zoonoses (EVZ), partly because of improving analytical methods and technologies for data capture and management, and partly because the demand is growing for more objective ways of allocating limited resources in the face of the emerging threat posed by these diseases. This review documents applications of geographical information systems (GIS), remote sensing (RS) and spatially-explicit statistical and mathematical models to epidemiological studies of EVZ. Landscape epidemiology uses statistical associations between environmental variables and diseases to study and predict their spatial distributions. Phylogeography augments epidemiological knowledge by studying the evolution of viral genetics through space and time. Cluster detection and early warning systems assist surveillance and can permit timely interventions. Advanced statistical models can accommodate spatial dependence present in epidemiological datasets and can permit assessment of uncertainties in disease data and predictions. Mathematical models are particularly useful for testing and comparing alternative control strategies, whereas spatial decision-support systems integrate a variety of spatial epidemiological tools to facilitate widespread dissemination and interpretation of disease data. Improved spatial data collection systems and greater practical application of spatial epidemiological tools should be applied in real-world scenarios.
dc.publisherW. B. Saunders Co., Ltd.
dc.sourceVeterinary Journal
dc.subjectKeywords: avian influenza; cluster analysis; data collection method; decision support system; epidemiological data; geographic distribution; geographic information system; human; infection control; mathematical model; nonhuman; phylogeography; rabies; remote sensin Geographical information systems; Highly pathogenic avian influenza; Rabies; Rift Valley fever; Risk analysis; Spatial analysis; West Nile virus
dc.titleEmerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume182
dc.date.issued2009
local.identifier.absfor111706 - Epidemiology
local.identifier.ariespublicationU3488905xPUB4193
local.type.statusPublished Version
local.contributor.affiliationClements, Archie, College of Medicine, Biology and Environment, ANU
local.contributor.affiliationPfeiffer, Dirk U., University of London
local.description.embargo2037-12-31
local.bibliographicCitation.issue1
local.bibliographicCitation.startpage21
local.bibliographicCitation.lastpage30
local.identifier.doi10.1016/j.tvjl.2008.05.010
dc.date.updated2016-02-24T10:06:15Z
local.identifier.scopusID2-s2.0-67349123354
CollectionsANU Research Publications

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