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

Clements, Archie C A and Pfeiffer, D. U (2009) Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning. The Veterinary Journal, 182 1: 21-30. doi:10.1016/j.tvjl.2008.05.010


Author Clements, Archie C A
Pfeiffer, D. U
Title Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
Journal name The Veterinary Journal   Check publisher's open access policy
ISSN 1090-0233
1532-2971
Publication date 2009-10-01
Year available 2008
Sub-type Critical review of research, literature review, critical commentary
DOI 10.1016/j.tvjl.2008.05.010
Open Access Status
Volume 182
Issue 1
Start page 21
End page 30
Total pages 10
Editor A. J. Higgins
Place of publication The United Kingdom
Publisher W.B Saunders Co. Ltd.
Language eng
Subject C1
920120 Zoonoses
111706 Epidemiology
Abstract 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 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.
Keyword Geographical information systems
Highly pathogenic avian influenza
Rabies
Rift Valley fever
Risk analysis
Spatial analysis
West Nile virus
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online 20 August 2008. doi:10.1016/j.tvjl.2008.05.010 E-publication no issue, volume or pages numbers.

Document type: Journal Article
Sub-type: Critical review of research, literature review, critical commentary
Collections: Faculty of Health and Behavioural Sciences -- Publications
2009 Higher Education Research Data Collection
 
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Created: Wed, 25 Mar 2009, 19:59:05 EST by Geraldine Fitzgerald on behalf of School of Public Health