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

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...

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Detalles Bibliográficos
Autores principales: Clements, Archie C.A., Pfeiffer, Dirk U.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110545/
https://www.ncbi.nlm.nih.gov/pubmed/18718800
http://dx.doi.org/10.1016/j.tvjl.2008.05.010
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author Clements, Archie C.A.
Pfeiffer, Dirk U.
author_facet Clements, Archie C.A.
Pfeiffer, Dirk U.
author_sort Clements, Archie C.A.
collection PubMed
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 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.
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spelling pubmed-71105452020-04-02 Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning Clements, Archie C.A. Pfeiffer, Dirk U. Vet J Article 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. Elsevier Ltd. 2009-10 2008-08-20 /pmc/articles/PMC7110545/ /pubmed/18718800 http://dx.doi.org/10.1016/j.tvjl.2008.05.010 Text en Copyright © 2008 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Clements, Archie C.A.
Pfeiffer, Dirk U.
Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
title Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
title_full Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
title_fullStr Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
title_full_unstemmed Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
title_short Emerging viral zoonoses: Frameworks for spatial and spatiotemporal risk assessment and resource planning
title_sort emerging viral zoonoses: frameworks for spatial and spatiotemporal risk assessment and resource planning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7110545/
https://www.ncbi.nlm.nih.gov/pubmed/18718800
http://dx.doi.org/10.1016/j.tvjl.2008.05.010
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