Mapping the likelihood of introduction and spread of HPAI Virus H5N1 in Africa, Ghana, Ethiopia, Kenya and Nigeria
The results of an analysis of the spatial distribution of disease risk and its visual presentation through risk maps allow for the design of targeted and therefore more cost-effective animal disease surveillance strategies. There are various methods by which disease risk maps can be generated. One o...
Main Authors: | , , , |
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Format: | Report |
Language: | English |
Published: |
International Food Policy Research Institute (IFPRI); International Livestock Research Institute (ILRI); Royal Veterinary College (RVC)
2009
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Subjects: | |
Online Access: | http://www.ifpri.org/publication/mapping-likelihood-introduction-and-spread-hpai-virus-h5n1-africa-ghana-ethiopia-kenya-a http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/25950 |
Summary: | The results of an analysis of the spatial distribution of disease risk and its visual presentation through risk maps allow for the design of targeted and therefore more cost-effective animal disease surveillance strategies. There are various methods by which disease risk maps can be generated. One of these is multicriteria decision modelling (MCDM) which is a knowledge-driven approach to the production of risk maps. As with all modelling work, it is important for the user of these outputs to be aware of the assumptions made in relation to the models and any potential sources of selection and information bias when interpreting the results of such analyses. The objective of this study was to describe the spatial variation in the likelihood of (i) introduction and (ii) spread of highly pathogenic avian influenza virus (HPAIV) subtype H5N1 on a continental scale in Africa. This report describes the methods used to produce likelihood maps illustrating the likelihood of introduction and subsequent spread of HPAIV H5N1 at both the continental and country level (Kenya, Nigeria, Ethiopia and Ghana; targeted countries of the DfID project), and highlights limitations associated with the maps. Non-PR IFPRI2; GRP40 |
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