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Appears in Collections:Economics Technical Reports
Title: Characterising Livestock System Zoonoses Hotspots
Author(s): Kleczkowski, Adam
Breed, Andrew C
Matthews, Louise
Thronicker, Dominique
de Vries, Frans
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Citation: Kleczkowski A, Breed AC, Matthews L, Thronicker D & de Vries F (2012) Characterising Livestock System Zoonoses Hotspots. Department for International Development (DFID). University of Stirling.
Issue Date: 2012
Date Deposited: 14-Dec-2012
Publisher: University of Stirling
Abstract: A systematic review of the published literature was undertaken, to explore the ability of different types of model to help identify the relative importance of different drivers leading to the development of zoonoses hotspots. We estimated that out of 373 papers we included in our review, 108 papers touched upon the objective of 'Assessment of interventions and intervention policies', 75 addressed the objective of 'Analysis of economic aspects of disease outbreaks and interventions', 67 the objective of 'Prediction of future outbreaks', but only 37 broadly addressed the objective of 'Sensitivity analysis to identify criteria leading to enhanced risk'. Most models of zoonotic diseases are currently capturing outbreaks over relatively short time and largely ignoring socio-economic drivers leading to pathogen emergence, spill-over and spread. In order to study long-term changes we need to understand how socio-economic and climatic changes affect structure of livestock production and how these in turn affect disease emergence and spread. Models capable of describing this processes do not appear to exist, although some progress has been made in linking social and economical aspects of livestock production and in linking economics to disease dynamics. Henceforth we conclude that a new modelling framework is required that expands and formalises the 'one world, one health' strategy, enabling its deployment in the re-thinking of prevention and control strategies. Although modelling can only provide means to identify risks associated with socio-economic changes, it can never be a substitute for data collection. Finally, we note that uncertainty analysis and uncertainty communication form a key element of modelling process and yet are rarely addressed.
Type: Technical Report
Affiliation: Mathematics
Animal Health and Veterinary Laboratories Agency
University of Glasgow
University of Stirling

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