Final published version
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Rationalising development of classification systems describing livestock production systems for disease burden analysis within the Global Burden of Animal Diseases programme
AU - Li, Yin
AU - McIntyre, K. Marie
AU - Rasmussen, Philip
AU - Gilbert, William
AU - Chaters, Gemma
AU - Raymond, Kassy
AU - Jemberu, Wudu T.
AU - Larkins, Andrew
AU - Patterson, Grace T.
AU - Kwok, Stephen
AU - Kappes, Alexander James
AU - Mayberry, Dianne
AU - Schrobback, Peggy
AU - Acosta, Mario Herrero
AU - Stacey, Deborah A.
AU - Huntington, Benjamin
AU - Bruce, Mieghan
AU - Knight-Jones, Theodore
AU - Rushton, Jonathan
PY - 2024/3/31
Y1 - 2024/3/31
N2 - The heterogeneity that exists across the global spectrum of livestock production means that livestock productivity, efficiency, health expenditure and health outcomes vary across production systems. To ensure that burden of disease estimates are specific to the represented livestock population and people reliant upon them, livestock populations need to be systematically classified into different types of production system, reflective of the heterogeneity across production systems.This paper explores the data currently available of livestock production system classifications and animal health through a scoping review as a foundation for the development of a framework that facilitates more specific estimates of livestock disease burdens. A top-down framework to classification is outlined based on a systematic review of existing classification methods and provides a basis for simple grouping of livestock at global scale.The proposed top-down classification framework, which is dominated by commodity focus of production along with intensity of resource use, may have less relevance at the sub-national level in some jurisdictions and will need to be informed and adapted with information on how countries themselves categorize livestock and their production systems. The findings in this study provide a foundation for analysing animal health burdens across a broad level of production systems. The developed framework will fill a major gap in how livestock production and health are currently approached and analysed.
AB - The heterogeneity that exists across the global spectrum of livestock production means that livestock productivity, efficiency, health expenditure and health outcomes vary across production systems. To ensure that burden of disease estimates are specific to the represented livestock population and people reliant upon them, livestock populations need to be systematically classified into different types of production system, reflective of the heterogeneity across production systems.This paper explores the data currently available of livestock production system classifications and animal health through a scoping review as a foundation for the development of a framework that facilitates more specific estimates of livestock disease burdens. A top-down framework to classification is outlined based on a systematic review of existing classification methods and provides a basis for simple grouping of livestock at global scale.The proposed top-down classification framework, which is dominated by commodity focus of production along with intensity of resource use, may have less relevance at the sub-national level in some jurisdictions and will need to be informed and adapted with information on how countries themselves categorize livestock and their production systems. The findings in this study provide a foundation for analysing animal health burdens across a broad level of production systems. The developed framework will fill a major gap in how livestock production and health are currently approached and analysed.
U2 - 10.1016/j.rvsc.2023.105102
DO - 10.1016/j.rvsc.2023.105102
M3 - Journal article
VL - 168
JO - Research in Veterinary Science
JF - Research in Veterinary Science
SN - 0034-5288
M1 - 105102
ER -