Summary of current knowledge of the size and spatial distribution of the horse population within Great Britain

被引:25
作者
Boden, Lisa A. [1 ]
Parkin, Tim D. H. [2 ]
Yates, Julia [2 ]
Mellor, Dominic [2 ]
Kao, Rowland R. [1 ]
机构
[1] Univ Glasgow, Coll Med Vet & Life Sci, Boyd Orr Ctr Populat & Ecosyst Hlth, Inst Biodivers Anim Hlth & Comparat Med, Glasgow G61 1QH, Lanark, Scotland
[2] Univ Glasgow, Coll Med Vet & Life Sci, Boyd Orr Ctr Populat & Ecosyst Hlth, Sch Vet Med, Glasgow G61 1QH, Lanark, Scotland
基金
英国惠康基金;
关键词
Equine; Demography; Spatial distribution; Infectious disease; The National Equine Database; EQUINE POPULATION;
D O I
10.1186/1746-6148-8-43
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
Background: Robust demographic information is important to understanding the risk of introduction and spread of exotic diseases as well as the development of effective disease control strategies, but is often based on datasets collected for other purposes. Thus, it is important to validate, or at least cross-reference these datasets to other sources to assess whether they are being used appropriately. The aim of this study was to use horse location data collected from different contributing industry sectors ("Stakeholder horse data") to calibrate the spatial distribution of horses as indicated by owner locations registered in the National Equine Database (the NED). Results: A conservative estimate for the accurately geo-located NED horse population within GB is approximately 840,000 horses. This is likely to be an underestimate because of the exclusion of horses due to age or location criteria. In both datasets, horse density was higher in England and Wales than in Scotland. The high density of horses located in urban areas as indicated in the NED is consistent with previous reports indicating that owner location cannot always be viewed as a direct substitute for horse location. Otherwise, at a regional resolution, there are few differences between the datasets. There are inevitable biases in the stakeholder data, and leisure horses that are unaffiliated to major stakeholders are not included in these data. Despite this, the similarity in distributions of these datasets is re-assuring, suggesting that there are few regional biases in the NED. Conclusions: Our analyses suggest that stakeholder data could be used to monitor possible changes in horse demographics. Given such changes in horse demographics and the advantages of stakeholder data (which include annual updates and accurate horse location), it may be appropriate to use these data for future disease modelling in conjunction with, if not in place of the NED.
引用
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页数:7
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