First report of the within-farm prevalence of bovine digital dermatitis in Chinese Holstein dairy cows in Jiangsu, China: A Bayesian modelling approach

Digital dermatitis is one of the most important causes of lameness in dairy cattle, particularly in housed, intensively-managed cattle. The number of modern intensive dairy farms in China has increased markedly in recent years; however, we lack research on digital dermatitis in Chinese dairy cattle....

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Veröffentlicht in:Research in veterinary science 2024-06, Vol.172, p.105238-105238, Article 105238
Hauptverfasser: Ma, X., Laven, R.A., Jiang, P., Yang, D.A.
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Sprache:eng
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Zusammenfassung:Digital dermatitis is one of the most important causes of lameness in dairy cattle, particularly in housed, intensively-managed cattle. The number of modern intensive dairy farms in China has increased markedly in recent years; however, we lack research on digital dermatitis in Chinese dairy cattle. This preliminary study aimed to estimate the prevalence of digital dermatitis on three conveniently selected farms in Jiangsu, China. The washed hind feet of all lactating cows on all three farms were examined during milking with the aid of a mobile phone light source. True prevalence was then estimated from the apparent prevalence using a Bayesian superpopulation approach to account for the imperfect nature of identifying digital dermatitis in cows during milking. Despite none of the farms having thought it necessary to implement routine digital dermatitis monitoring or control, the disease was found on all three sampled farms. All lesions observed were either chronic M4 or M4.1 type-lesions, with no M2 lesions (i.e. acute ulcerated lesions) observed. The estimated true prevalences on the farms were 7.3% (95% credible interval [CrI]: 5.4%–9.6%), 8.3% (95%CrI: 6.3%–10.8%), and 29.8% (95%CrI: 22.9%–37.2%). •This is the first epidemiological study of bovine digital dermatitis (DD) in China.•The lesions are lack of variations in morphological stages with lesions being observed as M4 and M4.1 lesions.•An advanced statistical method was implemented to estimate the DD prevalence after accounting for the imperfect diagnostic method.
ISSN:0034-5288
1532-2661
DOI:10.1016/j.rvsc.2024.105238