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Tytuł pozycji:

Bayesian estimation of the true prevalence of paratuberculosis in Hungarian dairy cattle herds.

Tytuł:
Bayesian estimation of the true prevalence of paratuberculosis in Hungarian dairy cattle herds.
Autorzy:
Ozsvari L; Department of Veterinary Forensics and Economics, University of Veterinary Medicine Budapest, Budapest, Hungary. Electronic address: .
Lang Z; Department of Biomathematics and Informatics, University of Veterinary Medicine Budapest, Budapest, Hungary.
Monostori A; Livestock Performance Testing Ltd., Gödöllő, Hungary.
Kostoulas P; Faculty of Veterinary Science, University of Thessaly, Volos, 43100, Greece.
Fodor I; Department of Veterinary Forensics and Economics, University of Veterinary Medicine Budapest, Budapest, Hungary.
Źródło:
Preventive veterinary medicine [Prev Vet Med] 2020 Oct; Vol. 183, pp. 105124. Date of Electronic Publication: 2020 Aug 19.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Publication: Amsterdam : Elsevier Scientific Publishing
Original Publication: Amsterdam, Netherlands : Elsevier, [1982-
MeSH Terms:
Cattle Diseases/*epidemiology
Milk/*microbiology
Mycobacterium avium subsp. paratuberculosis/*isolation & purification
Paratuberculosis/*epidemiology
Animals ; Bayes Theorem ; Cattle ; Dairying ; Enzyme-Linked Immunosorbent Assay/veterinary ; Female ; Hungary/epidemiology ; Prevalence ; Probability
Contributed Indexing:
Keywords: Age-specific sensitivity; Bayesian model; Dairy cattle; Paratuberculosis; Simulation model; True prevalence
Entry Date(s):
Date Created: 20200905 Date Completed: 20210507 Latest Revision: 20210507
Update Code:
20240104
DOI:
10.1016/j.prevetmed.2020.105124
PMID:
32889487
Czasopismo naukowe
Paratuberculosis is a chronic incurable disease caused by Mycobacterium avium subsp. paratuberculosis (MAP), which leads to extensive economic losses on dairy farms, and may also pose serious public health risk to the consumers. The aim of our study was to estimate the true prevalence of paratuberculosis in commercial dairy cattle herds participating in a voluntary MAP testing programme that started in February 2018 in Hungary. Milk samples collected during official milk recording were used for MAP ELISA testing. A Bayesian two-stage hierarchical (herd and animal level) model was fitted to the data. Altogether, 26,437 cows from 51 herds were sampled, which represents 14.4 % of the Hungarian dairy cow population. The median herd size was 477 cows (interquartile range: 331-709). Each studied farm had at least one ELISA positive cow, resulting in a herd-level apparent prevalence of 100 %. The overall within herd apparent prevalence was 5.5 %. Herd-level true prevalence was estimated at 89.1 % [95 % credible interval (CrI): 80.3-95.6%]. Within the infected herds, the median animal-level true prevalence was 4.4 % (3.2-5.8%) for primiparous and 10.3 % (7.9-12.9%) for multiparous cows, respectively. The probability of having an animal-level true prevalence of at least 5% among primiparous cows, within infected herds, was 17.8 %. Similarly, the probability of having an animal-level true prevalence of at least 5% or 10 % among multiparous cows was 100 % and 56 %, respectively. Simulations assuming herd-level true prevalence varying from 50 to 100 % revealed high accuracy of our Bayesian model. Our study showed that a large percentage of the studied Hungarian dairy cattle herds was infected with MAP.
(Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

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