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Mastitis in dairy production: Estimation of sensitivity, specificity and disease prevalence in the absence of a gold standard


Uhler, Caroline (2009). Mastitis in dairy production: Estimation of sensitivity, specificity and disease prevalence in the absence of a gold standard. Journal of agricultural, biological, and environmental statistics, 14(1):79-98.

Abstract

Mastitis, a worldwide endemic disease of dairy cows, is an important cause of decreased efficiency in milk production. Early medical treatment can reduce the nonreversible losses in milk production caused by this infection. Various diagnostic tests for mastitis are available, including a test measuring the electrical conductivity of milk (MEC test), the industry standard of somatic cell counting (SCC test), a bacteriological test, and a recently developed test measuring mammary associated amyloid A (MAA test). None of these tests is considered a gold standard, however. The aim of the present study was to determine which of these tests provides the best results, and at what cost, to improve the efficiency of milk production. For this study, 25 cows were tested at all four quarters of the udder with each of the aforementioned mastitis diagnostic tests. Based on the data, the disease prevalence as well as the sensitivity and the specificity of the four tests were estimated with a Bayesian approach by extending the Hui and Walter model with two independent tests and two populations to a model with four partially dependent tests and one population. This model was further combined with a receiver operating characteristics analysis to estimate the overall test accuracy

Abstract

Mastitis, a worldwide endemic disease of dairy cows, is an important cause of decreased efficiency in milk production. Early medical treatment can reduce the nonreversible losses in milk production caused by this infection. Various diagnostic tests for mastitis are available, including a test measuring the electrical conductivity of milk (MEC test), the industry standard of somatic cell counting (SCC test), a bacteriological test, and a recently developed test measuring mammary associated amyloid A (MAA test). None of these tests is considered a gold standard, however. The aim of the present study was to determine which of these tests provides the best results, and at what cost, to improve the efficiency of milk production. For this study, 25 cows were tested at all four quarters of the udder with each of the aforementioned mastitis diagnostic tests. Based on the data, the disease prevalence as well as the sensitivity and the specificity of the four tests were estimated with a Bayesian approach by extending the Hui and Walter model with two independent tests and two populations to a model with four partially dependent tests and one population. This model was further combined with a receiver operating characteristics analysis to estimate the overall test accuracy

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:National licences > 142-005
Dewey Decimal Classification:Unspecified
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Life Sciences > Agricultural and Biological Sciences (miscellaneous)
Physical Sciences > General Environmental Science
Life Sciences > General Agricultural and Biological Sciences
Social Sciences & Humanities > Statistics, Probability and Uncertainty
Physical Sciences > Applied Mathematics
Language:English
Date:1 March 2009
Deposited On:06 Dec 2018 15:44
Last Modified:15 Apr 2021 14:53
Publisher:Springer
ISSN:1085-7117
OA Status:Green
Publisher DOI:https://doi.org/10.1198/jabes.2009.0005

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