A Bayesian approach to interpreting Staphylococcus aureus diagnostic indicators for on-farm decision making

Sandra Costello; George Shook; Terry Smith

A Bayesian approach to interpreting Staphylococcus aureus diagnostic indicators for on-farm decision making

In: Mastitis in dairy production

Authors:

Sandra Costello

Sandra Costello ¹Dairy Alliance, Penn State University, USA

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George Shook

George Shook ²Dairy Science Department, University of Wisconsin, Madison, USA

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Terry Smith

Terry Smith ³Dairy Strategies, Madison, USA

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Type:: Chapter

Pages:: 455–461

DOI:: https://doi.org/10.3920/9789086865505_068

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A Bayesian network (BN) modeled Staphylococcus aureus (SA) evidence on probability of mastitis in individual cows. Herd evidence was provided by bulk tank culture (BTC), antibody test (BTMAb), somatic cell count (BTSCC), and risk factors (HRF). Culture (CC), antibody test (CowAb), lactation-to-date somatic cell score (C-SCS), and risk factors (CRF) provided cow evidence. Herd evidence served as priors (P(SA)) to cow probabilities. Risk factors were processed as likelihoods based on strength of association to SA. Two herd scenarios were modeled. Herd-1 had moderate (17%) while Herd-2 had high risk of SA (43%). HRF had little effect on cow posterior probabilities when risk was moderate unless herd diagnostic indicators were high. Given Herd-1, P(SA) ranged from 1.7 to 91.8% depending on herd diagnostic evidence. Given Herd-2, posterior probabilities ranged from 5.8 to 97.6% with the same evidence. Two cow scenarios were modeled to evaluate effects of CRF on posteriors when combined with herd and cow diagnostic evidence. Overall likelihood was 1.33 for Cow-1 and 1.69 for Cow-2. Given Cow-2 and Herd-1, a positive BTC and high BTMAb, cow posterior probabilities exceeded 50% when C-SCS was below 3.0. Given Herd-1 and Cow- 2, cow posteriors exceeded 50% when BTC was positive and C-SCS above 6.0. As strength of herd evidence increased, probability of cow infections increased, improving SA detection with less cow diagnostic evidence. Probabilities can assist dairy managers in determining relevancy of diagnostic indicators for mastitis decision-making.

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Mastitis in dairy production

Current knowledge and future solutions

E-Book ISBN:: 9789086865505

Publisher:: Wageningen Academic

Print Publication Date:: 24 Oct 2005

Subjects
- Life Sciences

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A Bayesian approach to interpreting Staphylococcus aureus diagnostic indicators for on-farm decision making

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Mastitis in dairy production

Current knowledge and future solutions

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