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The value of pathogen information in treating clinical mastitis

Published online by Cambridge University Press:  15 November 2016

Elva Cha ,
Rebecca L Smith ,
Anders R Kristensen ,
Julia A Hertl ,
Ynte H Schukken ,
Loren W Tauer ,
Frank L Welcome  and
Yrjö T Gröhn
Elva Cha*
Affiliation:
Department of Population Medicine and Diagnostic Sciences, Section of Epidemiology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
Rebecca L Smith
Affiliation:
Department of Pathobiology, College of Veterinary Medicine, University of Illinois, Urbana, IL 61801, USA
Anders R Kristensen
Affiliation:
Department of Large Animal Sciences, HERD – Centre for Herd-oriented Education, Research and Development, University of Copenhagen, Grønnegårdsvej 2, DK-1870 Frederiksberg C, Copenhagen, Denmark
Julia A Hertl
Affiliation:
Department of Population Medicine and Diagnostic Sciences, Section of Epidemiology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
Ynte H Schukken
Affiliation:
Department of Population Medicine and Diagnostic Sciences, Section of Epidemiology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA GD Animal Health, Deventer, The Netherlands and Department of Animal Sciences, Wageningen University, The Netherlands
Loren W Tauer
Affiliation:
Charles H. Dyson School of Applied Economics and Management, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853, USA
Frank L Welcome
Affiliation:
Department of Population Medicine and Diagnostic Sciences, Quality Milk Production Services, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
Yrjö T Gröhn
Affiliation:
Department of Population Medicine and Diagnostic Sciences, Section of Epidemiology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
*
*For correspondence; e-mail: elvacha@gmail.com
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Abstract

The objective of this study was to determine the economic value of obtaining timely and more accurate clinical mastitis (CM) test results for optimal treatment of cows. Typically CM is first identified when the farmer observes recognisable outward signs. Further information of whether the pathogen causing CM is Gram-positive, Gram-negative or other (including no growth) can be determined by using on-farm culture methods. The most detailed level of information for mastitis diagnostics is obtainable by sending milk samples for culture to an external laboratory. Knowing the exact pathogen permits the treatment method to be specifically targeted to the causation pathogen, resulting in less discarded milk. The disadvantages are the additional waiting time to receive test results, which delays treating cows, and the cost of the culture test. Net returns per year (NR) for various levels of information were estimated using a dynamic programming model. The Value of Information (VOI) was then calculated as the difference in NR using a specific level of information as compared to more detailed information on the CM causative agent. The highest VOI was observed where the farmer assumed the pathogen causing CM was the one with the highest incidence in the herd and no pathogen specific CM information was obtained. The VOI of pathogen specific information, compared with non-optimal treatment of Staphylococcus aureus where recurrence and spread occurred due to lack of treatment efficacy, was $20.43 when the same incorrect treatment was applied to recurrent cases, and $30.52 when recurrent cases were assumed to be the next highest incidence pathogen and treated accordingly. This indicates that negative consequences associated with choosing the wrong CM treatment can make additional information cost-effective if pathogen identification is assessed at the generic information level and if the pathogen can spread to other cows if not treated appropriately.

Keywords

Value of informationmastitisdairy
Type
Research Article
Information
Journal of Dairy Research , Volume 83 , Issue 4 , November 2016 , pp. 456 - 463
Copyright
Copyright © Proprietors of Journal of Dairy Research 2016 

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