An analysis of recovery probability from high somatic cell counts in UK dairy cows

  • Madeleine Archer School of Agriculture, Policy and Development, University of Reading, Whiteknights, PO Box 237, Reading, RG6 6AR, UK
  • Nicholas Taylor Veterinary Epidemiology and Economics Research Unit (VEERU) - School of Agriculture, Policy and Development, University of Reading, Whiteknights, PO Box 237, Reading, RG6 6AR, UK
  • James Hanks Veterinary Epidemiology and Economics Research Unit (VEERU) - School of Agriculture, Policy and Development, University of Reading, Whiteknights, PO Box 237, Reading, RG6 6AR, UK
  • Yiorgos Gadanakis School of Agriculture, Policy and Development, University of Reading, Whiteknights, PO Box 237, Reading, RG6 6AR, UK

Published:

2019-12-11

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DOI

https://doi.org/10.18849/ve.v4i4.205

Abstract

Objective:

The particular interest of this study was to identify the relative impacts of magnitude and category of high SCC on ‘recovery’, once other factors were taken into account.

Background:

A high SCC (≥200 thousand cells/ml) is commonly associated with intra-mammary infection (IMI), one of the most economically important diseases faced by the dairy industry. High SCC is important in its own right because the bulk milk tank SCC is a determinant of the price farmers receive for their milk.

Evidentiary value:

A high SCC may be transient, returning (‘recovering’) to low SCC at the next monthly milk recording. Better understanding of factors influencing the probability of ‘recovery’ from high SCC, could improve decision making on how to manage cows with high SCCs in the most effective manner to minimise both production loss and unnecessary interventions that may include antimicrobial use.

Methods:

This research used monthly milk recording data to explore how the probability of ‘recovery’ from high somatic cell count (SCC) is associated with different factors such as parity, stage of lactation, the magnitude of SCC and category of high SCC (e.g. new or chronic). Different factors (SCC magnitude; category of high SCC, e.g. new or chronic; parity; and lactation stage) were analysed using a multilevel, mixed effect logistic regression model to assess the association with recovery probability. Data of 12,250 full lactation records from 499 milk-recorded UK dairy herds were used, from which 30,080 high SCC ‘cases’ were analysed.

Results:

In line with established evidence, increasing parity, increasing days in lactation and increasing magnitude of SCC are associated with decreased probability of recovery. The important result is that the category of high SCC is the most influential factor, with probability of recovery after two consecutive high SCC being around half or less the probability of recovery after just one high SCC.

Conclusion:

The results provide evidential support for category of high SCC to be used ahead of magnitude of SCC when advising farmers about prioritising high SCC cases for investigation and possible treatment, drying-off or culling.

Application:

Dairy herd management software companies should work with farmers and their advisors to ensure SCC data are presented in the most useful way, allowing easy interpretation and translation into the most effective interventions that can increase the efficiency of the dairy industry as well as avoiding needless or ineffectual interventions, that may include use of antimicrobials.

 

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