Abstract

In many countries, blanket dry cow therapy (DCT) is the standard way to dry off cows. Because of concerns about antibiotic resistance, selective DCT is proposed as an alternative. The economic consequences of different types of DCT were studied previously, but variation between input traits and different types of pathogens were not taken into account. The goal of this study was to create a stochastic Monte Carlo model to simulate the dynamics of intramammary infections (IMI) around the dry period to predict the economic consequences of DCT for different types of pathogens (Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Staphylococcus aureus, and Escherichia coli). The traits used in the model can be varied. The probabilities within the basic situation were collected from the literature and, because not all information needed was available in the literature, by interviewing experts (n = 10). The expert opinions were translated into minimum, most expected, and maximum values for each of the different probabilities. For Dutch farmers, the costs associated with mastitis and mastitis control around the dry period varied between ∉10.61 and ∉26.61 (average ∉15.60) for blanket DCT, between ∉4.86 and ∉29.41 (average ∉13.72) for selective DCT, and between ∉4.08 and ∉42.60 (average ∉18.02) for no DCT. Although there were small differences between the treatment groups, the variation within the treatment groups was much larger. The major portion of the costs for selective treatment (59% of the total costs) and no DCT (82%) was derived from the costs of clinical mastitis after calving, and for blanket DCT, the costs of treatment (65%) exceeded the costs of clinical mastitis (27%). The cost of mastitis around the dry period was most sensitive to a change in the risk of new IMI during the dry period, spontaneous cure, and costs associated with the antibiotic treatment. The optimal decision to dry off cows depends on the attitude of the farmer toward risk and other farm-specific traits and probabilities such as the new IMI rate during the dry period. Therefore, it is necessary to make farm-specific calculations so that farmers are able to factor this information into their decisions when choosing the best DCT for their situations.

Full Text
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