Down P M, Green M J, Hudson C D
School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, LE12 5RD, United Kingdom.
J Dairy Sci. 2013 Oct;96(10):6301-14. doi: 10.3168/jds.2012-6470. Epub 2013 Aug 16.
The aim of this research was to use probabilistic sensitivity analysis to evaluate the relative importance of different components of a model designed to estimate the cost of clinical mastitis (CM). A particular focus was placed on the importance of pathogen transmission relative to other factors, such as milk price or treatment costs. A stochastic Monte Carlo model was developed to simulate a case of CM at the cow level and to calculate the associated costs for 5 defined treatment protocols. The 5 treatment protocols modeled were 3 d of antibiotic intramammary treatment, 5 d of antibiotic intramammary treatment, 3 d of intramammary and systemic antibiotic treatment, 3d of intramammary and systemic antibiotic treatment plus 1 d of nonsteroidal antiinflammatory drug treatment, and 5 d of intramammary and systemic antibiotic treatment. Uniform distributions were used throughout the model to enable investigation of the cost of CM over a spectrum of clinically realistic scenarios without specifying which scenario was more or less likely. A risk of transmission parameter distribution, based on literature values, was included to model the effect of pathogen transmission to uninfected cows, from cows that remained subclinically infected after treatment for CM. Spearman rank correlation coefficients were used to evaluate the relationships between model input values and the estimated cost of CM. Linear regression models were used to explore the effect that changes to specific independent variables had on the cost of CM. Risk of transmission was found to have the strongest association with the cost of CM, followed by bacteriological cure rate, cost of culling, and yield loss. Other factors such as milk price, cost of labor, and cost of medicines were of minimal influence in comparison. The cost of CM was similar for all 5 treatment protocols. The results from this study suggest that, when seeking to minimize the economic impact of CM in dairy herds, great emphasis should be placed on the reduction of pathogen transmission from cows with CM to uninfected cows.
本研究的目的是使用概率敏感性分析来评估一个旨在估算临床型乳腺炎（CM）成本的模型中不同组成部分的相对重要性。特别关注病原体传播相对于其他因素（如牛奶价格或治疗成本）的重要性。开发了一个随机蒙特卡洛模型，以模拟奶牛层面的一例CM病例，并计算5种既定治疗方案的相关成本。所模拟的5种治疗方案分别是：3天的抗生素乳房内治疗、5天的抗生素乳房内治疗、3天的乳房内和全身性抗生素治疗、3天的乳房内和全身性抗生素治疗加1天的非甾体抗炎药治疗，以及5天的乳房内和全身性抗生素治疗。在整个模型中使用均匀分布，以便在一系列临床现实场景中研究CM的成本，而无需指定哪种场景更有可能或更不可能。基于文献值纳入了传播参数分布风险，以模拟病原体从治疗CM后仍处于亚临床感染状态的奶牛传播到未感染奶牛的影响。使用斯皮尔曼等级相关系数来评估模型输入值与CM估计成本之间的关系。使用线性回归模型来探讨特定自变量的变化对CM成本的影响。发现传播风险与CM成本的关联最强，其次是细菌学治愈率、淘汰成本和产量损失。相比之下，其他因素如牛奶价格、劳动力成本和药品成本的影响最小。所有5种治疗方案的CM成本相似。本研究结果表明，当试图将CM对奶牛群的经济影响降至最低时，应高度重视减少从患有CM的奶牛向未感染奶牛的病原体传播。
