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文化和算法指导的选择性干奶牛疗法的部分预算分析。

Partial budget analysis of culture- and algorithm-guided selective dry cow therapy.

机构信息

Department of Veterinary Population Medicine, University of Minnesota, St. Paul 55108; Faculty of Science, Sydney School of Veterinary Science, The University of Sydney, Camden, New South Wales 2570, Australia.

Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853.

出版信息

J Dairy Sci. 2021 May;104(5):5652-5664. doi: 10.3168/jds.2020-19366. Epub 2021 Mar 6.

DOI:10.3168/jds.2020-19366
PMID:33685701
Abstract

The objectives of this study were to (1) use partial budget analysis to estimate the cash impact for herds that switch from blanket dry cow therapy (BDCT) to culture- or algorithm-guided selective dry cow therapy (SDCT) and (2) conduct a sensitivity analysis to investigate effects in situations where SDCT increased clinical and subclinical mastitis risk during the subsequent lactation. A partial budget model was created using Monte Carlo simulation with @Risk software. Expenditures associated with dry-off procedures and health outcomes (clinical and subclinical mastitis) during the first 30 d in milk were used to model herd-level effects, expressed in units of US dollars per cow dry-off. Values for each economic component were derived from findings from a recent multisite clinical trial, peer-reviewed journal articles, USDA databases, and our experiences in facilitating the implementation of SDCT on farms. Fixed values were used for variables expected to have minimal variation within the US dairy herd population (e.g., cost of rapid culture plates) and sampling distributions were used for variables that were hypothesized to vary enough to effect the herd net cash impact of one or more DCT approach(es). For Objective 1, herd-level udder health was assumed to be unaffected by the implementation of SDCT. For culture-guided SDCT, producers could expect to save an average of +$2.14 (-$2.31 to $7.23 for 5th and 95th percentiles) per cow dry-off as compared with BDCT, with 75.5% of iterations being ≥$0.00. For algorithm-guided SDCT, the mean net cash impact was +$7.85 ($3.39-12.90) per cow dry-off, with 100% of iterations being ≥$0.00. The major contributors to variance in cash impact for both SDCT approaches were percent of quarters treated at dry-off and the cost of dry cow antibiotics. For Objective 2, we repeated the partial budget model with the 30-d clinical and subclinical mastitis incidence increasing by 1, 2, and 5% (i.e., risk difference = 0.01, 0.02, and 0.05) in both SDCT groups compared with BDCT. For algorithm-guided SDCT, average net cash impacts were ≥$0.00 per cow dry-off (i.e., cost effective) when mastitis incidence increased slightly. However, as clinical mastitis incidence increased, economic returns for SDCT diminished. These findings indicate that when SDCT is implemented appropriately (i.e., no to little negative effect on health), it might be a cost-effective practice for US herds under a range of economic conditions.

摘要

本研究的目的是

(1)使用部分预算分析来估计从 blanket dry cow therapy(BDCT)转为 culture- 或 algorithm-guided selective dry cow therapy(SDCT)的牛群的现金影响;(2)进行敏感性分析,以调查在随后的泌乳期,SDCT 增加临床和亚临床乳腺炎风险的情况下的影响。使用 @Risk 软件的蒙特卡罗模拟创建了一个部分预算模型。使用干奶牛程序和产犊后 30 天内健康结果(临床和亚临床乳腺炎)的支出来模拟牛群水平的影响,以每头奶牛干奶的美元单位表示。每个经济组成部分的值均源自最近的多地点临床试验、同行评议的期刊文章、USDA 数据库以及我们在农场实施 SDCT 的经验。对于预计在美国奶牛群中变化很小的变量(例如,快速培养板的成本),使用固定值,而对于假设变化足以影响一种或多种 DCT 方法的牛群净现金影响的变量,则使用抽样分布。对于目标 1,假设实施 SDCT 不会影响乳房健康。与 BDCT 相比,对于 culture-guided SDCT,生产者每头奶牛干奶可节省平均+2.14 美元(第 5 个和第 95 个百分位数为+2.14 美元至+7.23 美元),其中 75.5%的迭代结果≥0.00 美元。对于 algorithm-guided SDCT,平均净现金影响为每头奶牛干奶+7.85 美元(+3.39 美元至+12.90 美元),100%的迭代结果≥0.00 美元。两种 SDCT 方法的现金影响差异的主要贡献因素是干奶牛期处理的乳房象限比例和干奶牛抗生素的成本。对于目标 2,我们使用 30 天的临床和亚临床乳腺炎发病率增加 1%、2%和 5%(即风险差异=0.01、0.02 和 0.05)的部分预算模型重复进行了模型。与 BDCT 相比,对于 algorithm-guided SDCT,当乳腺炎发病率略有增加时,每头奶牛干奶的平均净现金影响≥0.00 美元(即具有成本效益)。然而,随着临床乳腺炎发病率的增加,SDCT 的经济回报减少。这些发现表明,在适当实施 SDCT 的情况下(即对健康没有负面影响或影响很小),在美国的许多经济条件下,SDCT 可能是一种具有成本效益的实践。

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