Using economic outcomes in the evaluation of metaphylactic antibiotic decision making for control of bovine respiratory disease in feedyard cattle

Abstract

The decision to use metaphylactic antibiotics to control bovine respiratory disease in feedyard cattle has important economic, animal welfare, and antimicrobial stewardship impacts. Models that consider risk factors for benefitting economically from metaphylaxis including cattle characteristics, disease characteristics (i.e. metaphylaxis efficacy), production costs (animal purchase, feed, labor, facilities, etc.), and income value of cattle sold show that these characteristics have complex interactions with each other and the financial outcome of a cohort of cattle. Two modeling methods were used to identify key variables driving economic metaphylactic decisions. The first economic model evaluated the cohort characteristics of cattle that did not receive metaphylaxis at the feedyard but that would benefit economically. Estimated net returns were calculated for 12,785 cohorts for three metaphylactic options: no metaphylaxis, low-cost/low-efficacy metaphylaxis, and high-cost/high-efficacy metaphylaxis. Logistic regression models were used to determine the probability of cohorts benefiting from metaphylaxis. Results show that cohort demographics such as sex, entry weight category, cohort size, and average daily gain influence the probability of a cohort benefiting economically from metaphylaxis. Monte Carlo simulation is a technique that uses random sampling of uncertain variable(s) to estimate a range of potential outcomes. While Monte Carlo simulation is used regularly in other disciplines, it is scarcely utilized to determine the economics of health outcomes in veterinary medicine. The use of Monte Carlo simulation to quantify the economic benefits of metaphylaxis is a novel approach to metaphylactic decision making. A second economic model was developed that used a Monte Carlo-based stochastic approach to evaluate the economic benefits of metaphylactic antibiotics. Original cohort data (n=16,368 lots) were modeled for the actual and the opposite metaphylactic scenarios, then simulated across 10 years of monthly pricing data to generate cohort-month scenarios. The cohort-month scenarios were replicated 10 times, with each replication randomly sampling a metaphylactic efficacy odds ratio and average daily gain adjustment factor. Linear regression and standardized beta coefficients identified mortality due to bovine respiratory disease as the most influential variable of difference in net returns between metaphylaxis and no metaphylaxis. Together, these chapters provide evidence-based tools that advance economically sound, welfare-conscious, and stewardship-focused metaphylaxis decisions in feedyard cattle. These findings show that advanced modeling can help to guide more accurate metaphylactic antibiotic use in feedyard cattle.