This study’s objective was to estimate net returns and return risk for antimicrobial metaphylaxis options to manage bovine respiratory disease (BRD) in high health-risk feedlot cattle. The effectiveness of antimicrobials for metaphylaxis varies by cattle population. How differing antimicrobial effectiveness translates to net return profitability for heterogeneous cattle populations is less understood. Net returns and return risk were assessed using a net return simulation model adapted to allow for heterogeneity in high health-risk cattle placement characteristics and antimicrobial choice to control BRD. The net return model incorporated how antimicrobials modify BRD health and performance outcomes. Health and performance outcomes were calibrated from published literature and proprietary feedlot data. Proprietary data came from 10 Midwestern feedlots representing nearly 6 million animals and 50,000 cohorts. Twelve placement-by-metaphylaxis decision combinations were assessed: high health-risk steer placement demographics were 600 or 800 lb steers placed in Winter (Oct–Mar) or Summer (Apr–Sept) managed with one of three different health programs: “no metaphylaxis,” “Upper Tier” antimicrobial, or “Lower Tier” antimicrobial. Net return distributions were compared between “no metaphylaxis” and a specific antimicrobial tier within specific cattle populations. We found the expected incremental net return of administering an “Upper Tier” (“Lower Tier”) antimicrobial for metaphylaxis compared to “no metaphylaxis” for high health-risk steers was $122.55 per head ($65.72) for 600 lb and $148.65 per head ($79.65) for 800 lb winter placements. The incremental expected net return and risk mitigated by metaphylaxis varied by placement weight, season, and antimicrobial choice. The probability net returns would decline by at least $50 per head was significantly reduced (from approximately 4% to 40%) when any antimicrobial was used on high health-risk steers. Both tiers of antimicrobials used for metaphylaxis increased expected net returns and decreased net return variability relative to no metaphylaxis. Thus, feedlots were more certain and realize a greater profit on high health-risk pens of steers when metaphylaxis was used. This occurred because the reduction in cattle health and performance outcomes using any antimicrobial was sufficiently large to cover added initial and subsequent antimicrobial costs. Results aid in assessing metaphylaxis strategies in high health-risk cattle.

Food safety remains a major issue to many consumers. Previous studies examining the economic impact of food safety recalls have focused on Class I recalls. Antibiotic residue in meat products, a Class II recall, has increased in consumer importance yet little is known about how much research and development expenditure should be allocated to reduce antibiotic residue pre-and post-harvest. This study compares demand elasticities and the decrease in willingness to pay in response to either an E. coli (Class I) or antibiotic residue (Class II) recall. We compare and contrast two competing behavioral frameworks, Random Utility and Regret Minimizing. Modeling behavior using the random regret framework is found to be more powerful for assessing consumer responses. In addition, we explore if different groups of consumers exist that either maximize utility or minimize regret. Consumer devaluations of E. coli (Class I) are 40-65% larger than antibiotic residue (Class II). Approximately 60% of consumers are identified as regret minimizers and 40% were identified as utility maximizers. While industry response and government policy recommendations differed conditional on modeling framework, the regret minimizing framework required smaller price discounts than regret minimizing to maintain the same level of market share.

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Conventional choice experiments ask respondents to choose their most preferred item, but in reality, consumers select both an item and quantity. Using a split sample design focused on U.S. meat demand, we find that flexibility in consumer quantity choice provides similar choice rationality and consumer segmentation as the conventional restricted quantity framework. Improvements include generating choice frequencies consistent with historical purchase data and willingness-to-pay estimates more comparable to observed retail price data.Additional benefits include the ability to understand consumer preferences for variety and habit formation and generated data that is compatible with traditional demand estimation, all of which are not possible under the conventional restricted quantity framework.

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