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Keywords:

  • Antimicrobial risk assessment;
  • campylobacter;
  • causality;
  • enrofloxacin;
  • fluoroquinolone resistance

The FDA Center for Veterinary Medicine (CVM) (Bartholomew et al., 2005) recently proposed an approach to risk management based on the linear modeling framework: Risk = K × Exposure. They suggest that, once K has been estimated from historical data, it can be used to predict how limiting future exposure will reduce future risk. They illustrate the approach for fluoroquinolone-resistant campylobacter in chicken. However, despite its appealing simplicity, the proposed approach confuses a possibly meaningless descriptive statistical ratio with a valid predictive causal relation. In general, the historical ratio K = (Risk/Exposure) may not predict how changing future exposures will affect future risks, and hence it does not necessarily provide an appropriate guide to current risk management actions. We identify several limitations of the proposed framework, including omission of frequency and severity of human health harm in quantifying “Risk” and omission of microbial load from “Exposure.” Finally, we show that an extended linear modeling approach that considers impacts of changing animal antibiotic use on susceptible as well as on resistant bacteria is consistent with the conclusion that reducing “Exposure” can greatly increase “Risk.”