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Quantifying human health impacts of risk management alternatives for enrofloxacin

Quantifying human health impacts of risk management alternatives for enrofloxacin. Tony Cox and Douglas Popken Cox Associates Denver December 10 th 2002 www.cox-associates.com. Background.

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Quantifying human health impacts of risk management alternatives for enrofloxacin

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  1. Quantifying human health impacts of risk management alternatives for enrofloxacin Tony Cox and Douglas Popken Cox Associates Denver December 10th 2002 www.cox-associates.com

  2. Background • The fluoroquinolone antimicrobial enrofloxicin has been used in chickens (~1% of broiler flocks) since 1995 to prevent mortalities. • The fluoroquinolone antimicrobial ciprofloxacin is used in humans – sometimes for empiric treatment of campylobacteriosis/diarrhea. • Chickens carry campylobacter. • Fluoroquinolone-resistant campylobacter (FQ-r CP) has been isolated from human with increasing frequency since 1995. • Some investigators suspect (1) causes (4). © Cox Associates, 2002. Tony@cox-associates.com

  3. The Risk Analysis Problem • Does enrofloxacin use in chickens cause increased resistance (FQ-r CP) in humans? • If so, what are the clinical consequences? (Frequency, severity, quantitative risk assessment) • How can human health risks best be managed? • How would a ban on enrofloxacin (urged by FDA’s Center for Veterinary Medicine) affect human health risks? © Cox Associates, 2002. Tony@cox-associates.com

  4. Hazard Identification • Q: Does enrofloxacin use in chickens increase FQ-r CP in people? • Traditional answer: Of course! • Recent Data: Apparently not: • Total chicken consumption is negatively associated with risk of campylobacteriosis (CP) • Home-cooked chicken is protective against CP (Friedman et al., 2000; Effler, 2001 data; others) • Chicken consumption is not associated with FQ-r CP cases (Smith, 1999 data) © Cox Associates, 2002. Tony@cox-associates.com

  5. Ecological Data (CDC FoodNet Population Study) © Cox Associates, 2002. Tony@cox-associates.com

  6. Exploratory Data Plots Confirm Apparent Protective Effect © Cox Associates, 2002. Tony@cox-associates.com

  7. Chicken of many types is protective (CDC Data of Friedman et al.) © Cox Associates, 2002. Tony@cox-associates.com

  8. So, where does CP risk come from? • If it is not chickens, then what is it? • Speculations are plentiful… • Chickens (despite the epidemiology) • Undercooked chickens cross-contaminating other foods, e.g., salad. (But chicken juice and handling raw chicken are protective…) • Pets, especially dogs, puppies (maybe cats) • Contaminated drinking water • Commercially prepared chicken (e.g., Effler, 2001) • Epidemiology suggests that restaurants, foreign travel, human medicine, and perhaps water are the source, not chicken per se (Rodrigues, 2001, Smith 1999, etc.) © Cox Associates, 2002. Tony@cox-associates.com

  9. Quantifying Risk: Results • For females, chicken or hamburger cooked at home is protective. • Chicken or hamburger cooked commercially is a risk factor. • The RR from eating fried chicken is > 2 for commercially prepared chicken, < 0.5 for home-cooked chicken. • Similar patterns hold for males and for other types of chicken (e.g., stir-fry) and other meats (e.g., steak, sausage, hamburger). © Cox Associates, 2002. Tony@cox-associates.com

  10. Hazard Identification (Cont.) • The general pattern is consistent, robust… and not primarily about chicken. • Home-cooked meats are safe (negative association with CP risk) • Meats cooked outside the home are risky • Chicken is similar to other meats in being safe at home, risky in restaurants © Cox Associates, 2002. Tony@cox-associates.com

  11. First Conclusion on Hazard ID • Multivariate analysis confirms the pattern identified by Friedman et al. (2000) and some other authors (e.g., Effler, 2001): chicken cooked at home is protective while commercially cooked chicken is a risk factor for CP.. • It appears to be part of a more general pattern that applies to other meats too. © Cox Associates, 2002. Tony@cox-associates.com

  12. Hazard Identification Part 2: Human Health Harm • Q: Does FQ-r CP harm human health? • Traditional answer: Yes. FQ-r CP patients prescribed ciprofloxacin may have 2 excess days of diarrhea on average (CDC, Marano 2000) • Piddock (1999): Ciprofloxacin eradicated “FQ-r” CP in 38/39 cases. (FQ-r CP is an in vitro concept.) • CDC Data: No. Marano et al. seem not to have corrected for foreign travel as a confounder. © Cox Associates, 2002. Tony@cox-associates.com

  13. Confounded hazard assessment • Causal hypothesis/model 1: CIPRES  TRAVEL  DAYSDIAR, • Causal hypothesis/model 2: TRAVEL  CIPRES  DAYSDIAR • Q: Which model is correct (if either)? • How can we tell from data? • A: Implied conditional independence relations are testable and discriminate between causal models! © Cox Associates, 2002. Tony@cox-associates.com

  14. Testing Implied CI Relations • Model 2 is rejected in favor of Model 1 for domestically acquired CP cases: © Cox Associates, 2002. Tony@cox-associates.com

  15. Reanalysis of Smith (1999) Data: Chicken is not a risk factor for FQ-r CP © Cox Associates, 2002. Tony@cox-associates.com

  16. Hazard ID Conclusions • The data (CDC, Effler, Smith, etc.) do not suggest a causal relation between consumption of chicken and risk of CP… • Nor between consumption of chicken and FQ-r CP… • Nor between FQ-r CP and human health harm (excess days of diarrhea) • So, a contingent approach is needed for the rest of the risk assessment. (If a risk does exist, then how big might it be and how best to manage it?) © Cox Associates, 2002. Tony@cox-associates.com

  17. Exposure Assessment • Quantitative exposure = microbial load distribution (colony-forming units, CFUs) of CP (or FQ-r CP) ingested. • Exposure assessment quantifies the frequency distribution of microbial loads in the chicken-eating population – and how it will change for different risk management interventions. • A farm-to-fork discrete-event simulation model provides a way to integrate all the required data needed to predict exposure CDFs. © Cox Associates, 2002. Tony@cox-associates.com

  18. Farm-to-Fork Simulation: Chicken Processes © Cox Associates, 2002. Tony@cox-associates.com

  19. Human Processes © Cox Associates, 2002. Tony@cox-associates.com

  20. Farm-to-Clinic Parameters and Data © Cox Associates, 2002. Tony@cox-associates.com

  21. © Cox Associates, 2002. Tony@cox-associates.com

  22. Exposure Assessment Results • Microbial load distributions are quantified from farm to fork based on available data. • Farm-to-retail portion of the chain relies on measurements of loads. • Retail-to-illness part depends on dose-response model and matching predicted to observed/assumed chicken-attributable risks. • 20% chicken-attributable fraction assumed • < 2% is more appropriate for CDC data on FQ-r CP attributable risk among domestic cases. © Cox Associates, 2002. Tony@cox-associates.com

  23. Dose-Response Model • Black, Teunis, and others have used data from healthy young male volunteers to fit a Beta-Poisson dose-response model for CP infection and illness. • Exact and approximate models yield similar curves • The dose-response data/model suggest high risks (~20% response) above 500-800 CFU, lower risks below this range. • We adapted the Teunis et al. model, but results are insensitive to exact dose-response model. • Adjusted for age sensitivity © Cox Associates, 2002. Tony@cox-associates.com

  24. Baseline Results (assuming 2 excess days per case) © Cox Associates, 2002. Tony@cox-associates.com

  25. Example Sensitivity Analysis © Cox Associates, 2002. Tony@cox-associates.com

  26. The right tail matters most! • Sensitivity analyses show that the right tail of the microbial load distribution causes most illnesses (of course)… • Changes should concentrate on reducing this right tail (variance) rather than on the mean, which is nearly irrelevant for risk. • Good risk management is like good quality control in this case: reduce variance in microbial loads! © Cox Associates, 2002. Tony@cox-associates.com

  27. Risk management interventions evaluated • Do nothing • Ban enrofloxacin (FDA-CVM) • Additional chlorinated water (HACCP) • (2 gal/bird) • Antimicrobial spray (HACCP) • Irradiation • Process contaminated flocks last © Cox Associates, 2002. Tony@cox-associates.com

  28. Results 1: Focus on Processing © Cox Associates, 2002. Tony@cox-associates.com

  29. Results 2: Don’t Ban! A ban increases health risk! © Cox Associates, 2002. Tony@cox-associates.com

  30. Q: How can this be? • A: Banning enrofloxacin increases the prevalence of airsacculitis… • Even assuming farmer’s try other drugs • Which increases the variance in bird sizes and weights at processing… • Which increases fecal contamination and variance/right tail of microbial load. • Data: Russell, 2002 © Cox Associates, 2002. Tony@cox-associates.com

  31. What happens to the right tail? © Cox Associates, 2002. Tony@cox-associates.com

  32. Cost-Benefit Calculations • Assumes $515.53 economic loss per case (USDA, 1996, adjusted to 2001 dollars) • Net estimated US Economic costs (millions): © Cox Associates, 2002. Tony@cox-associates.com

  33. Conclusions Hazard identification does not show a chicken-caused hazard. But, if there is a human health risk, then… • HACCP-type control measures at processing create the largest estimated net benefit. • Water and spray alternatives are relatively low-tech options that are quite cost-effective • Banning enrofloxacin is the only measure that would increase human health risks. • Creates > 20 illness-days from FQ-s CP cases per day hypothetically prevented from FQ-r CP. © Cox Associates, 2002. Tony@cox-associates.com

  34. Risk Management Implications • Focus more on restaurant hygiene. • HACCP type controls at processing can reduce microbial loads and potential risks. • Human health benefits > 100 x those from reduced FQ-r CP • Successful HACCP controls further reduce benefits from farm measures • Banning enrofloxacin increases microbial loads and potential risks. • A multi-pathway analysis (look at impacts on FQ-s CP and Salmonella as well as FQ-r CP) is essential for good risk analysis and risk management in this application. © Cox Associates, 2002. Tony@cox-associates.com

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