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We used a retrospective modeling approach instead of the traditional farm to fork model; back calculating (Cm) the number of human macrolide resistant C. coli mfections caused by eating contaminated pork, due to specific macrolide use in swine. We used the estimated number of culture confirmed human infections (Ct). As a measure of human health risk, we then calculated the expected number among the (Cm) cases that experience an adverse treatment outcome (prolonged illness) due to macrolide resistance, using estimates for fluoroqu inolone. We divided the model into Release, Exposure and Consequence assessment sections according to FDA guidance 152 and utilized @Risk software with 20,000 iterations for simulation. The results show the human health risks are negligible. For example, the predicted annual risk, for preventton and growth promotion uses is only 1 in 92 million per U.S. resident, with a 5% chance it could be as high as 1 in 52 million. Our model focuses on the impact of resistance on human treatment. It assumes that macrolide resistance C. coli infection reduces treatment efficacy. However, it is possible that risks less than our estimates. Introduction Campylobacter is considered an important food-borne pathogen. Erythromycin. a macrolide antibiottc, is recommended for the treatment and control of severe culture confirmed campylobacteriosis. Recent studies have reported higher frequencies of resistant Campylobacter in conventional swine farms compared to antibiotic free farms. There are concerns that macrolide antibiotic use on swine farms may increase human health risk. Our objective was to conduct a stochastic quantitative risk assessment of potential adverse health outcomes due to macrolide resistant C. coli infection originating from macrolide use on the swine farm. Materials and Methods We chose a retrospective modeling approach instead of the traditional farm to fork model which is significantly more data intensive. Hence, we back calculated (Cm) the number of human macrolide resistant C. coli infections caused by eating contaminated pork, due to a specific type of macrolide use in swine. We started with estimated number of total culture confirmed human tnfections (Ct). As a measure of human health risk, we then calculated the expected number among the Cm cases that might experience an adverse treatment outcome due to macrolide resistance. An adverse treatment outcome refers to ineffective treatment resulting in prolonged illness such as extra days of diarrhea or fever. We divided our model into Release, Exposure and Consequence assessment secttons according to FDA guidance 152 (www. fda.qov/cvm/guidance/fquide152 DOC). We utilized a variety of uncertainty distributions for the parameters and simulated with @Risk software (20,000 iterations). Release Assessment: In th is section , we calculated the fraction of C. coli population 1n swine that is macrolide resistant due to different types of macrolide (rm). Following we describe the estimatton of rm for prevention and growth promotion uses (Tylan Premix® and Tylan Sulfa-G ®) followed by the estimation for treatment and control uses (Tylan Injection®, Tylan Soluble® and Pulmotil Premix®) Let rb be the background resistant fraction that exists without exposure to macrol ide, and r1 be the steady state resistant fraction in a conventional farm in which a fraction (a) of the swine have been exposed to a specific macrolide. The total resistant fraction (r1) is linearly related to the fract1on exposed (a) as a first order approximation shown m Equation 1. 14 S fepork 2007Verona (Italy) Sesston 1: Risk assessment and Public health

A Quantitative Risk Assessment of the Human Health Impacts Due to Macrolide Use in Swine