Epidemic characteristics, drug-resistant analysis and quantitative risk assessment of Salmonella in poultry meat in Shanghai

CAI Hua, SONG Xia,XU Biyao, QIU Danping, QIN Luxin, YANG Jingjin,LUO Baozhang,LIU Hong

Zhongguo shipin weisheng zazhi(2022)

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摘要
ObjectiveTo investigate the contamination and drug-resistant distribution of Salmonella in poultry meat in Shanghai and conduct a quantitative risk assessment.MethodsAccording to the method of microbiological risk assessment, the risk assessment of Salmonella in poultry meat was carried out by four steps: hazard identification, hazard characterization, exposure assessment and risk characterization. The data for hazard identification and hazard characterization were derived from published scientific literatures and reports. Combining quantitative data of Salmonella with residents’ consumption data of poultry meat, a Beta-Poisson dose-response model and Monte Carlo simulation method were applied to analyze the health risk.ResultsThe contamination rate of Salmonella in poultry meat was 13.0% (68/522) in Shanghai and about 78.2% (43/55) of the isolates showed antimicrobial resistance. The resistance rate to ampicillin, tetracycline and ampicillin/sulbactam was over 30%. The multiple drug resistance rate was 43.6% (24/55). Estimated probability of infectious illness was 8.32×10-5. That indicated the number of illnesses might reach 25 339 cases every year, of which 19 815 were infected by drug-resistant strains and 11 048 were infected by multi-drug-resistant strains. Sensitivity analysis showed that the initial contamination concentration, consumption per serving and two cross-contamination parameters had greater impact.ConclusionA high level antimicrobial resistance was found among Salmonella isolates from poultry meat in Shanghai, so was the multi-drug resistance condition. The risk of Salmonella in poultry meat is relatively high for Shanghai population, and cross-contamination is one of the main factors.
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关键词
drug-resistant salmonella,poultry meat,cross-contamination,quantitative risk assessment,monte carlo simulation
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