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Antimicrobial Resistance Risk Assessment of Vibrio parahaemolyticus Isolated from Farmed Green Mussels in Singapore.

Hong Ming Glendon OngYang ZhongChengcheng HuKar Hui OngWei Ching KhorJoergen SchlundtKyaw Thu Aung
Published in: Microorganisms (2023)
Vibrio parahaemolyticus , commonly found in seafood products, is responsible for gastroenteritis resulting from the consumption of undercooked seafood. Hence, there is a need to characterize and quantify the risk involved from this pathogen. However, there has been no study reporting the quantification of hemolytic antimicrobial-resistant (AMR) Vibrio parahaemolyticus in locally farmed shellfish in Singapore. In this study, ampicillin, penicillin G, tetracycline resistant, and non-AMR hemolytic V. parahaemolyticus were surveyed and quantified in green mussel samples from different premises in the food chain (farm and retail). The occurrence data showed that 31/45 (68.9%) of farmed green mussel samples, 6/6 (100%) farm water samples, and 41/45 (91.1%) retail shellfish samples detected the presence of hemolytic V. parahaemolyticus. V. parahaemolyticus counts ranged from 1.6-5.9 Log CFU/g in the retail shellfish samples and 1.0-2.9 Log CFU/g in the farm water samples. AMR risk assessments (ARRA), specifically for ampicillin, penicillin G, tetracycline, and hemolytic (non-AMR) scenarios were conducted for the full farm-to-home and partial retail-to-home chains. The hemolytic ARRA scenario estimated an average probability of illness of 5.7 × 10 -3 and 1.2 × 10 -2 per serving for the full and partial chains, respectively, translating to 165 and 355 annual cases per total population or 2.9 and 6.2 cases per 100,000 population, respectively. The average probability of illness per year ratios for the three ARRAs to the hemolytic ARRA were 0.82, 0.81, and 0.47 (ampicillin, penicillin G, and tetracycline, respectively) for the full chain and 0.54, 0.39, and 0.09 (ampicillin, penicillin G, and tetracycline, respectively) for the partial chain. The sensitivity analysis showed that the overall cooking effect, initial concentrations of pathogenic V. parahaemolyticus , and harvest duration and harvest temperature were key variables influencing the risk estimates in all of the modelled ARRAs. The study findings can be used by relevant stakeholders to make informed decisions for risk management that improve food safety.
Keyphrases
  • antimicrobial resistance
  • risk assessment
  • healthcare
  • deep learning