P2-222 Quantitative Risk Assessment for Shiga Toxin-producing E. coli (STEC) in Producer-Distributor Bulk Milk Sold

Tuesday, July 11, 2017
Exhibit Hall (Tampa Convention Center)
Elna Buys , University of Pretoria , Pretoria , South Africa
Patrick Njage , University of Pretoria , Pretoria , South Africa
Victor Ntuli , University of Pretoria , Pretoria , South Africa
Introduction : We recently reported a high prevalence of Shigatoxin producing E. coli (STEC) O157 and non-O157 in raw and pasteurised producer-distributor bulk milk (PDBM) in South Africa. Escherichia coli has evolved from clinical novelty to primary food safety and public health concern, globally.

Purpose : The purpose of this study was to carry out a quantitative risk assessment for STEC in PDBM sold in South Africa.

Methods : Taking into account prior collected prevalence data of STEC in raw and pasteurised PDBM, and information on handling, processing, transportation and consumption patterns along the PDBM chain, probabilistic exposure models with Monte Carlo simulation were developed. Hazard characterisation was based on dose-response, using Beta-Poisson model to calculate the probability of illness from STEC. Monte Carlo simulation was carried out using @Risk software. Sensitivity analysis for the assessment of the uncertainty and variability associated with the model was also carried out. Input data used in modelling was obtained from recent published and unpublished literature from South Africa.

Results : The estimated concentration of STEC in raw and pasteurised PDBM samples was 0.12 cfu/ml and 0.08 cfu/ml, respectively. The model predicted 0.2 hemolytic uremic syndrome cases for every 20,000 consumers per annum. Sensitivity analysis to assess the uncertainty and variability associated with the model revealed boiling milk before consumption and strict control of temperature during storage along the chain have significant influence on the disease incidence.

Significance : Results from this study can be used to formulate risk-based mitigation strategies and policies under the current production and marketing conditions of PDBM in South Africa. The models can be used in other risk assessments for milk produced from similar scenarios.