Quantitative risk assessment of verocytotoxin-producing Escherichia coli O157 and Campylobacter jejuni related to consumption of raw milk in a province in Northern Italy.

Abstract

A quantitative risk assessment was developed to describe the risk of campylobacteriosis and hemolytic uremic syndrome (HUS) linked to consumption of raw milk sold in vending machines in Northern Italy. Exposure assessment considered the microbiological status of dairy farms, expected milk contamination, storage conditions from bulk tank to home storage, microbial growth during storage, destruction experiments, consumption frequency of raw milk, age of consumers, serving size, and consumption preference. The differential risk between milk handled under regulation conditions (4°C throughout all phases) and the worst field handling conditions was considered. The probability of Campylobacter jejuni infection was modeled with a single-hit dose-response beta-Poisson model, whereas for HUS an exponential dose-response model was chosen and two probabilities were used to model the higher susceptibility of children younger than 5 years old. For every 10,000 to 20,000 consumers each year, the models predicted for the best and worst storage conditions, respectively, 2.12 and 1.14 campylobacteriosis cases and 0.02 and 0.09 HUS cases in the 0- to 5-year age group and 0.1 and 0.5 HUS cases in the >5-year age group. The expected pediatric HUS cases do not differ considerably from those reported in Italy by the Minister of Health. The model developed may be a useful tool for extending the assessment of the risk of campylobacteriosis and HUS due to raw milk consumption at the national level in Italy. Considering the epidemiological implications of this study, the risk of illness linked to raw milk consumption should not be ignored and could be reduced by the use of simple measures. Boiling milk before consumption and strict control of temperatures by farmers during raw milk distribution have significant effects on campylobacteriosis and HUS and are essential measures for risk management.