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.

Bovine beta casein A1 is one of the most common variants in dairy cattle breeds; it is considered a risk factor in milk intolerance and in other important human diseases, because of the bioactive peptide beta casomorphin-7 (BCM7) produced by raw or processed A1-milk, but not by A2-milk, during digestion. The aim of this study was to perform a cheap and rapid method to investigate beta casein polymorphism in copious animals. The study included 2 dairy farms with a totally of 1230 cows. Beta casein genotypes were estimated evaluating Exon 7 region of bovine beta casein gene (CSN2) by sequences analysis. In the population included in the study 5 variants (A1, A2, B, F, I) and 13 genotypes (A1A1, A1A2, A1B, A1F, A1I, A2A2, A2B, A2F, A2I, BB, BF, BI, FI) were detected. The method showed high sensibility and specificity, resulted low-cost and few time consuming.

A retrospective observational study evaluated the risk factors for pre-slaughter losses (i.e. animal deaths occurring during transport and lairage) and their economic impact in Italian heavy pigs (~160 kg bodyweight). Of the 3 344 730 pigs transported, 1780 (0.053%) died before slaughter, with most losses occurring during transport (56.6%). The estimated economic impact was of 424 000 €. The percentage of batches with at least one animal lost pre-slaughter increased during summer (P < 0.001). The proportion of pre-slaughter losses was higher when journey lasted more than 90 min (P < 0.001) and was positively correlated with transport duration (P < 0.01). Losses were higher (P < 0.01) in batches transported at low stocking densities (i.e. when heavier pigs were transported). Batches with lower slaughtering order (i.e. longer lairage time) had higher proportions of losses (P < 0.001). Logistic regression analysis showed that the odds of a given batch to have at least one animal lost pre-slaughter were 1.32 times higher for batches slaughtered in summer, 1.54 times higher if journey durations exceeded 90 min, 1.25 times higher for batches with low slaughtering order, and not significantly influenced by stocking density during transport.Additional keywords: economic impact, pig welfare, transport.The identification of critical points during transport and slaughtering procedures may significantly improve animal welfare during transport. In heavy pigs, long travel duration, low stocking density and overnight lairage resulted in increased animal losses. The routine collection and analysis of animal-loss data at slaughterhouses could reduce the economic impact of animal losses and be of help in improving future legislation on the protection of pigs during transport.

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A quantitative risk assessment (RA) was developed to estimate haemolytic-uremic syndrome (HUS) cases in paediatric population associated with the consumption of raw milk sold in vending machines in Italy. The historical national evolution of raw milk consumption phenomenon since 2008, when consumer interest started to grow, and after 7 years of marketing adjustment, is outlined. Exposure assessment was based on the official Shiga toxin-producing Escherichia coli O157:H7 (STEC) microbiological records of raw milk samples from vending machines monitored by the regional Veterinary Authorities from 2008 to 2014, microbial growth during storage, consumption frequency of raw milk, serving size, consumption preference and age of consumers. The differential risk considered milk handled under regulation conditions (4°C throughout all phases) and the worst time-temperature field handling conditions detected. In case of boiling milk before consumption, we assumed that the risk of HUS is fixed at zero. The model estimates clearly show that the public health significance of HUS cases due to raw milk STEC contamination depends on the current variability surrounding the risk profile of the food and the consumer behaviour has more impact than milk storage scenario. The estimated HUS cases predicted by our model are roughly in line with the effective STEC O157-associated HUS cases notified in Italy only when the proportion of consumers not boiling milk before consumption is assumed to be 1%. Raw milk consumption remains a source of E. coli O157:H7 for humans, but its overall relevance is likely to have subsided and significant caution should be exerted for temporal, geographical and consumers behaviour analysis. Health education programmes and regulatory actions are required to educate people, primarily children, on other STEC sources.

The trade in live crustaceans implies keeping these animals alive after capture and/or farming until purchase by the final consumer. Regarding animal welfare, the European Union includes cephalopods in Directive 2010/63/EU on the protection of animals used for scientific purposes, but there are no further regulations on crustaceans in EU legislation. The present study analysed the provisions of Italian municipal regulations on animal welfare applicable to crustaceans. Only 62 of the 110 municipal websites of the provincial capitals reported a regulation safeguarding animal welfare. These regulations contain different rules on: aquaria characteristics (size, volume and shape); management of aquaria; maintenance (preservation and exposure) of live aquatic species; slaughtering and/or suppression of aquatic species and crustaceans; tying of crustacean claws; and crustacean cooking. The analysis on Italian municipal regulations on crustaceans' animal welfare showed that the provisions are vague, lacking uniformity and scientific guidelines.

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The slaughterhouse can act as a valid checkpoint to estimate the prevalence and the economic impact of diseases in farm animals. At present, scoring lesions is a challenging and time-consuming activity, which is carried out by veterinarians serving the slaughter chain. Over recent years, artificial intelligence(AI) has gained traction in many fields of research, including livestock production. In particular, AI-based methods appear able to solve highly repetitive tasks and to consistently analyze large amounts of data, such as those collected by veterinarians during postmortem inspection in high-throughput slaughterhouses. The present study aims to develop an AI-based method capable of recognizing and quantifying enzootic pneumonia-like lesions on digital images captured from slaughtered pigs under routine abattoir conditions. Overall, the data indicate that the AI-based method proposed herein could properly identify and score enzootic pneumonia-like lesions without interfering with the slaughter chain routine. According to European legislation, the application of such a method avoids the handling of carcasses and organs, decreasing the risk of microbial contamination, and could provide further alternatives in the field of food hygiene.