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A model describing Listeria innocua evolution according to process parameters of 51 Italian salami processes and HPP in 31 companies was developed. A total of 51 challenge tests were performed. During processing a L. innocua reduction of 0.34-4.32 Log10 CFU/g was observed and HPP further reduced the count of 0.48-3.47 Log10 CFU/g; an overall reduction of 1.04-5.68 is reached. PH after acidification/drying process, a w after seasoning, duration of the seasoning and caliber resulted associated (p < 0.05) with L. innocua decrease. HPP efficacy was associated (p < 0.05) with a w and pH of the product: higher the pH and a w after the acidification/drying and seasoning phases, higher resulted the L. innocua reduction after HPP. No significant association was observed between L.innocua and salt, nitrate and starter content and other characteristics of process. The model meets companies and Authorities needs and represents a useful tool to predict L. monocytogenes lethality, giving recommendations to food business operators interested in exportation to the U.S., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

This study involved ten enterprises producing Italian salami, 20 different samples of fermented sausages underwent challenge tests to assess and record the following parameters: time, temperature, pH, a w , and Salmonella counts. A linear regression model was used to describe the Salmonella spp. decay: at the end of the process the result of total Salmonella reduction was 0.97-5.84 Log 10 CFU/g and it was significantly associated with pH at the end of acidification/drying process, a w at the end of seasoning period, the duration of seasoning, and the caliber of salami respectively. High Pressure Processing (HPP) further reduced the Salmonella level by 2.41-5.84 Log 10 CFU/g with an efficacy that resulted inversely associated with a w of salami at the end of seasoning; the objective of 5-Log reduction was always reached in all the cases tested by the production process plus HPP. This model could be a useful tool for enterprises and Authorities to evaluate the efficacy of the processes to reduce Salmonella load for exportation to the U.S., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Quantitative microbial risk assessment (QMRA) models are extensively applied to inform management of a broad range of food safety risks. Inevitably, QMRA modeling involves an element of simplification of the biological process of interest. Two features that are frequently simplified or disregarded are the pathogenicity of multiple strains of a single pathogen and consumer behavior at the household level. In this study, we developed a QMRA model with a multiple-strain approach and a consumer phase module (CPM) based on uncertainty distributions fitted from field data. We modeled exposure to staphylococcal enterotoxin A in raw milk in Lombardy; a specific enterotoxin production module was thus included. The model is adaptable and could be used to assess the risk related to other pathogens in raw milk as well as other staphylococcal enterotoxins. The multiplestrain approach, implemented as a multinomial process, allowed the inclusion of variability and uncertainty with regard to pathogenicity at the bacterial level. Data from 301 questionnaires submitted to raw milk consumers were used to obtain uncertainty distributions for the CPM. The distributions were modeled to be easily updatable with further data or evidence. The sources of uncertainty due to the multiple-strain approach and the CPM were identified, and their impact on the output was assessed by comparing specific scenarios to the baseline. When the distributions reflecting the uncertainty in consumer behavior were fixed to the 95th percentile, the risk of exposure increased up to 160 times. This reflects the importance of taking into consideration the diversity of consumers' habits at the household level and the impact that the lack of knowledge about variables in the CPM can have on the final QMRA estimates. The multiple-strain approach lends itself to use in other food matrices besides raw milk and allows the model to better capture the complexity of the real world and to be capable of geographical specificity.

Two quantitative risk assessment (RA) models were developed to describe the risk of salmonellosis and listeriosis linked to consumption of raw milk sold in vending machines in Italy. Exposure assessment considered the official microbiological records monitoring raw milk samples from vending machines performed by the regional veterinary authorities from 2008 to 2011, microbial growth during storage, destruction experiments, consumption frequency of raw milk, serving size, and consumption preference. Two separate RA models were developed: one for the consumption of boiled milk and the other for the consumption of raw milk. The RA models predicted no human listeriosis cases per year either in the best or worst storage conditions and with or without boiling raw milk, whereas the annual estimated cases of salmonellosis depend on the dose-response relationships used in the model, the milk storage conditions, and consumer behavior in relation to boiling raw milk or not. For example, the estimated salmonellosis cases ranged from no expected cases, assuming that the entire population boiled milk before consumption, to a maximum of 980,128 cases, assuming that the entire population drank raw milk without boiling, in the worst milk storage conditions, and with the lowest dose-response model. The findings of this study clearly show how consumer behavior could affect the probability and number of salmonellosis cases and in general, the risk of illness. Hence, the proposed RA models emphasize yet again that boiling milk before drinking is a simple yet effective tool to protect consumers against the risk of illness inherent in the consumption of raw milk. The models may also offer risk managers a useful tool to identify or implement appropriate measures to control the risk of acquiring foodborne pathogens. Quantification of the risks associated with raw milk consumption is necessary from a public health perspective.

Prevalence data were collected from official microbiological records monitoring four selected foodborne pathogens (Salmonella, Listeria monocytogenes, Escherichia coli O157:H7, and Campylobacter jejuni) in raw milk sold by self-service vending machines in seven Italian regions (60,907 samples from 1,239 vending machines) from 2008 to 2011. Data from samples analyzed by both culture-based and real-time PCR methods were collected in one region. One hundred raw milk consumers in four regions were interviewed while purchasing raw milk from vending machines. One hundred seventy-eight of 60,907 samples were positive for one of the four foodborne pathogens investigated: 18 samples were positive for Salmonella, 83 for L. monocytogenes, 24 for E. coli O157:H7, and 53 for C. jejuni in the seven regions investigated. No significant differences in prevalence were found among regions, but a significant increase in C. jejuni prevalence was observed over the years of the study. A comparison of the two analysis methods revealed that real-time PCR was 2.71 to 9.40 times more sensitive than the culture-based method. Data on consumer habits revealed that some behaviors may enhance the risk of infection linked to raw milk consumption: 37% of consumers did not boil milk before consumption, 93% never used an insulated bag to transport raw milk home, and raw milk was consumed by children younger than 5 years of age. These results emphasize that end-product controls alone are not sufficient to guarantee an adequate level of consumer protection. The beta distribution of positive samples in this study and the data on raw milk consumer habits will be useful for the development of a national quantitative risk assessment of Salmonella, L. monocytogenes, E. coli O157, and C. jejuni infection associated with raw milk consumption.

All dairy farms authorized to produce and sell raw milk in a province of Northern Italy were investigated to determine the presence of Campylobacter spp., verocytotoxin-producing Escherichia coli (VTEC), Listeria monocytogenes, and Salmonella spp. in in-line milk filters and to assess their association with suspected risk factors on farms. A logistic regression model was used to analyze data collected describing the characteristics and management practices of 27 farms and the microbiological status of 378 in-line milk filters by both culture-based and molecular methods. Thermotolerant Campylobacter, VTEC, and L. monocytogenes were detected in 24 (6.45%), 32 (8.4%), and 2 (0.5%) samples, respectively. No Salmonella spp. were detected. For risk analysis, data of L. monocytogenes and Salmonella spp. were not included in the model because of the low prevalence or absence of these organisms. The univariate analysis disclosed that the presence of VTEC and/or Campylobacter spp. in milk filters was associated with lack of cleanliness of bedding, water trough, and feed trough; nonevaluation of water hardness; lack of cleanliness of milk tank; and nonapplication of forestripping. After multivariate analysis, an association was observed with inadequate cleanliness of bedding and milk tank and the nonapplication of forestripping. PCR analysis of milk filters was a rapid and sensitive method for the microbiological evaluation of herd contamination status and should be included among the registration requirements for the authorization to produce and sell raw milk. Specific control actions must be incorporated into the farmer's daily practices to ensure the low-risk production of raw milk.