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Background Management of food safety at the international level has been moved towards a risk-based approach with regulators and food business operators (FBOs) around the world adopting the risk analysis framework. Despite the extensive use of Quantitative Microbiological Risk Assessment (QMRA) within the context of food safety, the application of such a risk-based approach for food spoilage is limited. Scope and approach The present study provides a detailed description of QMRA structure applied for assessing the risk of spoilage in foods by presenting the main principles, the methodological standards and the application scheme for a risk-based food quality management. Key findings and conclusions The output of QMRA for a quality hazard such as food spoilage can provide a transparent scientific basis to support food quality management decisions by food business operators (FBOs) while replacing empirical-based decisions. Probabilistic QMRA models for food spoilage can simulate what-if scenarios with different combinations of settings regarding product formulation, process and storage conditions, expiration dating etc. and assess their impact on the risk of spoilage. This can support the FBOs in selecting an effective expiration date (use-by or best before date), which leads to the maximum exploitation of the “true” product's shelf life, while minimizing the risk of spoilage to an acceptable (by the managers) level, in accordance to the Appropriate Level of Protection (ALOP) for food safety. Furthermore, QMRA can provide the elements for a cost-benefit analogy in relation to the identified mitigation strategies for reducing the risk of spoilage and/or extending the shelf life of foods.

Background Quantitative microbiological risk assessment (QMRA) is the most complex stage of risk analysis, an important management tool that considers the entire food production chain. Through safety limits, health authorities and producers are concerned with achieving the minimum risk to consumer health. Dairy products are a class of foods very susceptible to microbial contamination, and need an extensive database of studies in this regard. Scope and approach This review aims to provide an understanding of the structure of QMRA and its application in dairy products, taking into account the processing chains of dairy products and the influence of study factors in different regions. The limitations and factors of complexity in the construction of the QMRA models in milk and cheese pasteurized or not, are also presented. Key findings and conclusion Considerable differences were found in consumption habits between populations in different regions, significantly affecting the risk associated with infection or disease. Transport and retail conditions of the products also show a strong influence on the final risk, as well as the hygiene conditions of the milk used as raw material. Studies of this type are scarce, especially in dairy products, requiring further development of QMRA models. Risk assessment is a promising tool for verifying the effectiveness of using new processing technologies, based on the search for the lowest possible risk associated with food.

The objective of this study was to develop a quantitative microbial risk assessment (QMRA) model to evaluate potential risk mitigation strategies to reduce the probability of acquiring hemolytic uremic syndrome (HUS) associated with beef consumption in Argentina. Five scenarios were simulated to evaluate the effect of interventions on the probability of acquiring HUS from Shiga toxin-producing Escherichia coli (STEC)-contaminated ground beef and commercial hamburger consumption. These control strategies were chosen based on previous results of the sensitivity analysis of a baseline QMRA model ( Brusa et al., 2020). The application of improvement actions in abattoirs not applying Hazard Analysis and Critical Control Points (HACCP) for STEC would result 7.6 times lower in the probability that consumers acquired HUS from ground beef consumption, while the implementation of improvements in butcher shops would lead to a smaller reduction. In abattoirs applying HACCP for STEC, the risk of acquiring HUS from commercial hamburger consumption was significantly reduced. Treatment with 2% lactic acid, hot water and irradiation reduced 4.5, 3.5 and 93.1 times the risk of HUS, respectively. The most efficient interventions, in terms of case reduction, being those that are applied in the initial stages of the meat chain.

Understanding the dose-response relationship between ingested pathogenic bacteria and infection probability is a key factor for appropriate risk assessment of foodborne pathogens. The objectives of this study were to develop and validate a novel mechanistic dose-response model for Campylobacter jejuni and simulate the underlying mechanism of foodborne illness during digestion. Bacterial behavior in the human gastrointestinal environment, including survival at low pH in the gastric environment after meals, transition to intestines, and invasion to intestinal tissues, was described using a Bayesian statistical model based on the reported experimental results of each process while considering physical food types (liquid versus solid) and host age (young adult versus elderly). Combining the models in each process, the relationship between pathogen intake and the infection probability of C. jejuni was estimated and compared with reported epidemiological dose-response relationships. Taking food types and host age into account, the prediction range of the infection probability of C. jejuni successfully covered the reported dose-response relationships from actual C. jejuni outbreaks. According to sensitivity analysis of predicted infection probabilities, the host age factor and the food type factor have relatively higher relevance than other factors. Thus, the developed “key events dose-response framework” can derive novel information for quantitative microbiological risk assessment in addition to dose-response relationship. The framework is potentially applicable to other pathogens to quantify the dose-response relationship from experimental data obtained from digestion. IMPORTANCE Based on the mechanistic approach called the key events dose-response framework (KEDRF), an alternative to previous nonmechanistic approaches, the dose-response models for infection probability of C. jejuni were developed considering with age of people who ingest pathogen and food type. The developed predictive framework illustrates highly accurate prediction of dose (minimum difference 0.21 log CFU) for a certain infection probability compared with the previously reported dose-response relationship. In addition, the developed prediction procedure revealed that the dose-response relationship strongly depends on food type as well as host age. The implementation of the key events dose-response framework will mechanistically and logically reveal the dose-response relationship and provide useful information with quantitative microbiological risk assessment of C. jejuni on foods.

Fresh betel leaves (Piper betle L.), imported into the UK are a traditional ready-to-eat food consumed by Asian populations. We report here the consolidation of routinely collected data to model the public health risks from consumption of this food. Amongst 2110 samples collected at Border Inspection, wholesale, catering or retail, Salmonella was detected in 488 (23%) of samples tested between 2011 and 2017 and was the most commonly Salmonella-contaminated ready-to-eat food examined by Public Health England during this period. Using data from multiple samples (usually 5) tested per consignment sampled at Border Inspection, contamination levels were calculated by most probable number: seasonal, temporal and country specific differences were detected. Quantitative contamination data was used to estimate the levels present at retail, and a β-Poisson dose response model the probability of illness was calculated. Using data for products imported from India, the probability of acquiring infection following a single exposure (comprising of a single leaf) was estimated to be between 0.00003 (January-March) and 0.0001 (July-September). Using British Asian population data for individuals over 30 years of age in England in 2011, two estimates of consumption were modelled as 2.1 and 12.8 million servings per annum. Results from the model estimated 160 cases (range 102 to 242) and 960 cases (range 612 to 1456) per year in England for the two consumption estimates and equated to 34 (range 22 to 51) and 204 (range 130 to 310) salmonellosis cases per year reported to national surveillance. Salmonella from 475 of the contaminated samples were further characterised which showed a heterogeneous population structure with 46 S. enterica subsp. Enterica serovars, together with S. enterica subs diarizonae and salamae identified. Isolates from individual consignments were diverse and close genetic relationships between independent isolates were very rare except from within an individual consignment. There were no outbreaks detected as associated with betel leaf consumption. However analysis by whole genome sequencing of the 2014-17 data identified two cases where the clinical isolate had5 single nucleotide polymorphism differences to isolates from betel leaves which is indicative of a likely epidemiological link and common source of contamination. Due to the diversity of the Salmonella contaminating this product, associations between salmonellosis cases and betel leaf consumption will appear sporadic and unlikely to be detected by current surveillance strategies based on outbreak detection.

Anthropogenic contamination of beaches in the south of Brazil was assessed by detection of Escherichia coli, human mastadenovirus species C (HAdV-C) and F (HAdV-F) and hepatitis E virus (HEV). Sampling was carried out in October (2016), and in January, April and July (2017). Water, sediment, sea surface microlayer (SML), bivalves, and air sentinel samples were evaluated. Quantitative microbiological risk assessment (QMRA) was used to estimate the probability of swimmer infection. HAdV-C was present in 26% of the samples, for both qPCR and viral isolation. The highest rates of detection in genomic copies (GC) were in water (2.42E+10 GC/L), SML (2.08E+10 GC/L), sediment (3.82E+08 GC/g) and bivalves (3.91E+07 GC/g). QMRA estimated daily and annual risks with a maximum value (9.99E-01) in almost all of the samples. Viable HAdV-C was often detected in the SML, pointing that this is a source of infection for people bathing in these waters.

Recent developments in genome sequencing open new opportunities for explaining the intraspecific variability of phenotypes (e.g. virulence, growth behavior). Successful association between WGS-data and specific phenotypes is thought to contribute to better predicting microbial behaviors. Implementing this information in hazard identification, exposure assessment, and hazard characterization processes will refine quantitative microbial risk assessments (QMRA) models. The aim of this study was to explore the refinements in QMRA studies when considering phenogenotype associations for the hazard properties, particularly related to the growth ability at low temperature (minimal growth temperature, Tmin) and the virulence. The used QMRA-model was previously developed for the assessment of the number of listeriosis cases associated to cold-smoked salmon in France. The global prevalence in the existing model was replaced by the specific prevalence for each genotypic subgroup (clonal complex - CC) in Europe. In order to describe the variability of Listeria monocytogenes’ growth characteristics more accurately, two different distributions of Tmin were implemented. For risk characterization, three different groups of virulence were considered according to the CCs. Each group was associated with a specific dose-response model. The new QMRA model showed that CCs contributing the most in consumer exposure were not those that contributed the most to listeriosis cases. The most prevailing CCs led to few listeriosis cases, whereas uncommon high virulent strains were responsible for the majority of predicted cases. Similarly, the less prevailing group of strains with high Tmin was approximately two times less implicated when considering human listeriosis in comparison to food contamination. Considering genotypic data in QMRA opens the way for the establishment of risk based measures specific to distinct sub-groups of L. monocytogenes.

The current review highlighted the quantitative microbiological risk assessment of Vibrio parahaemolyticus in Prawn farm wastewaters (PFWWs) and the applicability of nanoparticles for eliminating antibiotic-resistant bacteria (ARB). The high availability of the antibiotics in the environment and their transmission into human through the food-chain might cause unknown health effects. The aquaculture environments are considered as a reservoir for the antibiotic resistance genes (ARGs) and contributed effectively in the increasing of ABR. The metagenomic analysis is used to explore ARGs in the non-clinical environment. V. parahaemolyticus is among the pathogenic bacteria which are transmitted through sea food causing human acute gastroenteritis due to available thermostable direct hemolysin (tdh), adhesins, TDH related hemolysin (trh). The inactivation of pathogenic bacteria using nanoparticles act by disturbing the cell membrane, interrupting the transport system, DNA and mitochondria damage, and oxidizing the cellular component by reactive oxygen species (ROS). The chloramphenicol, nitrofurans, and nitroimidazole are among the prohibited drugs in fish and fishery product. The utilization of probiotics is the most effective and safe alternative for antibiotics in Prawn aquaculture. This review will ensure public understanding among the readers on how they can decrease the risk of the antimicrobial resistance distribution in the environment.

Battered poultry products may be wrongly regarded and treated by consumers as ready-to-eat and, as such, be implicated in foodborne disease outbreaks. This study aimed at the quantitative description of the growth behavior of Listeria monocytogenes in fresh, partially cooked (non-ready-to-eat) battered chicken nuggets as function of temperature. Commercially prepared chicken breast nuggets were inoculated with L. monocytogenes and stored at different isothermal conditions (4, 8, 12, and 16 °C). The pathogen’s growth behavior was characterized via a two-step predictive modelling approach: estimation of growth kinetic parameters using a primary model, and description of the effect of temperature on the estimated maximum specific growth rate (μmax) using a secondary model. Model evaluation was undertaken using independent growth data under both constant and dynamic temperature conditions. According to the findings of this study, L. monocytogenes may proliferate in battered chicken nuggets in the course of their shelf life to levels potentially hazardous for susceptible population groups, even under well-controlled refrigerated storage conditions. Model evaluation demonstrated a satisfactory performance, where the estimated bias factor (Bf) was 0.92 and 1.08 under constant and dynamic temperature conditions, respectively, while the accuracy factor (Af) value was 1.08, in both cases. The collected data should be useful in model development and quantitative microbiological risk assessment in battered poultry products.

Understanding the dose-response relationship between ingested pathogenic bacteria and infection probability is a key factor for appropriate risk assessment of foodborne pathogens. The objectives of this study were to develop and validate a novel mechanistic dose-response model for Campylobacter jejuni and simulate the underlying mechanism of foodborne illness during digestion. Bacterial behavior in the human gastrointestinal environment, including survival at low pH in the gastric environment after meals, transition to intestines, and invasion to intestinal tissues, was described using a Bayesian statistical model based on the reported experimental results of each process while considering physical food types (liquid or solid) and host age (young adult or elderly). Combining the models in each process, the relationship between pathogen intake and the infection probability of C. jejuni was estimated and compared with reported epidemiological dose-response relationships. Taking food types and host age into account, the prediction range of the infection probability of C. jejuni successfully covered the reported dose-response relationships from actual C. jejuni outbreaks. According to sensitivity analysis of predicted infection probabilities, the host age factor and the food type factor have relatively higher relevance than other factors. Thus, the developed Key Events Dose Response Framework can derive novel information for quantitative microbiological risk assessment in addition of dose-response relationship. The developed framework is potentially applicable to other pathogens to quantify the dose-response relationship from experimental data obtained from digestion. Importance Based on the mechanistic approach called Key Events Dose Response Framework alternative to previous non-mechanistic approach, the dose-response models for infection probability of C. jejuni were developed considering with age of people who take pathogen and food type. The developed predictive framework illustrated highly accurate prediction of dose (minimum difference 0.21 log CFU) for a certain infection probability compared with the previously reported dose-response relationship. In addition, the developed prediction procedure revealed that the dose-response relationship strongly depends on food type as well as host age. The implementation of Key Event Dose Response Framework will mechanistically and logically reveal the dose-response relationship and provide useful information with quantitative microbiological risk assessment of C. jejuni on foods.

Foodborne diseases constitute a major concern in societies, and their causes are aimed to be identified and minimized. Only in the last few years, this is encouraged by the application of risk assessment, management, and communication. This work presents a probabilistic quantitative microbiological risk assessment and management of Listeria monocytogenes in ready-to-eat lettuce salads in Spain. For risk assessment, a guideline provided by Codex Alimentarius was followed. Food chain was modeled from processing of raw material at the factory up to consumption. Different assumptions were made to describe the variables of the model by probability distributions or mathematical models. Monte Carlo simulations of the model were run to estimate the number of cases in low-risk and high-risk populations. Although results deviated from the number of cases observed in Spain, given an ideal situation of 100% compliance of the microbiological criterion ≤100 cfu/g throughout the shelf-life of the product, the resulting number of cases was near the real situation. From the 4 risk management measures simulated, the injection of a mixture of gases into packages at manufacture (CO2 about 5.5%, O2 about 3%, and N2 for the balance) was the most effective in reducing the number of cases, followed by 4 d of storage at home and prevention of high-risk consumers from consumption of ready-to-eat lettuce salads. More research and cooperation between different stakeholder organizations are needed in order to progressively improve the model. With this work, a breakthrough has been made with regards to risk assessment and management procedures and implementation.

Outbreaks of waterborne diseases still are a public health problem in the 21st century, especially on developing countries, but also in developed countries. Drinking Water Treatment Plants (DWTP) are in charge of guaranteeing that tap water has a good quality (in terms of both microbiological and physicochemical aspects), so that, among other things, they minimize the risk of suffering an infectious disease. Nevertheless, perturbations during the treatment process, extreme meteorological conditions or tap water pollution during its distribution can trigger microbiological risk and can provoke epidemic outbreaks. To quantify microbiological risk QMRA (Quantitative Microbiological Risk Assessment) methodology can be applied. QMRA is a four steps methodology that explores several aspects as: type of pathogenic microorganisms, inlet water characteristics, treatment operation, epidemiological data, etc. In the present report microbiological risk of tap water treated by DWTP Ter is analyzed according to the QMRA methodology. First of all, a classification algorithm has been developed to estimate the microbiological concentration on the DWTP inlet by using different environmental conditions daily monitored. The algorithm has been developed using big volumes of data (daily data from historical series of 20 years), and for this reason it was necessary to use Data Mining tools. Finally, estimated microbiological concentrations have been used to calculate one of the most common metrics used for quantifying microbiological risk: DALY (Disability Adjusted Life Years). This metric has been calculated following the WHO’s and Microrisk’s manuals directrices. DALY has allowed to quantify the risk in a range of values and has allowed to visualize under which conditions a dangerous situation could arise. Microbiological risk calculus for tap water treated in DWTP Ter has been resulted to be low in most of the cases, but some scenarios where the risk would overcome the WHO’s limit have been detected. Special focus should be paid on these scenarios, where water treatment should be more accurate

Toxoplasma gondii (T. gondii) is a protozoan parasite with a worldwide distribution. It can infect all warm-blooded animals, and is the causative agent of toxoplasmosis. The global disease burden of toxoplasmosis is substantial and therefore considered as a public health problem worldwide. Quantitative microbial risk assessment (QMRA) is a source attribution method, which aggregates all available data on different aspects to compare the importance of different sources of infection. This thesis focuses on the assessment of relative attribution of different meat products and soil to human T. gondii infection by using QMRA models. In chapter 1, the life cycle of T. gondii, source of human infection, and different source attribution methods are described. In chapter 2, an overview of existing mathematical models to study the transmission of T. gondii and their assessments of different control strategies is described. Due to the complicated life cycle of the parasite and the absence of field data, models do not always represent reality. In chapter 3, a study estimating the seroprevalence and associated risk factors in indoor-housed Dutch dairy goats to investigate whether a biosecurity intervention would be feasible for reducing the risk of toxoplasmosis in grazing animals is presented. The estimated low seroprevalence suggested that indoor housing seems reduce the exposure of goats to T. gondii. In chapter 4, a hierarchical meta-analysis was performed to estimate the adjusted seroprevalence in pregnant women and livestock in China. These results not only provided us accurate insight on T. gondii infection status in China, but also important data in the meat-borne QMRA model. In chapter 5, the QMRA model of meat-borne T. gondii infection in the Netherlands as described previously by Opsteegh et al. (2011) was updated. The updated model found that filet americain, spiced and smoked pork sausage and leg of mutton were the top three products associated with the highest number of predicted infections. In addition, salting had a great effect on T. gondii survival but does not necessarily inactive all T. gondii. The Dutch QMRA model was implemented for China in chapter 6. It identified pork as the main source of T. gondii infection, followed by poultry, small ruminants, ducks and cattle. Results from the QMRA models clearly show that the prevalence of T. gondii infection in livestock does not necessarily present an indication for the risk of infection or the importance of the different types of meat on a population level. In chapter 7, The risk associated with T. gondii exposure via soil intake in the Netherlands was estimated and a sensitive magnetic capture qPCR method was developed. Currently the model likely overestimates the risk of infection via soil, and several data gaps were identified. We recommend to collect specific data for different population groups in the future. In chapter 8, the values and limitations of the quantitative risk assessment approach for toxoplasmosis source attribution were discussed. The findings in this thesis can aid science-based decision-making on where to target interventions, thereby, in the end, reducing the disease burden of toxoplasmosis.

We developed a quantitative microbiological risk assessment (QMRA) of haemolytic uremic syndrome (HUS) associated with Shiga toxin-producing Escherichia coli (STEC)-contaminated beef (intact beef cuts, ground beef and commercial hamburgers) in children under 15 years of age from Argentina. The QMRA was used to characterize STEC prevalence and concentration levels in each product through the Argentinean beef supply chain, including cattle primary production, cattle transport, processing and storage in the abattoir, retail and home preparation, and consumption. Median HUS probability from beef cut, ground beef and commercial hamburger consumption was

Wastewater treatment plants (WWTPs) are a nonnegligible source of bioaerosols that can pose health risks to workers and nearby residents. Thus, this study systematically investigated the emission characteristics of the size distribution and concentration of Staphylococcus aureus bioaerosol in a WWTP. Then, the research focused on the quantitative microbiological risk assessment (QMRA) of workers and nearby residents for equipping them with various grades personal protective equipment (PPE). Results showed that the peak proportion of the size distributions of bioaerosol particles in the three sources all obtained a size range between 3.3 and 4.7 μm. In the residential building, the peak proportion was larger (>7.0 μm). Referring to the three sources, the average bioaerosol concentrations were in the following sequence: inverted umbrella aerator tank > residual sludge storage yard > microporous aerator tank. The health risks of residents were generally 1–2 orders of magnitude higher than the other two exposure scenarios and were clearly beyond the benchmarks. Meanwhile, the health risks of the field engineer were usually lower than those of the staff at the residual sludge storage yard. In general, equipping workers and residents with PPE could at least decrease the health risks by one order of magnitude, and higher-grade PPE could appropriately promote the reduction of health risks. This research systematically delivered a series of novel data about the emission characteristics of Staphylococcus aureus bioaerosol in a WWTP. It advanced the understanding of the quantitative health risks of equipping individuals with various PPE.

International audience; Each year in Europe, meat is associated with 2.3 million foodborne illnesses, with a high contribution from beef meat. Many of these illnesses are attributed to pathogenic bacterial contamination and inadequate operations leading to growth and/or insufficient inactivation occurring along the whole farm-to-fork chain. To ensure consumer health, decision-making processes in food safety rely on Quantitative Microbiological Risk Assessment (QMRA) with many applications in recent decades. The present study aims to conduct a critical analysis of beef QMRAs and to identify future challenges. A systematic approach, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was used to collate beef QMRA models, identify steps of the farm-to-fork chain considered, and analyze inputs and outputs included as well as modelling methods. A total of 2343 articles were collected and 67 were selected. These studies focused mainly on western countries and considered Escherichia coli (EHEC) and Salmonella spp. pathogens. Future challenges were identified and included the need of whole-chain assessments, centralization of data collection processes, and improvement of model interoperability through harmonization. The present analysis can serve as a source of data and information to inform QMRA framework for beef meat and will help the scientific community and food safety authorities to identify specific monitoring and research needs.

Modeling has become an important and efficient tool to predict microbial behavior in food safety and engineering. Foodborne pathogen infections, leading to foodborne illnesses and significant economic losses, are closely associated with public human health. Therefore, various mathematical models have been developed for food safety management, identifying critical control points, evaluating reformulations, and education in food engineering. These models can predict the microbial growth or response in different environments including temperature, moisture, pH, and concentration of preservatives in simulated or actual food systems. In this chapter, the most widely used traditional and novel food microbial predictive models are classified into primary, secondary, and tertiary models. They are introduced specifically for better understanding the theory, function, and systematical applications, as well as the origin, development process, state-of-the-art and the prospects of each model. In addition, the four specific growth models, i.e. Baranyi and Roberts model, square root model, response surface methodology, and artificial neural networks, as well as the software for Integrated Pathogen Modelling Program (IPMP 2013), are described in detail with an emphasis on the basic assumptions, limitations, and possible enhancements. The predictive models have commanded a bigger slice of the food safety engineering, such as in HACCP (Hazard Analysis Critical Control Point) and QMRA (Quantitative Microbiological Risk Assessment) programs with their increasing robustness and improving capabilities.

Urban Water Supply (UWS) is one of the most critical and sensitive systems to sustain overall city operations. The European Union (EU) has strict water quality regulations that currently depend on periodic laboratory tests of selected parameters in most of the cases. The tests of some biological parameters can take up to 48 hours, which leads to the delay of risk detection and lengthens the response time for taking countermeasures in UWS. This situation increases the risk of negative impacts to the health of mass population. To address this challenge, we propose a data-driven risk analysis method which is low-cost and efficient. First, we build a framework for risk evaluation and prediction, within which a risk evaluation model is introduced considering the Quantitative Microbiological Risk Assessment (QMRA) process suggested by the World Health Organization (WHO). Second, we present a collaborative method to analyze biological risk features and similarities across different locations. Third, we propose a new risk prediction algorithm. We apply this method on the real-world data collected from 4 UWS systems in Norway. The preliminary results are depicted in risk maps and prediction accuracies are compared with different strategies. The application results show that our method is practical with good accuracy and explainability.

Street sold foods have gained popularity in recent times, particularly in developing countries where their sale is often unregulated, hence, has a potential to transmitting pathogenic microorganisms which are of public health concern. A survey of two street foods, kachumbari (a type of a vegetable salad) and mandazi (a type of a wheat-based flour snack) was carried out in a Kenyan town to determine the prevalence and conduct a quantitative microbiological risk assessment to estimate the risks of infection due to consumption of the two products contaminated with Salmonella. A prevalence of 19% (16 out of 86 samples) and 7% (6 out of 86 samples) was observed for kachumbari and mandazi respectively. A risk assessment model composed of three different steps (nodes) comprising finished product (processed ready-to-eat), waiting (storage) period and consumption was used for the microbiological risk assessment. Models built in excel spreadsheets using @Risk software package, version 6 (Palisade USA) was used to obtain the inputs, outputs, and run the Monte Carlo simulations at 5000 iterations. The model estimated that in 95% of the cases, the consumers of kachumbari would be exposed to a maximum dose of 8.30 x 104 Salmonella cells per single serving. On the other hand, in 95% of the cases, consumers of mandazi would be exposed to a maximum dose of 4.0 x 104 Salmonella cells per single serving. The model also predicted that 64.3% and 69% of the population was at risk of developing salmonellosis upon consumption of contaminated kachumbari and mandazi respectively. The results indicate that these two products can contribute to high levels of salmonellosis morbidity. Nevertheless, a significant reduction in the level of ingested Salmonella cells in kachumbari and mandazi could be attained through a reduction of the prevalence of the pathogen contamination at or before the point of sale by the employment of good hygienic practices during their preparation and subsequent handling, in addition to enforcement of food hygiene regulations regarding street foods to ensure microbiologically safe foods are sold to the consumers. In order to improve the accuracy of this risk assessment model, more data, whenever available should be used in such studies.

Both in Europe and worldwide cheese has caused important outbreaks of listeriosis and can be a vehicle for transmission of Listeria monocytogenes to consumers. A systematic review and meta-analysis were conducted using scientific literature and European Food Safety Authority (EFSA) reports to summarize available data on the prevalence of L. monocytogenes in different types of cheeses produced in Europe. Meta-analysis models were used to estimate mean prevalence of the pathogen and to compare prevalence among types of cheeses (fresh, ripened, veined, smear and brined) and cheeses produced using, respectively, pasteurized or un-pasteurized milk. Data from a total of 130,604 samples were analysed. Mean prevalence for presence during 2005–2015 estimated from scientific literature (2.3% with confidence interval (CI): 1.4–3.8%) was more than three times higher than results from EFSA reports (0.7%; CI: 0.5–1.1%). The prevalence differed among types of cheeses including fresh (0.8%; CI: 0.3–1.9%), ripened (2.0%; CI: 0.8–4.9%), veined (2.4%; CI: 0.9–6.3%), smear (5.1%; CI: 1.9–13.1%) and brined (11.8%; CI: 3.5–33.3%). Mean prevalence of L. monocytogenes in soft/semi-soft cheeses were not significantly different (P > 0.05) for cheeses produced from pasteurized (0.9%; CI: 0.4–1.9%) or un-pasteurized (1.0%; CI: 0.4–2.2%) milk. For cheese samples reported by EFSA 0.2% CI: 0.1–0.4% had concentration of L. monocytogenes above the critical European limits of 100 cfu/g. In addition, this systematic review focused on groups/species of microorganisms suitable as indicator organisms for L. monocytogenes in cheeses to reflect the level of production hygiene or as index organisms to assess the prevalence of L. monocytogenes in cheeses. However, no suitable indicator or index organisms were identified. The performed meta-analyses improved our understanding of L. monocytogenes prevalence in different types of cheeses and provided results that can be useful as input for quantitative microbiological risk assessment modelling.

In this study, a full cycle of agricultural reuse of agro-food wastewater (synthetic fresh-cut wastewater, SFCWW) at pilot plant scale has been investigated. Treated SFCWW by ozonation and two solar processes (H2O2/solar, Fe3+-EDDHA/H2O2/solar) was used to irrigate two raw-eaten crops (lettuce and radish) grown in peat. Two foodborne pathogens (E. coli O157:H7 and Salmonella enteritidis) and five organic microcontaminants (OMCs: atrazine, azoxystrobin, buprofezin, procymidone and terbutryn) were monitored along the whole process. The three studied processes showed a high treatment capability (reaching microbial loads 90 % for solar treated and ozonated SFCWW, respectively) and bioaccumulation in both crops in comparison with the results obtained with untreated SFCWW. Moreover, the chlorophyll content in the harvested lettuces irrigated with SFCWW treated by Fe3+-EDDHA/H2O2/solar was twice than that irrigated with SFCWW treated by H2O2/solar and ozone, indicating the additional advantage of using Fe3+-EDDHA as an iron source to reduce the risk of iron chlorosis in crops. Finally, the chemical (dietary risk assessment for the combined exposure of the 5 OMCs) and quantitative microbiological risk assessment (QMRA) of the harvested crops showed the capability of the studied processes to reduce the risk associated with untreated SFCWW reuse by more than 50 % and more than 4 orders of magnitude, respectively.

Considerable attention has been recently given to possible transmission of SARS-CoV-2 via water media. This review addresses this issue and examines the fate of coronaviruses (CoVs) in water systems, with particular attention to the recently available information on the novel SARS-CoV-2. The methods for the determination of viable virus particles and quantification of CoVs and, in particular, of SARS-CoV-2 in water and wastewater are discussed with particular regard to the methods of concentration and to the emerging methods of detection. The analysis of the environmental stability of CoVs, with particular regard of SARS-CoV-2, and the efficacy of the disinfection methods are extensively reviewed as well. This information provides a broad view of the state-of-the-art for researchers involved in the investigation of CoVs in aquatic systems, and poses the basis for further analyses and discussions on the risk associated to the presence of SARS-CoV-2 in water media. The examined data indicates that detection of the virus in wastewater and natural water bodies provides a potentially powerful tool for quantitative microbiological risk assessment (QMRA) and for wastewater-based epidemiology (WBE) for the evaluation of the level of circulation of the virus in a population. Assays of the viable virions in water media provide information on the integrity, capability of replication (in suitable host species) and on the potential infectivity. Challenges and critical issues relevant to the detection of coronaviruses in different water matrixes with both direct and surrogate methods as well as in the implementation of epidemiological tools are presented and critically discussed., Graphical Abstract ga1

The risk of acquiring listeriosis from consuming fermented sausages and dry-cured pork shoulder (capicola/bondiola) in Argentina was estimated using quantitative microbiological risk assessment. The model included data about initial prevalence and contamination level of Listeria monocytogenes, product formulation with or without a starter culture (lactic acid bacteria [LAB]), time and temperature during distribution and storage prior to consumption, and consumption patterns. The probability of listeriosis from fermented sausage consumption in at-risk populations was estimated with average values of

A quantitative microbiological risk assessment model was used to quantify the risk of salmonellosis caused by bacterial growth and cross-contamination of chicken meals prepared in households of China. Chinese data on initial loads of Salmonella in chicken carcasses sold at retail, storage time and handling of raw chicken meat in household kitchens and confirmatory transfer rates of Salmonella among different kitchen objects were collected. Only one third of Chinese families in our sample separated the cutting board between raw and ready-to-eat foods. The cross-contamination of ready-to-eat foods from chicken meals via the cutting board, the knife and cooks’ hands increased the frequency of pathogen ingestion and the risk of salmonellosis. A significant decrease in the risk of salmonellosis could be achieved by reducing the cross-contamination when handling raw chicken meat and ready-to-eat foods. Decreasing the prevalence of Salmonella contamination to 8.8% or removing chicken carcasses with contamination densities higher than 100 MPN/100 g at retail was less effective. Using transfer rates of Salmonella from raw chicken meat to the wooden cutting board instead of that from references, a statistically higher risk of salmonellosis per serve due to the cross-contamination in households was observed. The present study validated values of hygiene practices in China to reduce the risk of salmonellosis from contaminated raw chicken meat at retail. Deliberate surveys for cooking behaviors and transfer rates of Salmonella from and to different objects including wooden cutting boards were needed.

Dry fermented sausage (salami) is a very popular ready-to-eat product in Southern Brazil, of which the raw materials can be contaminated with pathogens such as Salmonella. This product can put consumers at risk if a failure occurs during the manufacturing process. To investigate this risk, a quantitative microbiological risk assessment was performed. The objective was to assess the impact of Salmonella inactivation during the process of fermenting and drying and the distribution of the bacteria in minced pork used in Italian-Style salami on the consumer health risk, using a modular process risk model (MPRM) approach. A total of 405 scenarios were tested combining five scenarios for sausage fermentation, three maturation times (12, 15, and 24 days), nine scenarios for prevalence and concentrations of Salmonella on pork carcasses, and three scenarios for clustering of cells (homogeneous and heterogeneous). In general, it was observed that the mean exposure to Salmonella due to ingestion of a portion of contaminated salami was very low; “zero risks” (with no cases of salmonellosis among 100,000 consumed portions of salami) were found in 65% of the scenarios (265/405) assessed and low risks were found in the other 35% of the scenarios (140/405). Low risks were observed in all scenarios that included 24 days of maturation (0 to 9.8 × 10−9; n = 135 scenarios) or ≥2.2 log reduction at any stage of the process (0 to 3 × 10−9; n = 189 scenarios). According to the model, 134 of the 135 scenarios presenting log reduction greater than 3.3 during maturation reduced the mean risk to zero. The most important variables, increasing the risk, were lack of fermentation, short maturation period (12 days), and high concentration of Salmonella on the carcass. On the contrary, a negative association (indicating a decreased risk) was observed when 24 days of maturation is applied and or with good fermentation process. If a realistic heterogeneous distribution of bacteria over the sausages is assumed instead of homogeneous distribution, the estimated risk is larger. Although in general the mean risks found here were low, selling dry fermented sausage before complete maturation of the product and failure in fermentation can pose a risk to the consumers from the studied region. It was found that a maturation period of 24 days can be considered safe, even in a situation with high initial levels of contamination.