ABSTRACT

Foodborne diseases remain a global public health challenge worldwide. The European surveillance system of multistate foodborne outbreaks integrates elements from public and animal health and the food chain for early detection, assessment, and control. This review includes descriptions of the significant outbreaks that occurred in Europe in the last decade. Their significance and relevance to public health is derived from the changes, improvements, and novelties that pushed toward building a safer food system in the European Union, certainly driven by the One Health approach. In 2011, a point source monoclonal outbreak of infections caused by Escherichia coli serotype O104:H4 in sprouted seeds resulted in hundreds of cases of hemolytic uremic syndrome and several fatalities. In 2015, a prolonged outbreak of Listeria monocytogenes infections caused by contamination of frozen corn in Europe resulted in 47 cases and nine deaths. In 2016, a persistent polyclonal outbreak of Salmonella Enteritidis was linked to the consumption of eggs and was associated with hundreds of cases. The outbreak evaluations highlight the importance of rapid sharing of data (e.g., sequencing and tracing data) and the need for harmonizing bioinformatics outputs and computational approaches to facilitate detection and investigation of foodborne illnesses. These outbreaks led to development of a legal framework for a European collaboration platform for sharing whole genome sequence data and enabled the enforcement of existing hygiene and food safety provisions and the development of new hygiene guidelines and best practices. This review also briefly touches on the new trends in information technologies that are being explored for food traceability and safety. These technologies could enhance the traceability of food throughout the supply chain and redirect the conventional tracing system toward a digitized supply chain.

HIGHLIGHTS
  • Multistate outbreak investigations led to building a One Health–based food system.

  • Real-time data generation and sharing is crucial during food safety emergencies.

  • Standardization of bioinformatic pipelines is needed for comparability of investigation results.

  • Application of information technologies to food traceability is gaining momentum.

Worldwide, unsafe food causes an annual 600 million cases of foodborne illnesses and 420,000 deaths, and 40% of these deaths occur among children younger than 5 years of age (82). In 2019, 27 European Union (EU) member states reported 5,175 foodborne outbreaks, with 49,463 cases of illnesses, 3,859 hospitalizations, and 60 deaths. The number of deaths increased with respect to the previous year. Domestic and public settings such as restaurants, cafés, pubs, bars, hotels, and catering services were where most individuals were exposed to the contaminated food. Salmonella was the most commonly identified agent, accounting for 17.9% of the total outbreaks, and Salmonella Enteritidis was the predominant serovar reported. The number of outbreaks associated with Listeria monocytogenes infection has continuously increased over the last 4 years in EU. Salmonella in eggs and egg products and in mixed foods and norovirus in fish and fishery products are the top three agent-food pairs that caused the highest number of illness (45).

Foodborne diseases remain a global public health challenge with a significant burden (82). Two of the contributing factors are the increased susceptibility of the general population (e.g., elderly or immunocompromised people), leading to more severe illness outcomes, and the increased spread of antibiotic resistance, as observed recently in human and animal isolates of Salmonella and Campylobacter (44). Another important factor is the globalization of food supply chains, which lead to large-scale distribution of food items and the potential for spread of pathogens. The movements of people, new consumption habits, and changes in the virulence of known pathogens also play significant roles in foodborne illnesses (80). To meet these challenges, collaboration is required across multiple sectors with joint efforts to prevent foodborne diseases and build stronger food safety systems.

This review was conducted to describe the major multistate foodborne outbreaks that occurred in Europe in the last decade and that resulted in substantial changes, improvements, and novel approaches, pushing toward strengthening European food safety systems based on the One Health approach. This review also briefly touches upon the new trends in technologies that are being explored in the field of food traceability and safety.

The European monitoring system for foodborne diseases and zoonoses from animals, food, and feed relies on the annual collection of information (19) from EU member states. The European Commission has directed the European Food Safety Authority (EFSA) and the European Centre for Disease Control and Prevention (ECDC) to collect and analyze data from EU member states. Annually, these data sets are jointly published in the One Health zoonoses report (45).

Across Europe, the flow of information on hazards to public health detected in food is ensured by the 40-year Rapid Alert System for Food and Feed (RASFF) established by the European Commission, an official system for sharing information on hazards found in food and feed traded across Europe and for tracing food back and forward. This tool guarantees the exchange of information and coordination among the food authorities when control measures are needed or when specific foods are identified as causes of national outbreaks (32). In 2019, the EU member states produced 40 RASFF notifications on food poisoning events (foodborne outbreaks). The probable causative agent was Salmonella in 14 events, L. monocytogenes in 11 events, and noroviruses in 7 events (32).

Another operational tool is the Early Warning and Response System (EWRS) of the European Commission, where the public health authorities report certain communicable diseases, including foodborne diseases, to the European community. This network of authorities is responsible for determining the measures required to control communicable disease–related events (23). The Epi-Pulse (previously known as EPIS, Epidemic Intelligence Information System) platform hosted by ECDC is a communication and coordination platform where public health authorities exchange information about emerging clusters, outbreaks, and unusual increases of cases to facilitate the early detection of foodborne cases and outbreaks and their reporting under Decision 1082/2013/EU (23).

The majority of the multistate outbreaks are recognized when national epidemiological investigations point to a possible contaminated food that was traded across Europe. The public health authorities launch an alert in the EWRS and exchange information on the type of disease and number of human cases in the Epi-Pulse. The food authorities in the EU member states make available in the RASFF tracing data related to the suspected contaminated food. The EFSA and ECDC evaluate and combine the data shared by national food and public health authorities to monitor whether national incidents evolve into multistate outbreaks.

The EFSA is mandated by the European Commission to collaborate with the ECDC on the assessment of these multistate outbreaks and to produce a technical report, “Rapid Outbreak Assessment (ROA) on Multi-Country Foodborne Outbreak” (EFSA mandate M-2013-0119). Only the multistate food poisoning events that are considered relevant by either the ECDC or the European Commission trigger the production of an ROA. The ROA can support risk managers and policymakers in the EU (officials of the European Commission and EU member states) for implementation of interventions along the food chain to prevent new cases of infection and stop the outbreak.

Between May and July 2011, a point source outbreak of infections caused by a rare genotype of enterohemorrhagic E. coli (EHEC) O104:H4 contaminating sprouted seeds occurred in Europe, with clusters of cases in Germany and France. This outbreak of EHEC infections, unusual in its magnitude and gender and age distribution, was the largest ever recorded in Europe and worldwide (13, 14, 71). Overall, 855 cases of hemolytic uremic syndrome (HUS) and 2,987 case of bloody diarrhea, including 53 fatalities, were reported in Germany (71). A total of 24 cases, 7 of which developed into HUS, were reported in France (50, 60). Outbreak-related cases were also recorded in other European countries, Canada, and the United States (5, 12, 21, 81).

In Germany, the majority of affected individuals in this outbreak were adults, in contrast with the cases in small children recorded the year before, and more of the illnesses occurred in females than in males (71). A unique feature was the estimated median incubation period of 8 days, longer than the 3 to 4 days reported for the Shiga toxin–producing E. coli (STEC) O157:H7 (49).

The causative agent of the infections was quickly characterized via whole genome sequencing (WGS) and had uncommon virulence due to a combination of virulence genes typical of enteroaggregative E. coli (genes attA, aggR, aap, aggA, and aggC, located on a virulence plasmid) and STEC (stx2a gene) (49, 72, 73). The other typical STEC genes (stx1, eae, and ehx) were missing. The outbreak strain was resistant to beta-lactam antibiotics and third-generation cephalosporins and partially resistant to fluoroquinolones (nalidixic acid). The strain carried the plasmidborne blaCTX-M-15 and a blaTEM-1 genes (49).

Upon identification of the national outbreak, the public health authority in Germany launched an alert via the EWRS to report a significant increase in the number of patients with HUS and bloody diarrhea. Epidemiological investigations into the cause of the outbreak were initiated. In the early stage, epidemiological studies indicated that raw fresh vegetables (cucumbers, tomatoes, and lettuce) were possible vehicles of the infections. Later, the task force in Germany redirected the investigations toward a type of sprouts originating from a horticultural farm and toward sprouts that two affected individuals had grown themselves. Fenugreek and lentil seeds were the common denominator among the majority of the cases (71). Control measures were implemented, the public was warned about the consumption of these sprouts, and the ban on cucumbers, tomatoes, and lettuce was lifted (11). Recalls and withdrawal of sprouts resulted in a decline of E. coli O104:H4 infections and led to the end of the outbreak in July 2011.

Simultaneously, the EFSA was urgently tasked by the European Commission to coordinate a comprehensive traceback and traceforward exercise to identify the source of the outbreaks to determine whether the origin of the suspected sprouted seeds in the German cluster was linked to the French cluster (34). An EFSA task force was set up, and experts from the EFSA, the European Commission, relevant EU member states, the ECDC, the World Health Organization, and the Food and Agriculture Organization of the United Nations joined. Traceback and traceforward data were exchanged through the RASFF, allowing the EU member states and European institutions to receive up-to-date information. A batch of fenugreek seeds imported from Egypt was identified as the most likely common link between the French and German clusters. The batch likely became contaminated before being imported into Europe (34). Consumers were warned about the consumption of sprouts and were especially advised not to grow sprouts for their own consumption and not to eat sprouts and sprouted seeds unless thoroughly cooked (13).

Examination of the European historical data on STEC in animals and food (including sprouts) and the data on the foodborne outbreaks caused by STEC revealed that E. coli O104:H4 was very rare in Europe and had never been reported in animals and food at the time of the outbreak (14). Exposure assessments were also performed to urgently alert the public on the STEC threats associated with the consumption of fresh vegetables. Possible preharvest and postharvest hygiene and control options to mitigate the risk of contamination with this pathogen also were assessed (35). Prevention of seed contamination was regarded as of particular importance given the long-term survival of bacteria on seeds and the exponential growth of these bacteria during the germination and sprouting process (temperature and humidity conditions favorable for growth) (33).

This outbreak also raised concerns about the genomic plasticity of STEC and the unpredictable emergence of new pathogenic strains. The outbreak investigation revealed the difficulty of predicting the emergence of new pathogenic strains by screening for only the intimin (eae) variant gene or Stx toxin subtype or by focusing on the serogroup. No single or combination of gene markers fully define a pathogenic strain. The seropathotype classification (58) available at that time was based only on the reported frequency of STEC in human disease, on the association with outbreaks, and on the severity of the outcomes of HUS and hemorrhagic colitis (36). This molecular approach was reconsidered and revised, and all STEC strains are now considered pathogenic and capable of causing severe illnesses (39).

The sprouted seeds outbreak highlighted the importance of and the need for coordination between the two existing surveillance platforms, creating linkages between the alerts launched in EWRS and the tracing data provided through RASFF notifications (21). This outbreak also set the stage for closer collaboration between the independent agencies of the European Commission, in particular the EFSA and the ECDC, to provide national health authorities with a risk assessment of the severity of public health threats and measures (23). In the years following 2011, this collaboration evolved into the joint technical report known as the ROA.

In the field of outbreak preparedness, in 2012 the Standing Committee on the Food Chain and Animal Health endorsed a vision paper on the development of databases for molecular testing of foodborne pathogens (22). The European Commission directed its agencies to support the development of a common repository, the joint ECDC-EFSA molecular typing database, in which molecular typing data from pulsed-field gel electrophoresis (PFGE) and multiple-loci variable-number tandem repeat analysis (MLVA) of the major pathogenic agents (Salmonella, L. monocytogenes, and STEC) detected in humans, animals, food, feed, and food-feed environment could be stored to enable early detection of cross-border outbreaks and promote understanding of the epidemiology of these pathogens (70). This database set the stage for the upcoming One Health WGS system aimed at the collection and joint analysis of WGS data from foodborne isolates from human, food, feed, animal, and environmental samples (EFSA mandate M-2020-0015).

The STEC O104:H4 infection outbreak was also the first crowdsourcing effort for genomic characterization of a pathogen during a foodborne outbreak, indicating that real-time sharing of genomic data was possible and beneficial (72). The outbreak associated with sprouted seeds caused losses for fruit and vegetable farmers of about 812 million in the first 2 weeks. The most directly affected vegetables were tomatoes, cucumbers, lettuces, endives, zucchinis, and sweet peppers. Consumers had refrained from buying these vegetables in the beginning of the outbreak because of the uncertainty surrounding the source and recommendations not to consume these products raw. In July of the same year, media campaigns were also launched in all EU member states, and more attention was paid to communication issues as an integral part of the European response to a crisis (21).

This food safety crisis generated a set of specific rules for the sprout sector and new pieces of legislation to enforce the existing hygiene provisions for food of nonanimal origin (and its primary production). The regulatory measures included the approval of the establishments producing sprouted seeds (26), specific traceability requirements (24), and specific certification requirements for importation into the EU (27, 28). This food category also was added to the set of microbiological criteria in European legislation. Therefore, according to the food safety microbiological criteria, sprouted seeds and sprouts sold during their shelf life should not contain Salmonella (25) or STEC (including O104:H4) (20). The importance of adequate hygiene for prevention of contamination in sprouts (which are regarded as ready-to-eat [RTE]) was also strengthened by nonbinding guidance developed for the food business operators by some EU stakeholder organizations (e.g., the European Sprouted Seeds Association) (47) and other organizations (51).

Between 2015 and 2018, a prolonged multistate outbreak of infections caused by L. monocytogenes affected five countries in Europe (Austria, Denmark, Finland, Sweden, and the United Kingdom). The outbreak investigation included use of WGS. Overall, 47 cases of listeriosis caused by isolates with the same genetic cluster and identified through core genome multilocus sequence typing (cgMLST) were recorded, with nine subsequent deaths. The L. monocytogenes isolates were characterized as serogroup IVb, sequence type (ST) 6. The multistate outbreak investigation was triggered by the national investigation started in 2017 by public authorities in Finland, and other countries were warned through the EWRS. In response, Austria, Denmark, Sweden, and the United Kingdom started WGS of their available human L. monocytogenes IVb ST6 isolates to identify those genetically closely related to the Finnish isolates. An international outbreak investigation team was convened, and a European case definition was set up. In each of the five countries, patients were interviewed through national questionnaires about their food habits to gather information about possible causes of infections.

Listeria food isolates matching the outbreak strains were identified via WGS through the interaction of the EU Reference Laboratory for L. monocytogenes with its network. This process required several weeks. In France, one isolate was recovered from an environmental surface sample collected in 2017 at a food processing plant manufacturing frozen vegetables. In Austria, two food isolates from samples of two frozen mixed vegetable products (from 2016 and 2017) were also recovered; these two food products had frozen corn as a common ingredient. When the frozen corn became a suspected vehicle, officials began specifically asking patients to recall possible consumption of corn in the weeks before falling ill. One patient in Sweden recalled consumed corn, and one patient in Denmark often ate frozen mixed vegetables, possibly including corn. Only the patient in Finland referred to consumption of a specific brand of corn.

Food authorities initiated national investigations simultaneously. In Finland (early 2018), an isolate of L. monocytogenes IVb ST6 was identified in routine samples of frozen corn from a food business. These sampled batches belonged to the same brand of corn previously mentioned by the Finnish patient (in 2017). The traceback investigations of the corn batches implicated a company based in Hungary. The company was further inspected by officials, and samples were collected at the freezing plant (i.e., blanched and frozen vegetables after the freezing step). Analysis of the vegetable samples and an environmental sample revealed the presence of the outbreak strain. Meanwhile, other frozen vegetables traceable back to the same Hungarian food business were sampled in other countries (Austria, Belgium, Finland, France, Poland, and Sweden), and 25 L. monocytogenes food isolates matching the outbreak strain were recovered. The microbiological clustering analysis of the 47 clinical isolates and the 25 product or production environment isolates was performed by cgMLST with the Moura scheme (65). All L. monocytogenes isolates were within six cg allelic differences and within four or five cg allelic differences from the representative outbreak strain, indicating their close genetic relatedness.

In early 2019, the outbreak was considered over, and the high levels of news media coverage slowly ceased. With the source controlled and the corrective measures implemented (i.e., interruption of production), the number of reported illnesses decreased.

In this outbreak, data from WGS contributed largely to generation of hypotheses and the conduct of epidemiological investigations. The clustering analysis led to the hypothesis that the frozen corn was the vehicle of the infections and that the freezing plant in Hungary was the source. The coupling of the clustering analysis with the food exposure information provided proof of an epidemiological association between at least the Finnish case (in 2017) and the specific food item (brand of frozen corn). Epidemiological linking became more difficult for the cases in the other countries because of the delay in release of data (due to tracing gaps and delays in interviews). WGS techniques were already in use as the first analytical choice in some countries. Following this food incident, WGS techniques began to be routinely used in support of the multistate outbreak investigations in Europe (16, 17, 42, 43).

The outbreak associated with frozen corn prompted a revaluation of the efforts to identify points of contamination and more general efforts to reduce the risk of microbial contamination in frozen vegetable production systems.

To identify the point of contamination (or cross-contamination) with L. monocytogenes within the freezing plant and to implement corrective measures, the European Commission requested the EFSA to develop nonbinding guidelines on Listeria sampling strategies (41). These guidelines were intended to support both government officials at the national and local levels and the operators in the food industries. To maximize the sensitivity of detection and to support outbreak investigations, a seven-step sampling strategy was proposed in 2018: step 1, critical inspection of freezing plants; step 2, monitoring the critical sampling sites on food contact surfaces (e.g., freezing tunnels, slicers, and postblanch conveyor or vibratory belts), on nonfood contact surfaces (e.g., drains, rubber, and metal joints), and in processing water; step 3, monitoring with a predefined sampling plan; step 4, used of predefined sampling procedures; step 5, use of microbiological detection method ISO 11290-1 (55) rather than method ISO 11290-2 (56) to enhance the sensitivity of detection; step 6, characterization of the isolates to identify the point of contamination; and step 7, use of microbiological clustering analysis based on molecular techniques.

To reduce the risk of microbial contamination, strict compliance with food safety standards is of utmost importance during growing and harvesting, postharvest sorting, processing, and shipping. During processing, the main risk factors for contamination and growth of L. monocytogenes in blanched frozen vegetables are (i) the hygiene status of the incoming raw materials and the processing environment (including food and nonfood contact surfaces); (ii) the microbiological quality of the water; and (iii) the time-temperature parameters used for the processing steps (storage, washing, blanching, cooling, and freezing). Therefore, the hygienic design of the equipment, cleaning and disinfection of the environment, and water control are of paramount importance for reducing the probability of pathogen introduction, survival, and growth (40). After processing, the main risk factors affecting contamination with and growth of L. monocytogenes are the intrinsic characteristics of the blanched and frozen vegetables (e.g., pH, water activity, nutrients, presence of antimicrobial compounds, and natural microbiota), the time-temperature combinations during thawing and storage, and the cooking conditions (40). Hygiene guidance and industry standards for the commercial production of quick-frozen (blanched and unblanched) vegetables, which are regarded as not RTE, and for the control of L. monocytogenes in the production environment were developed by EU stakeholder organizations (e.g., the European Association of Fruit and Vegetables Processors) to stress the importance of hygiene in the prevention and control of Listeria contamination (10).

Multistate outbreaks of listeriosis associated with frozen vegetables were not reported in Europe before 2018 (42, 43). This outbreak raised new food safety concerns about the risk of L. monocytogenes contamination in blanched and frozen fruits and vegetables and especially for those vegetables (or fruits) regarded as not RTE and/or with unclear packaging advice for consumption. Improper handling behaviors such as consumption of thawed vegetables, particularly peas and sweet corn (e.g., in salads or smoothies) and their introduction as ingredients into RTE food (without a heating step) has been reported (79). These behaviors raised awareness among food safety risk managers of new food habits and food trends among consumers. The European Commission tasked the EFSA to assess the public health risk posed by L. monocytogenes. Thus, a modified generic quantitative risk assessment model encompassing the range of consumer habits of the EU population (age group 65 to 74 years) was used to evaluate the probability of illness per serving of blanched frozen vegetables consumed either cooked or uncooked. The model revealed that the estimated probability of illness in this age group per serving of uncooked frozen vegetables (blanch during processing) was up to 3,600 times higher than that for cooked frozen vegetables but lower than that for other RTE products such as cold-smoked fish, hot-smoked fish, gravad fish, cooked meat, sausage, pâté, and soft and semisoft cheeses (40).

However, contamination of frozen vegetables with Listeria is not a new problem. Before the European outbreak of 2015 to 2018, frozen corn was associated with a listeriosis outbreak in the United States that began in 2013 (6). Nine people from four states were infected (median age, 76 years), three in 2016 and six in 2013 to 2015, who were identified retrospectively through search of the PulseNet database, the U.S. molecular subtyping network for foodborne disease surveillance established by the Centers for Disease Control and Prevention. Epidemiological and laboratory data indicated that frozen vegetables (including frozen corn and peas) were the likely Listeria vehicle, and their common manufacturer was the source of infections in this outbreak.

Following these outbreaks, the microbiological quality of frozen fruits and vegetables became a focus in the scientific community, and baseline studies were conducted. In a British study, L. monocytogenes (serogroups 1/2a, 1/2b, and 4b) was detected in 0.9% (3 of 351) of frozen fruit samples, 10.3% (69 of 673) of frozen vegetable samples, and 23% (6 of 26) of fruit and vegetable mix samples, with an overall L. monocytogenes prevalence of 7% (78 of 1,050 total samples) and a prevalence of other Listeria species of 10% (101 of 1,050 total samples). The prevalence of L. monocytogenes in products whose intended use was not stated on the label was 7% (9 of 125 samples). Although all samples in the British study never exceeded the L. monocytogenes level established in EC 2073/2005 (as amended) of >100 CFU/g (20), the presence of Listeria was considered a problem. Some food products might be thawed and held at refrigeration or ambient temperature before consumption, non-RTE products might be consumed without the proper compliance with the cooking instructions, and some product labels do not include clear handling instructions and therefore these products are not cooked at all. All of these scenarios provide opportunities for growth of harmful bacteria, including L. monocytogenes (79).

The outbreak caused by contaminated frozen corn also highlighted the need for clear and consistent label information to raise awareness about the health risks associated with the consumption of uncooked frozen vegetables, particularly by susceptible population groups (40). Uncooked frozen berries contaminated with hepatitis A virus were responsible for a prolonged multistate outbreak affecting many countries in Europe during 2013 and 2014 (15, 74). This incident was an early signal of the need for a more robust food safety culture that could be promoted through raising awareness about the importance of proper food handling, heat treatment before consumption, and clear instructions for consumption.

The outbreak linked to frozen corn prompted an upgrade of the existing joint molecular typing database (set up after the outbreak linked to sprouted seeds) to include data generated with more discriminatory techniques. The joint ECDC-EFSA database was designed for sharing comparable typing data, based on PFGE and MLVA methods, in a common repository to enable joint analysis of data across sectors and support early detection and investigation of cross-border foodborne outbreaks (70). However, the need for higher resolution microbial subtyping, evident also in this outbreak, triggered the request from European Commission for the integration of WGS data in a One Health WGS system. This new system is designed to detect signals of multistate events based on WGS data by including two interoperating workflows supported by databases, one for human data received by the ECDC and one for nonhuman data received by the EFSA. Each workflow collects and stores the data (i.e., allelic profiles and descriptive data) in the respective data domain, and the two databases interact programmatically each time the ECDC or EFSA want to search for cross-sector matches. After a signal is detected and further investigation is considered necessary, additional work is done by the agencies to evaluate the event, including further WGS data exchange (EFSA mandate M-2020-0015).

Between 2016 and 2020, a persistent polyclonal outbreak of salmonellosis caused by Salmonella enterica serovar Enteritidis affected 18 countries in Europe. This outbreak is the largest European outbreak ever reported and was identified via MLVA and WGS. Of the 1,656 cases, 656 were classified as confirmed, 202 as probable, 385 as historical-confirmed, and 413 as historical-probable. Two historical-confirmed case patients, a child and an elderly person, died due to the infection. Confirmed cases were genetically linked to two WGS clusters (t5.175 and t5.360) based on single nucleotide polymorphism analysis (8), in which each isolate had five or fewer single nucleotide polymorphism differences from at least one other case in the cluster, based on single linkage clustering (17).

The multistate salmonellosis outbreak investigation was triggered by national investigations that were started in 2016 by the public health authorities in the United Kingdom (Scotland) and in the Netherlands, and other countries in Europe were warned through the EWRS. An international outbreak investigation team was convened, and the information gathered from patient interviews guided the investigations to eggs and egg products. In the United Kingdom, the suspected food items likely consumed in catering premises were traced back through extensive work to a consortium of farms and packaging centers in Poland (68). In 2015 to 2019, samples from various laying hen farms, the majority of which belonging to the same consortium, were positive for at least one of the clones within the two WGS clusters that caused the human infections.

After the first salmonellosis peaks (2016 to 2017), officials traced the eggs back to the Salmonella-positive farms. They inspected these farms and ordered implementation of stricter hygiene measures and compliance with food safety requirements. In 2018, the European Commission carried out an audit in Poland to evaluate the implementation of the Salmonella National Control programs, in particular for poultry populations and the systems used to prevent food contamination (29). Even when corrective measures were taken by the business operators (e.g., depopulation of the positive flocks and cleaning and disinfection of premises and equipment), in the following two years (2018 and 2019), some of the farms of the consortium were still found to be contaminated with the same outbreak strain or even multiple outbreak strains. This reiterated detection suggested persistent contamination with or possible reintroduction of Salmonella. When the outbreak was assessed, a common point of contamination across the laying hen farms and thus the root source of the contamination could not be established despite the upstream investigations (e.g., parent stocks, hatcheries, and rearing farms). Investigators never conclusively identified the precise source of the contamination. However, this outbreak exposed weaknesses in the food safety systems of the individuated farming facilities and offered an opportunity for their managers to take corrective actions.

The detection of Salmonella Enteritidis clone t5.175 was reported also in laying hen and broiler farms in Germany, indicating a possible wider circulation of the clone in Europe and the possible existence of multiple sources of infections in the original outbreak. The use of sequencing to identify bacterial genomes is increasing but at different rates among the EU countries, depending on nationals capabilities, and the resources spent on animal or food strains and human strains are unbalanced, in favor of the latter. Bacterial genome sequencing efforts also differ along the food production chain (17). Therefore, an estimation of the prevalence of some clones with respect to other clones and their geographical distribution remain underestimated or in some cases unknown. The rate at which data are shared among countries also varies; thus, the genetic diversity of Salmonella Enteritidis inferred from the shared and public genomes does not necessarily reflect the global diversity (1).

This egg-associated salmonellosis outbreak illustrates the challenges faced by investigators in attempting to trace an egg consumed by an outbreak victim back to a farmer through a distributor and a retail store where the egg was purchased or a restaurant (catering premises) where the egg was consumed. European legislation (18) requires that food traceability be guaranteed in each step of the food chain. Nevertheless, the actions taken by business operators of resorting, repacking, and assigning new identification numbers to a product further complicate the task of tracing a product's path, especially on a large scale such as in multistate outbreaks.

Similar tracing challenges have been apparent in Europe. In 2014 and 2015, a prolonged outbreak of hepatitis A occurred, with 1,500 cases in 13 countries. This outbreak, known as the largest hepatitis A outbreak in Europe (74), led the European Commission to ask the EFSA to coordinate an extensive exercise to identify the berries contaminated with the hepatitis A virus (mixed frozen berries), to trace them back to their place of production, and to find a point of contamination (37). Given the complexity of the outbreak, the type of food item involved, and the epidemiological evidence available at the time of the exercise, the traceback analysis did not reveal a single source of contamination. However, some common ingredients (Bulgarian blackberries and Polish red currants) were identified. These ingredients were common to the lots of mixed frozen berries likely associated with some cases. Given the large and complex data set, the exercise relied on the use of the software FoodChain-Lab (78) to analyze and visualize the data that resulted from the traceback activities.

In addition to the complexity of distribution chain, in the Salmonella Enteritidis infection outbreak the challenge was the timely recall of food exposure information by the interviewed patients. The use of nonstandardized questionnaires among the countries that were included in the investigation hindered the comparison of the collected data (68). The 2019 cases could not be epidemiologically linked to a specific food vehicle or food operator despite the microbiological evidence (17).

The finding that the outbreak linked to eggs was caused by Salmonella Enteritidis was not surprising, given the fact that in Europe this pathogen is the most frequent cause of salmonellosis, associated with 84.1% of the foodborne salmonellosis outbreaks. Eggs (and egg products) are the food vehicles mainly reported by the EU member states (45). Multistate outbreaks caused by consumption of eggs contaminated with Salmonella Enteritidis have been reported in the United States, with 3,578 cases in 11 states in 2010 (4) and 44 cases in 11 states in 2018 (7).

The continuous progress made in food safety technology, such as the use of genome sequencing and computational genome analysis, is already advancing the early detection and identification of small clusters (signals) of illness with unprecedented precision. These signals can trigger food investigations and further actions, preventing progression into bigger clusters, local outbreaks, or multistate outbreaks. Food investigations are conducted to quickly identify the contaminated or incriminated food (or single ingredient) and its precise location to ensure that the food is removed from the marketplace. For a prompt reaction, the sharing of data in real time is crucial. This sharing allows investigators to better understand the magnitude of the event (through sequencing data) and allows officials and food operators to intervene with control and corrective measures (through tracing data) in a timely manner. However, tracebacks still rely mostly on paper records. This type of record keeping and late delivery of data (sometimes incomplete or missing) make it difficult to rapidly track contaminated food products along the supply chain and prevent officials from ensuring quick removal of contaminated items from the marketplace.

With the digital revolution and the new European digital strategy (31), emerging technologies such as artificial intelligence, the Internet of Things (IoT), sensor technologies, and blockchain are being evaluated for their applicability in food production systems and the food supply chain. These emerging technologies can provide new tools for approaching food safety issues and investigating foodborne incidents, for instance, by means of a more traceable digital food system (77, 83). These new technologies have the potential for improving the speed and precision of the traceability of food products by providing real-time data, which are valuable in outbreak investigations, assessments, and management. Digital traceability could also allow officials to issue faster recalls of unsafe food items (77).

The IoT devices combine physical objects (“things”) with embedded sensors and software and Internet connectivity. This new technological paradigm appeared a few years ago, and IoT devices have been deployed worldwide (e.g., smart cities, e-health, and smart grid). Although this technology is still in its early development stages and applications for food safety are currently limited, IoT has potential as a source of information (large amounts of data) that can be used to supplement the traditional sources of information, such as surveillance, monitoring, and inspection systems already in place (3).

A recent review (3) of the current state of art of IoT technologies, including their feasibility for filling food safety and knowledge gaps, revealed that the majority of the available studies focused on IoT architectures are still theoretical, with few studies regarding real implementation in the food sector. The major applications of IoT were for tracing food products along the supply chain and for monitoring safety and quality variables such as temperature, humidity, location, and microbial activity. The food categories most often involved were meat, cold chain products, and agriculture products. Among the communication technologies used in IoT were the Internet, radio-frequency identification tags, and wireless sensor networks. Liu et al. (61) developed an IoT architecture to monitor food along the supply chain and allow storage and real-time sharing of the data among all actors in the supply chain. Musa and Vidyasankar (66) developed a system for monitoring the cold chain of blackberries (a highly perishable food) to allow estimation of the shelf life. When the calculated shelf life deviates from a threshold limit, the system automatically sends an alarm to the involved members of the food supply chain.

Big data approaches are receiving much attention because of their potential to close the gaps between the high fidelity of the genomic data and the epidemiological metadata (e.g., food tracing by radio-frequency identification tagging). These technologies have the potential to provide high discriminatory power for epidemiological data, similar to that of next-generation sequencing, and to thus link genomic data to epidemiological data in foodborne outbreak investigations and assessments (53).

The large amount of data generated by IoT devices might be integrated with blockchain technologies to increase the reliability of these data (69). The blockchain is a peer-to-peer distributed system in which the stored data become immutable (i.e., cannot be changed) and nonrepudiable (i.e., the authenticity cannot be denied). Thus, the blockchain ensures the security of the data stored in it (e.g., sensor data, electronic readable labels, barcodes, and radio-frequency identification tags) through the application of standard cryptographic techniques and improves the reliability of IoT systems. Although challenges remain, such as the scalability, for the use of blockchain technologies (48), applications in the context of food safety and traceability have been published (48, 52, 54, 59).

After the large amounts of data have been generated by IoT devices, statistical analysis can be performed to make predictions. Automated statistical approaches such as machine and deep learning have been widely applied, often leading to the new concept of smart devices (64). This technology can be used to analyze new and historical data to make predictions about future events. Another application of machine learning as an artificial intelligence tool is for mining online data (nontraditional sources of information), such as customer reviews, consumer complaints, location data, and dining apps, to pinpoint and investigate potential sources of illness in real time (machine-learned epidemiology), to generate hypothesis about food vehicles (outbreak investigation), and to guide officials conducting inspections (outbreak prevention) (75, 77).

The European surveillance system integrates elements from public and animal health systems and the food chain to detect, assess, and control multistate foodborne infections. This system is based on an inquiry and notification approach (EWRS, Epi-Pulse, and RASFF). The relevant authorities of a country warn the other countries of a national outbreak with a possible multistate spread. The other countries react when a similar food incident is detected or an unusual rate of infections is observed. At that point, the food and public health authorities of the EU member states start exchanging epidemiological and microbial subtyping information. The exchange of information is facilitated and coordinated by the EFSA and the ECDC and is followed up by the European Commission.

In this review, the major multistate outbreaks occurring in Europe in the last decade were described with the developments and enhancements they triggered to create a safer food system based on the One Health approach. Each of these outbreaks was characterized by different significant aspects. The outbreak linked to sprouted seeds was characterized by exposure to an emergent E. coli strain with unprecedented pathogenicity. In the outbreak linked to frozen corn, an unexpected (but certainly possible) combination of pathogenic L. monocytogenes and frozen vegetables caused serious illnesses for the first time in Europe. The outbreak linked to eggs was an example of a prolonged food incident with a persistent environmental component. This outbreak was significant because of the wide geographical distribution of Salmonella epidemic clones and by the challenges associated with identifying the multiple sources and root causes of the infections. In the outbreak of hepatitis A caused by frozen berries, the complexity of the production and distribution systems hindered identification of the point of contamination, providing an example of the importance of food safety culture and the need for consumer awareness about proper food handling. Consumers were advised to apply a heat treatment before consumption of the berries.

All of these outbreaks highlight the importance of rapid sharing of sequencing and tracing data, when early detection, timely investigation, and prompt management of the food incident is the goal. They also highlight the need for better harmonization at the European level of strategies for patient interviews to retrieve food exposure information and quickly direct the epidemiological investigation toward the likely source of infection. Investigation results led to the enforcement of the existing hygiene provisions for foods of nonanimal origin and to the development of new hygiene and best practices guidelines. A legal framework was developed for a European collaboration platform to share WGS data and facilitate foodborne detection and investigation. In 2019, in response to various foodborne incidents the European Commission (30) updated the general plan for crisis management in the food and feed safety area and clearly acknowledged the importance of promoting at the EU level the use of molecular typing analyses, including WGS, and the sharing of such results with the EFSA and the ECDC as a preparedness exercise for future crises. The introduction of WGS largely contributed to generation of hypotheses on the food vehicle in these infections and advanced the outbreak investigations. However, widely accepted guidance is still needed for the use of the WGS results to answer epidemiological questions (2, 38, 67).

The rapid increase and spread of noninteroperable analytical and reporting systems has hampered the effective use of WGS technologies in foodborne outbreak detection and investigation across sectors and jurisdictions (62, 63, 76). To ensure interoperability and accuracy, a common understanding must be established for the minimum quality standards needed for the sequence data, the derived WGS and typing data, and the associated metadata (38, 67). General requirements for the laboratory and bioinformatic components of WGS and associated metadata for foodborne bacteria have been recently published by the International Organization for Standardization (57). These guidelines provide the bases for harmonization of bioinformatic analysis and validation of the end-to-end WGS workflows.

Syntactic and semantic interoperability between systems are essential components for the application of modern technologies in outbreak detection and investigation across countries and sectors. To overcome the barriers related to the spread of incompatible systems, several international consortia (e.g., One Health European Joint Programme [https://onehealthejp.eu/], Global Microbial Identifier [https://www.globalmicrobialidentifier.org/], Public Health Alliance for Genomic Epidemiology [https://github.com/pha4ge/pha4ge.github.io], and Genomic Epidemiology Ontology [https://genepio.org/]) are working worldwide to establish common data formats (e.g., models for epidemiological and typing data), standardized reporting, common ontologies (e.g., FoodOn and FoodEx2) (9, 46), and communication protocols.

These systems should be designed to be automatically interoperable to guarantee the reliability of the data and metadata inserted, that is, these systems should be able to exchange information without a human operator. The reliability of the data is usually ensured by use of a trusted source. Therefore, such systems would need to enforce the accountability of the data, that is, to ensure that the data were generated by a specific (trusted) source, and that the trusted source cannot deny having generated or inserted such data (nonrepudiation).

A variety of experts working in multiple private and public sectors played key roles in the investigation and resolution of these outbreaks. Efforts to mitigate the risk of foodborne illnesses and outbreaks involve many stakeholders, and their inclusion provides a wider perspective. Another equally important component of a strong and resilient food safety system is a food safety culture that promotes safe food handling behaviors.

New technologies are accelerating changes in food safety systems. WGS, based on the latest next-generation sequencing technologies, improved the ability of officials to early outbreaks identify, to define the food vehicles, and to pinpoint root causes. WGS is a valuable tool in epidemiological investigations because of its the high discriminatory power, but its outputs and computational approaches must be harmonized to create meaningful data that will inform public health actions.

Information technologies are enhancing the traceability of food throughout the supply chain and are redirecting the conventional tracing systems toward a digitized supply chain with production of electronic whole-chain tracing data shareable in a real-time manner. These technologies can help close the gaps between genomic and tracing data to allow officials to better attribute cases of infections to contaminated foods and sources. The application of these technologies to the traceability systems is still in the early stages with more theoretical than practical applications, although day-to-day use should become more common in the near future.

The authors Ernesto Liebana, Valentina Rizzi, Mirko Rossi, and Eleonora Sarno are employed with the European Food Safety Authority (EFSA) in the Unit BIOCONTAM that provides scientific and administrative support to the Panel on Biological Hazards in the area of the hazard monitoring activities and the food/feed safety risk assessment (chemical and biological hazards) along the food chain from farm-to-fork in areas within the scope of BIOHAZ and CONTAM Panels (including relevant domain guidance/approaches/methodologies). The author Denise Pezzutto is affiliated with the EFSA in the Unit BIOCONTAM as a trainee. However, the present article is published under the sole responsibility of the authors and may not be considered an EFSA scientific output. The position and opinions presented in this article are those of the authors alone and are not intended to represent the views or any official position or scientific work of the EFSA. To learn about the views or scientific output of the EFSA, please consult its Web site at http://www.efsa.europa.eu.

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