Foodborne Outbreak Investigations Research Articles

Environmental Antecedents of Foodborne Illness Outbreaks, United States, 2017–2019

Foodborne outbreak investigations often provide data for public health officials to determine how the environment contributed to the outbreak and on how to prevent future outbreaks. State and local health departments are responsible for investigating foodborne illness outbreaks in their jurisdictions and reporting the data to national-level surveillance systems, including information from the environmental assessment. This assessment is designed to describe how the environment contributed to the outbreak and identifies factors that contributed to the outbreak and environmental antecedents to the outbreak. Environmental antecedents, also referred to as root causes, are specific reasons that allow biological or chemical agents to contaminate, survive, or grow in food. From 2017 to 2019, 24 jurisdictions reported 1,430 antecedents from 393 outbreaks to the National Environmental Assessments Reporting System. The most reported antecedents were lack of oversight of employees/enforcement of policies (89.1%), lack of training of employees on specific processes (74.0%), and lack of a food safety culture/attitude towards food safety (57.5%). These findings highlight the critical role that employees play in restaurant food safety and are heavily influenced by restaurant management, who can exercise active managerial control to manage these antecedents. Identifying antecedents during investigations is essential for understanding the outbreak’s root cause and implementing sustainable corrective actions to stop the immediate outbreak and future outbreaks.

Whole-Genome Sequencing-Based Confirmatory Methods on RT-qPCR Results for the Detection of Foodborne Viruses in Frozen Berries.

Accurate detection, identification, and subsequent confirmation of pathogens causing foodborne illness are essential for the prevention and investigation of foodborne outbreaks. This is particularly true when the causative agent is an enteric virus that has a very low infectious dose and is likely to be present at or near the limit of detection. In this study, whole-genome sequencing (WGS) was combined with either of two non-targeted pre-amplification methods (SPIA and SISPA) to investigate their utility as a confirmatory method for RT-qPCR positive results of foods contaminated with enteric viruses. Frozen berries (raspberries, strawberries, and blackberries) were chosen as the food matrix of interest due to their association with numerous outbreaks of foodborne illness. The hepatitis A virus (HAV) and human norovirus (HuNoV) were used as the contaminating agents. The non-targeted WGS strategy employed in this study could detect and confirm HuNoV and HAV at genomic copy numbers in the single digit range, and in a few cases, identified viruses present in samples that had been found negative by RT-qPCR analyses. However, some RT-qPCR-positive samples could not be confirmed using the WGS method, and in cases with very high Ct values, only a few viral reads and short sequences were recovered from the samples. WGS techniques show great potential for confirmation and identification of virally contaminated food items. The approaches described here should be further optimized for routine application to confirm the viral contamination in berries.

Outbreak Linked to Morel Mushroom Exposure - Montana, 2023.

During March-April 2023, a total of 51 persons reported mild to severe gastrointestinal illness after eating at restaurant A in Bozeman, Montana. The outbreak resulted in multiple severe outcomes, including three hospitalizations and two deaths. After an inspection and temporary restaurant closure, the Montana Department of Public Health and Human Services and Montana's Gallatin City-County Health Department collaborated with CDC to conduct a matched case-control study among restaurant patrons to help identify the source of the outbreak. Consumption of morel mushrooms, which are generally considered edible, was strongly associated with gastrointestinal illness. A dose-response relationship was identified, and consumption of raw morel mushrooms was more strongly associated with illness than was consumption of those that were at least partially cooked. In response to the outbreak, educational public messaging regarding morel mushroom preparation and safety was shared through multiple media sources. The investigation highlights the importance of prompt cross-agency communication and collaboration, the utility of epidemiologic studies in foodborne disease outbreak investigations, and the need for additional research about the impact of morel mushroom consumption on human health. Although the toxins in morel mushrooms that might cause illness are not fully understood, proper preparation procedures, including thorough cooking, might help to limit adverse health effects.

Strain-level characterization of foodborne pathogens without culture enrichment for outbreak investigation using shotgun metagenomics facilitated with nanopore adaptive sampling.

Shotgun metagenomics has previously proven effective in the investigation of foodborne outbreaks by providing rapid and comprehensive insights into the microbial contaminant. However, culture enrichment of the sample has remained a prerequisite, despite the potential impact on pathogen detection resulting from the growth competition. To circumvent the need for culture enrichment, we explored the use of adaptive sampling using various databases for a targeted nanopore sequencing, compared to shotgun metagenomics alone. The adaptive sampling method was first tested on DNA of mashed potatoes mixed with DNA of a Staphylococcus aureus strain previously associated with a foodborne outbreak. The selective sequencing was used to either deplete the potato sequencing reads or enrich for the pathogen sequencing reads, and compared to a shotgun sequencing. Then, living S. aureus were spiked at 105 CFU into 25 g of mashed potatoes. Three DNA extraction kits were tested, in combination with enrichment using adaptive sampling, following whole genome amplification. After data analysis, the possibility to characterize the contaminant with the different sequencing and extraction methods, without culture enrichment, was assessed. Overall, the adaptive sampling outperformed the shotgun sequencing. While the use of a host removal DNA extraction kit and targeted sequencing using a database of foodborne pathogens allowed rapid detection of the pathogen, the most complete characterization was achieved when using solely a database of S. aureus combined with a conventional DNA extraction kit, enabling accurate placement of the strain on a phylogenetic tree alongside outbreak cases. This method shows great potential for strain-level analysis of foodborne outbreaks without the need for culture enrichment, thereby enabling faster investigations and facilitating precise pathogen characterization. The integration of adaptive sampling with metagenomics presents a valuable strategy for more efficient and targeted analysis of microbial communities in foodborne outbreaks, contributing to improved food safety and public health.

Unveiling the gender gap in research: a bibliometric analysis of the 100 most-cited articles on food-borne pathogen outbreaks from 1990 to 2020.

Despite a recent increase in the representation of female authors in scientific literature, a significant gap persists concerning the inclusion of women in research. This necessitates the analysis of published literature from a gender perspective. This study aimed to provide gender distribution in authorship in the 100 most-cited articles on food-borne pathogen outbreaks from 1990 to 2020. Bibliometric analysis was conducted using the Scopus database. Two reviewers were selected to search the database. We included the 100 most-cited articles on foodborne outbreak investigations. The analysis was conducted using Statistical Package for Social Sciences (SPSS) version 26 and Microsoft Excel version 2016. The citation data, including total citations, citations per year, and representation of women as first and senior authors, was analyzed in terms of frequencies, mean, median, and interquartile range. The correlation between journal impact factor and the representation of women in high-impact factor journals was determined. A p-value of <0.05 was considered significant. Most of the top-cited articles were published between 2001 and 2010 (n=47). The top 3 most-cited articles were from the USA. Of the total 100 articles, women were the first and last authors in 46% and 28% of the articles, respectively, reflecting a significant gender gap. However, the proportion of females as principal investigators gradually increased from 25% (n=10/30) to 52% (n=24/47) during the period 2001-2010 and to 92% (n=12/13) during 2011-2020. The USA had the highest number of included articles (n=48), and women were principal authors in 56% (n=27) of them. The lowest representation of women was observed in Austria, Denmark, Japan, Netherlands, New Zealand, Nigeria, Portugal, and the United Kingdom. Women are under-represented in published literature on food-borne pathogen outbreaks. Although the representation of women as principal authors has recently increased, disparities still exist at the senior-author level, calling for women's advancement in academic science.

Prevention, protocols, and lab capacity: lessons from a norovirus outbreak in the Algarve.

This brief report presents the findings of an epidemiological investigation into a large-scale outbreak of norovirus gastroenteritis that occurred in a hotel in Algarve, Portugal, in August 2022. A total of 244 cases were reported, primarily affecting Portuguese families, with the parents aged 40-50 years and the children aged 0-19 years. Reported symptoms included vomiting, nausea, abdominal pain, and diarrhoea. Norovirus genotype GI.3 [P3] was detected in stool samples from eight probable cases, while food samples tested negative for norovirus and common pathogenic bacteria. The investigation data collected suggest that the source of the outbreak was likely in the hotel's common areas, with subsequent person-to-person transmission in other areas. The final report emphasizes the importance of improving outbreak prevention and control measures, including the development of a foodborne outbreak investigation protocol, the establishment of an outbreak response team, and the enhancement of regional laboratory capacity.

652. Foodborne outbreak investigation at a wedding event – Batken, Kyrgyzstan, June 2022

Abstract Background On August 2nd, 2022, local health departments were informed that over a hundred people had sought care or reported gastrointestinal illness after attending the same wedding event in Batken, Kyrgyzstan, on July 30th. We investigated to identify the source and associated risk factors to stop transmission. Methods Using a retrospective cohort study design, we interviewed consenting wedding participants. A case was anyone who was linked to the event who became acutely ill or sought medical care with food poisoning symptoms. We searched public health surveillance records for additional cases who sought healthcare for suspected foodborne disease, a reportable illness, from July 30th to August 2nd. Food and environmental samples were collected and tested. We used logistic regression to determine associations with case status. Results Of 250 attendees, 201 consented; 110 were cases and 91 non-cases. Among cases, 8%were &amp;lt; 20 years old, 27% were &amp;gt;61 years old, and 80% were female. Top symptoms were fatigue (96%), abdominal pain (95%), diarrhea (95%), and fever (84%). Most cases developed symptoms &amp;lt; 24 hours of the event and 79% sought care. Odds ratio was 7.8 for egg salad containing chicken (95% confidence interval [CI]: 4.1-14.4, p&amp;lt; 0.01), 5.1 for grilled chicken (CI: 2.8-9.4, p&amp;lt; 0.01) and 3.9 for chicken salad (CI: 2.2-7.1, p&amp;lt; 0.01). Attack rate was 66% (105/160) among people who ate any chicken (95% of cases and 60% of non-cases). Patients were not tested. Proteus vulgaris, Klebsiella spp., and Escherichia coli were detected in chicken samples. E. coli was detected in 3/32 environmental samples. Conclusion Contaminated chicken was the likely source of illness. Source pathogen is uncertain because patients were not tested. Symptoms and onset were more consistent with Klebsiella spp. than E. coli, but Klebsiella spp food-associated outbreaks are rare. Recommendations were made to ensure restaurant compliance with food safety measures. Diagnostic testing for gastrointestinal illness needs strengthening. Disclosures All Authors: No reported disclosures

Epidemiological Data Mining for Assisting with Foodborne Outbreak Investigation.

Diseases caused by the consumption of food are a significant but avoidable public health issue, and identifying the source of contamination is a key step in an outbreak investigation to prevent foodborne illnesses. Historical foodborne outbreaks provide rich data on critical attributes such as outbreak factors, food vehicles, and etiologies, and an improved understanding of the relationships between these attributes could provide insights for developing effective food safety interventions. The purpose of this study was to identify hidden patterns underlying the relations between the critical attributes involved in historical foodborne outbreaks through data mining approaches. A statistical analysis was used to identify the associations between outbreak factors and food sources, and the factors that were strongly significant were selected as predictive factors for food vehicles. A multinomial prediction model was built based on factors selected for predicting "simple" foods (beef, dairy, and vegetables) as sources of outbreaks. In addition, the relations between the food vehicles and common etiologies were investigated through text mining approaches (support vector machines, logistic regression, random forest, and naïve Bayes). A support vector machine model was identified as the optimal model to predict etiologies from the occurrence of food vehicles. Association rules also indicated the specific food vehicles that have strong relations to the etiologies. Meanwhile, a food ingredient network describing the relationships between foods and ingredients was constructed and used with Monte Carlo simulation to predict possible ingredients from foods that cause an outbreak. The simulated results were confirmed with foods and ingredients that are already known to cause historical foodborne outbreaks. The method could provide insights into the prediction of the possible ingredient sources of contamination when given the name of a food. The results could provide insights into the early identification of food sources of contamination and assist in future outbreak investigations. The data-driven approach will provide a new perspective and strategies for discovering hidden knowledge from massive data.

A Bayesian Method for Exposure Prevalence Comparison During Foodborne Disease Outbreak Investigations.

CDC and health departments investigate foodborne disease outbreaks to identify a source. To generate and test hypotheses about vehicles, investigators typically compare exposure prevalence among case-patients with the general population using a one-sample binomial test. We propose a Bayesian alternative that also accounts for uncertainty in the estimate of exposure prevalence in the reference population. We compared exposure prevalence in a 2020 outbreak of Escherichia coli O157:H7 illnesses linked to leafy greens with 2018-2019 FoodNet Population Survey estimates. We ran prospective simulations using our Bayesian approach at three time points during the investigation. The posterior probability that leafy green consumption prevalence was higher than the general population prevalence increased as additional case-patients were interviewed. Probabilities were >0.70 for multiple leafy green items 2 weeks before the exact binomial p-value was statistically significant. A Bayesian approach to assessing exposure prevalence among cases could be superior to the one-sample binomial test typically used during foodborne outbreak investigations.

An Overview of Foodborne Sample-Initiated Retrospective Outbreak Investigations and Interagency Collaboration in the United States

Foodborne outbreak investigations have traditionally included the detection of a cluster of illnesses first, followed by an epidemiologic investigation to identify a food of interest. The increasing use of whole genome sequencing (WGS) subtyping technology for clinical, environmental, and food isolates of foodborne pathogens, and the ability to share and compare the data on public platforms, present new opportunities to identify earlier links between illnesses and their potential sources. We describe a process called sample-initiated retrospective outbreak investigations (SIROIs) used by federal public health and regulatory partners in the United States. SIROIs begin with an evaluation of the genomic similarity between bacterial isolates recovered from food or environmental samples and clusters of clinical isolates while subsequent and parallel epidemiologic and traceback investigations are initiated to corroborate their connection. SIROIs allow for earlier hypothesis generation, followed by targeted collection of information about food exposures and the foods and manufacturer of interest, to confirm a link between the illnesses and their source. This often leads to earlier action that could reduce the breadth and burden of foodborne illness outbreaks. We describe two case studies of recent SIROIs and present the benefits and challenges. Benefits include insight into foodborne illness attribution, international collaboration, and opportunities for enhanced food safety efforts in the food industry. Challenges include resource intensiveness, variability of epidemiologic and traceback data, and an increasingly complex food supply chain. SIROIs are valuable in identifying connections among small numbers of illnesses that may span significant time periods; detecting early signals for larger outbreaks or food safety issues associated with manufacturers; improving our understanding of the scope of contamination of foods; and identifying novel pathogen/commodity pairs.

Evaluation of Genomic Typing Methods in the Salmonella Reference Laboratory in Public Health, England, 2012–2020

We aim to provide an evidence-based evaluation of whole genome sequence (WGS) methods, employed at the Salmonella reference laboratory in England, in terms of its impact on public health and whether these methods remain a fit for purpose test under UKAS ISO 15189. The evaluation of the genomic methods were mapped against the value of detecting microbiological clusters to support the investigation of food-borne outbreaks of Salmonella in England between 2012-2020. The analysis of WGS with both SNP- and allelic-based methods provided an unprecedented level of strain discrimination and detection of additional clusters when comparing to all of the previous typing methods. The robustness of the routine genomic sequencing at the reference laboratory ensured confidence in the microbiological identifications, even in large outbreaks with complex international food distribution networks. There was evidence that the phylogeny derived from the WGS data can be used to inform the provenance of strains and support discrimination between domestic and non-domestic transmission events. Further insight on the evolutionary context of the emerging pathogenic strains was enabled with a deep dive of the phylogenetic data, including the detection of nested clusters. The public availability of the WGS data linked to the clinical, epidemiological and environmental context of the sequenced strains has improved the trace-back investigations during outbreaks. The global expansion in the use of WGS-based typing in reference laboratories has shown that the WGS methods are a fit for purpose test in public health as it has ensured the rapid implementation of interventions to protect public health, informed risk assessment and has facilitated the management of national and international food-borne outbreaks of Salmonella.

First molecular characterization of Escherichia coli O157:H7 isolates from clinical samples in Paraguay using whole-genome sequencing

Escherichia coli O157:H7 is a foodborne pathogen implicated in numerous outbreaks worldwide that has the ability to cause extra-intestinal complications in humans. The Enteropathogens Division of the Central Public Health Laboratory (CPHL) in Paraguay is working to improve the genomic characterization of Shiga toxin-producing E. coli (STEC) to enhance laboratory-based surveillance and investigation of foodborne disease outbreaks. Whole genome sequencing (WGS) is proposed worldwide to be used in the routine laboratory as a high-resolution tool that allows to have all the results in a single workflow. This study aimed to carry out for the first time, the genomic characterization by WGS of nine STEC O157:H7 strains isolated from human samples in Paraguay. We were able to identify virulence and resistance mechanisms, MLST subtype, and even establish the phylogenetic relationships between isolates. Furthermore, we detected the presence of strains belonging to hypervirulent clade 8 in most of the isolates studied.

Characteristics associated with successful foodborne outbreak investigations involving United States retail food establishments (2014-2016).

This study examined relationships between foodborne outbreak investigation characteristics, such as the epidemiological methods used, and the success of the investigation, as determined by whether the investigation identified an outbreak agent (i.e. pathogen), food item and contributing factor. This study used data from the Centers for Disease Control and Prevention's (CDC) National Outbreak Reporting System and National Environmental Assessment Reporting System to identify outbreak investigation characteristics associated with outbreak investigation success. We identified investigation characteristics that increase the probability of successful outbreak investigations: a rigorous epidemiology investigation method; a thorough environmental assessment, as measured by number of visits to complete the assessment; and the collection of clinical samples. This research highlights the importance of a comprehensive outbreak investigation, which includes epidemiology, environmental health and laboratory personnel working together to solve the outbreak.

Use of Whole Genome Sequencing as Routine Typing Method — Improvements in the Investigation of Foodborne Outbreaks of Listeria monocytogenes

Use of Whole Genome Sequencing as Routine Typing Method — Improvements in the Investigation of Foodborne Outbreaks of <i>Listeria monocytogenes</i>

Barriers to stool specimen collection during foodborne and enteric illness outbreak investigations in Arizona and Colorado

Stool specimen collection during a foodborne or enteric illness outbreak investigation is essential for determining the outbreak etiology and for advancing the epidemiologic understanding of the pathogens and food vehicles causing illness. However, public health professionals face multifaceted barriers when trying to collect stool specimens from ill person during an outbreak investigation. The Colorado Integrated Food Safety Center of Excellence (Colorado IFS CoE) and the Arizona Department of Health Services surveyed local public health agencies (LPHAs) to identify barriers to collecting ≥2 clinical specimens in foodborne and enteric illness outbreaks. The most commonly selected patient-related barrier was that the patient did not think it is important to provide a stool sample because they are well by the time the LPHA follows-up (61%). The most frequently selected outbreak-related barrier was the LPHA did not learn about the outbreak until after symptoms had resolved (61%). Time/personnel not being available for stool collection was the most frequently chosen health department-related barrier (51%). Timing of the outbreak (e.g., on a weekend or holiday) was the most frequently selected transportation-related barrier (51%) to collecting ≥2 stool specimens. Many of the frequently cited barriers in this survey were similar to those previously reported, such as workforce capacity and patient privacy concerns, indicating that these barriers are ongoing. Reducing barriers to stool collection during outbreaks will require efforts led at the national and state levels, such as increased enteric illness program funding, educating public health staff on the importance of specimen collection during every enteric illness outbreak, and providing specimen collection resources to LPHA staff.

Whole-Genome Sequence Comparisons of Listeria monocytogenes Isolated from Meat and Fish Reveal High Inter- and Intra-Sample Diversity.

Interpretation of whole-genome sequencing (WGS) data for foodborne outbreak investigations is complex, as the genetic diversity within processing plants and transmission events need to be considered. In this study, we analyzed 92 food-associated Listeria monocytogenes isolates by WGS-based methods. We aimed to examine the genetic diversity within meat and fish production chains and to assess the applicability of suggested thresholds for clustering of potentially related isolates. Therefore, meat-associated isolates originating from the same samples or processing plants as well as fish-associated isolates were analyzed as distinct sets. In silico serogrouping, multilocus sequence typing (MLST), core genome MLST (cgMLST), and pangenome analysis were combined with screenings for prophages and genetic traits. Isolates of the same subtypes (cgMLST types (CTs) or MLST sequence types (STs)) were additionally compared by SNP calling. This revealed the occurrence of more than one CT within all three investigated plants and within two samples. Analysis of the fish set resulted in predominant assignment of isolates from pangasius catfish and salmon to ST2 and ST121, respectively, potentially indicating persistence within the respective production chains. The approach not only allowed the detection of distinct subtypes but also the determination of differences between closely related isolates, which need to be considered when interpreting WGS data for surveillance.

Improving Foodborne Disease Surveillance and Outbreak Detection and Response Using Peer Networks-The Integrated Food Safety Centers of Excellence.

Foodborne disease surveillance and outbreak investigations are foundational to the prevention and control of foodborne disease in the United States, where contaminated foods cause an estimated 48 million illnesses, 128 000 hospitalizations, and 3000 deaths each year. Surveillance activities and rapid detection and investigation of foodborne disease outbreaks require a trained and coordinated workforce across epidemiology, environmental health, and laboratory programs. Under the 2011 Food Safety Modernization Act, the Centers for Disease Control and Prevention (CDC) was called on to establish Integrated Food Safety (IFS) Centers of Excellence (CoEs) at state health departments, which would collaborate with academic partners, to identify, implement, and evaluate model practices in foodborne disease surveillance and outbreak response and to serve as a resource for public health professionals. CDC designated 5 IFS CoEs in August 2012 in Colorado, Florida, Minnesota, Oregon, and Tennessee; a sixth IFS CoE in New York was added in August 2014. For the August 2019-July 2024 funding period, 5 IFS CoEs were designated in Colorado, Minnesota, New York, Tennessee, and Washington. Each IFS CoE is based at the state health department that partners with at least one academic institution. IFS CoEs have built capacity across public health agencies by increasing the number of workforce development opportunities (developing >70 trainings, tools, and resources), supporting outbreak response activities (responding to >50 requests for outbreak technical assistance annually), mentoring students, and responding to emerging issues, such as changing laboratory methods and the COVID-19 pandemic.

Giardiasis (lambliasis) in Poland in 2020.

Assessment of the epidemiological situation of giardiasis in Poland in year 2020. The assessment of the epidemiological situation of giardiasis in Poland in 2020 was performed on the basis of aggregated data from the annual bulletins "Infectious diseases and poisoning in Poland" for the years 2006-2020, data on individual cases collected for the purposes of epidemiological surveillance in the EpiBaza system, and data from food-borne outbreak investigations recorded in the Registry of Epidemic Outbreaks (ROE). The number of new cases of giardiasis reported in Poland in 2020 amounted to 358 cases (incidence rate 0.9 per 100,000 population) and was about 2 times lower than in 2019 (784 cases) and 2.5 times lower than in 2018 (928 cases). In 2020, there was a further decrease in the number of registered cases, but it was much more pronounced than in the preceding years. As in previous years, no deaths from giardiasis were recorded. The downward trend in hospitalizations continued and in 2020 they accounted for approximately 12.6% of all cases, in 2019 the percentage was 15.2% and in 2018 - 19.4%. Most cases met the definition of a confirmed case, with 1 patient meeting the criteria of a probable case. In 2020, 6 outbreaks of giardiasis were reported, which is a decrease compared to 2019 (12 outbreaks) and thus means a reversal of the upward trend occurring at least since 2017. Data for 2020 should be interpreted taking into account the effect of the COVID-19 pandemic, which could have resulted in changes in long-term trends, but in particular contributed to a strong decrease in the number of cases not only of giardiasis, but also of other infectious diseases. In 2020, almost all EU/EEA countries reported a decrease in the incidence of giardiasis similar to that in Poland. However, as in 2019, in 2020 Poland differed from other EU/EEA countries in terms of incidence by age and sex.

Guidelines for reporting Whole Genome Sequencing‐based typing data through the EFSA One Health WGS System

In 2019, the European Food Safety Authority (EFSA) and the European Centre for Disease Prevention and Control (ECDC) received a mandate from the European Commission (EC) to implement and manage two interoperable systems for the collection and analysis of Whole Genome Sequence (WGS) data of Salmonella enterica, Listeria monocytogenes and Escherichia coli, including Shiga toxin-producing E. coli (STEC) from humans and from food, feed, animals and the related environment, to contribute to the epidemiological investigations of food-borne outbreaks and to the identification of emerging health threats. As response to this EC mandate, EFSA has developed the EFSA One Health WGS System that interoperates with the ECDC Molecular Typing system exchanging core genome Multi Locus Sequence Typing (cgMLST) profiles and minimum metadata. Interested European Union (EU) Member States (MS) and European Economic Area (EEA) countries can submit their typing data from food, feed and animal samples to the EFSA One Health WGS system either through an user-friendly interface or programmatically. This technical report describes the EFSA One Health WGS system, including his architecture, the users and their relative data visibility, as well as data ownership and intellectual property. This report provides also detailed information on the types and formats of data that can be submitted to the EFSA One Health WGS system. Moreover, these guidelines describe the individual steps of the reporting procedure in order to support the EU MSs and EEA countries in data submission and data management.

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model.

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food-pathogen pairs to provide insights for foodborne outbreak investigations.