Comparing Characteristics of Sporadic and Outbreak-Associated Foodborne Illnesses, United States, 2004-2011

Machine learning to attribute the source of Campylobacter infections in the United States: A retrospective analysis of national surveillance data

OBJECTIVES

Integrating pathogen genomic surveillance with bioinformatics can enhance public health responses by identifying risk and guiding interventions. This study focusses on the two predominant Campylobacter species, which are commonly found in the gut of birds and mammals and often infect humans via contaminated food. Rising incidence and antimicrobial resistance (AMR) are a global concern, and there is an urgent need to quantify the main routes to human infection.

METHODS

During routine US national surveillance (2009-2019), 8856 Campylobacter genomes from human infections and 16,703 from possible sources were sequenced. Using machine learning and probabilistic models, we target genetic variation associated with host adaptation to attribute the source of human infections and estimate the importance of different disease reservoirs.

RESULTS

Poultry was identified as the primary source of human infections, responsible for an estimated 68% of cases, followed by cattle (28%), and only a small contribution from wild birds (3%) and pork sources (1%). There was also evidence of an increase in multidrug resistance, particularly among isolates attributed to chickens.

CONCLUSIONS

National surveillance and source attribution can guide policy, and our study suggests that interventions targeting poultry will yield the greatest reductions in campylobacteriosis and spread of AMR in the US.

DATA AVAILABILITY

All sequence reads were uploaded and shared on NCBI's Sequence Read Archive (SRA) associated with BioProjects; PRJNA239251 (CDC / PulseNet surveillance), PRJNA287430 (FSIS surveillance), PRJNA292668 & PRJNA292664 (NARMS) and PRJNA258022 (FDA surveillance). Publicly available genomes, including reference genomes and isolates sampled worldwide from wild birds are associated with BioProject accessions: PRJNA176480, PRJNA177352, PRJNA342755, PRJNA345429, PRJNA312235, PRJNA415188, PRJNA524300, PRJNA528879, PRJNA529798, PRJNA575343, PRJNA524315 and PRJNA689604. Contiguous assemblies of all genome sequences compared are available at Mendeley data (assembled C. coli genomes doi: 10.17632/gxswjvxyh3.1; assembled C. jejuni genomes doi: 10.17632/6ngsz3dtbd.1) and individual project and accession numbers can be found in Supplementary tables S1 and S2, which also includes pubMLST identifiers for assembled genomes. Figshare (10.6084/m9.figshare.20279928). Interactive phylogenies are hosted on microreact separately for C. jejuni (https://microreact.org/project/pascoe-us-cjejuni) and C. coli (https://microreact.org/project/pascoe-us-ccoli).

Nontyphoidal Salmonella Outbreaks Associated With Chocolate Consumption: A Systematic Review

BACKGROUND

A large, cross-border outbreak of nontyphoidal salmonellosis connected to chocolate product consumption was recently reported. This occurrence motivated us to conduct a comprehensive review of existing literature concerning outbreaks of nontyphoidal salmonellosis associated with chocolate consumption.

METHODS

We performed a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (PROSPERO CRD42022369023) in 3 databases: U.S. National Library of Medicine, Web of Science and Excerpta Medica. Google Scholar and the bibliography of each identified report were also screened. Eligible were articles published after 1970, describing outbreaks of more than 10 patients with a nontyphoidal salmonellosis associated with chocolate consumption.

RESULTS

Twenty-three articles were included, which described 12 outbreaks involving a total of 3266 patients. All outbreaks occurred in high-income countries: 1 was limited to 1 city, 6 involved 1 country and the remaining 5 involved 2 or more countries. Six outbreaks peaked in winter, 3 in autumn, 2 in spring and 1 in summer. Children were mainly affected. No predominant serotype was identified.

CONCLUSIONS

Our data documents that chocolate is an optimal medium for the transmission of nontyphoidal salmonellosis. A connected worldwide reporting system including high-income, middle-income and low-income countries is crucial to detect infectious diseases outbreaks in an early phase and avoid their spread.

Mechanism of action of anthocyanin on the detoxification of foodborne contaminants-A review of recent literature

Foodborne contaminants refer to substances that are present in food and threaten food safety. Due to the progress in detection technology and the rising concerns regarding public health, there has been a surge in research focusing on the dangers posed by foodborne contaminants. These studies aim to explore and implement strategies that are both safe and efficient in mitigating the associated risks. Anthocyanins, a class of flavonoids, are abundantly present in various plant species, such as blueberries, grapes, purple sweet potatoes, cherries, mulberries, and others. Numerous epidemiological and nutritional intervention studies have provided evidence indicating that the consumption of anthocyanins through dietary intake offers a range of protective effects against the detrimental impact of foodborne contaminants. The present study aims to differentiate between two distinct subclasses of foodborne contaminants: those that are generated during the processing of food and those that originate from the surrounding environment. Furthermore, the impact of anthocyanins on foodborne contaminants was also summarized based on a review of articles published within the last 10 years. However, further investigation is warranted regarding the mechanism by which anthocyanins target foodborne contaminants, as well as the potential impact of individual variations in response. Additionally, it is important to note that there is currently a dearth of clinical research examining the efficacy of anthocyanins as an intervention for mitigating the effects of foodborne pollutants. Thus, by exploring the detoxification effect and mechanism of anthocyanins on foodborne pollutants, this review thereby provides evidence, supporting the utilization of anthocyanin-rich diets as a means to mitigate the detrimental effects of foodborne contaminants.

Rapid geographical source attribution of Salmonella enterica serovar Enteritidis genomes using hierarchical machine learning

Salmonella enterica serovar Enteritidis is one of the most frequent causes of Salmonellosis globally and is commonly transmitted from animals to humans by the consumption of contaminated foodstuffs. In the UK and many other countries in the Global North, a significant proportion of cases are caused by the consumption of imported food products or contracted during foreign travel, therefore, making the rapid identification of the geographical source of new infections a requirement for robust public health outbreak investigations. Herein, we detail the development and application of a hierarchical machine learning model to rapidly identify and trace the geographical source of S. Enteritidis infections from whole genome sequencing data. 2313 S. Enteritidis genomes, collected by the UKHSA between 2014-2019, were used to train a 'local classifier per node' hierarchical classifier to attribute isolates to four continents, 11 sub-regions, and 38 countries (53 classes). The highest classification accuracy was achieved at the continental level followed by the sub-regional and country levels (macro F1: 0.954, 0.718, 0.661, respectively). A number of countries commonly visited by UK travelers were predicted with high accuracy (hF1: >0.9). Longitudinal analysis and validation with publicly accessible international samples indicated that predictions were robust to prospective external datasets. The hierarchical machine learning framework provided granular geographical source prediction directly from sequencing reads in <4 min per sample, facilitating rapid outbreak resolution and real-time genomic epidemiology. The results suggest additional application to a broader range of pathogens and other geographically structured problems, such as antimicrobial resistance prediction, is warranted.

Phylogeny and Genomic Characterization of Clinical Salmonella enterica Serovar Newport Collected in Tennessee

Salmonella enterica subsp. enterica serovar Newport (S. Newport) is a clinically and epidemiologically significant serovar in the United States. It is the second most prevalent clinically isolated Salmonella serovar in the United States, and it can contaminate a wide variety of food products. In this study, we evaluated the population structure of S. Newport clinical isolates obtained by the Tennessee Department of Health during routine surveillance (n = 346), along with a diverse set of other global clinical isolates obtained from EnteroBase (n = 271). Most of these clinical isolates belonged to established lineages II and III. Additionally, we performed lineage-specific phylogenetic analyses and were able to identify 18 potential epidemiological clusters among the isolates from Tennessee, which represented a greater proportion of Tennessee isolates belonging to putative epidemiological clusters than the proportion of isolates of this serovar that are outbreak related. IMPORTANCE This study provides insight on the genomic diversity of one of the Salmonella serovars that most frequently cause human illness. Specifically, we explored the diversity of human clinical isolates from a localized region (Tennessee) and compared this level of diversity with the global context. Additionally, we showed that a greater proportion of isolates were associated with potential epidemiological clusters (based on genomic relatedness) than historical estimates. We also identified that one potential cluster was predicted to be multidrug resistant. Taken together, these findings provide insight on Salmonella enterica serovar Newport that can impact public health surveillance and responses and serve as a foundational context for the Salmonella research community.

Foodborne illness outbreaks linked to unpasteurised milk and relationship to changes in state laws - United States, 1998-2018

Consumption of unpasteurised milk in the United States has presented a public health challenge for decades because of the increased risk of pathogen transmission causing illness outbreaks. We analysed Foodborne Disease Outbreak Surveillance System data to characterise unpasteurised milk outbreaks. Using Poisson and negative binomial regression, we compared the number of outbreaks and outbreak-associated illnesses between jurisdictions grouped by legal status of unpasteurised milk sale based on a May 2019 survey of state laws. During 2013-2018, 75 outbreaks with 675 illnesses occurred that were linked to unpasteurised milk; of these, 325 illnesses (48%) were among people aged 0-19 years. Of 74 single-state outbreaks, 58 (78%) occurred in states where the sale of unpasteurised milk was expressly allowed. Compared with jurisdictions where retail sales were prohibited (n = 24), those where sales were expressly allowed (n = 27) were estimated to have 3.2 (95% CI 1.4-7.6) times greater number of outbreaks; of these, jurisdictions where sale was allowed in retail stores (n = 14) had 3.6 (95% CI 1.3-9.6) times greater number of outbreaks compared with those where sale was allowed on-farm only (n = 13). This study supports findings of previously published reports indicating that state laws resulting in increased availability of unpasteurised milk are associated with more outbreak-associated illnesses and outbreaks.

Foodborne Illness Outbreaks Reported to National Surveillance, United States, 2009–2018

Foodborne outbreaks reported to national surveillance systems represent a subset of all outbreaks in the United States; not all outbreaks are detected, investigated, and reported. We described the structural factors and outbreak characteristics of outbreaks reported during 2009–2018. We categorized states (plus DC) as high (highest quintile), middle (middle 3 quintiles), or low (lowest quintile) reporters on the basis of the number of reported outbreaks per 10 million population. Analysis revealed considerable variation across states in the number and types of foodborne outbreaks reported. High-reporting states reported 4 times more outbreaks than low reporters. Low reporters were more likely than high reporters to report larger outbreaks and less likely to implicate a setting or food vehicle; however, we did not observe a significant difference in the types of food vehicles identified. Per capita funding was strongly associated with increased reporting. Investments in public health programming have a measurable effect on outbreak reporting.

Use of Whole Genome Sequencing by the Federal Interagency Collaboration for Genomics for Food and Feed Safety in the United States

ABSTRACT

This multiagency report developed by the Interagency Collaboration for Genomics for Food and Feed Safety provides an overview of the use of and transition to whole genome sequencing (WGS) technology for detection and characterization of pathogens transmitted commonly by food and for identification of their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among the following federal agencies: National Institutes of Health; Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) and U.S. Food and Drug Administration (FDA); and the U.S. Department of Agriculture, Food Safety and Inspection Service, Agricultural Research Service, and Animal and Plant Health Inspection Service. We describe single nucleotide polymorphism, core-genome, and whole genome multilocus sequence typing data analysis methods as used in the PulseNet (CDC) and GenomeTrakr (FDA) networks, underscoring the complementary nature of the results for linking genetically related foodborne pathogens during outbreak investigations while allowing flexibility to meet the specific needs of Interagency Collaboration partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles) and source attribution efforts and increase transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information. We also highlight the impact of current trends in the use of culture-independent diagnostic tests for human diagnostic testing on analytical approaches related to food safety and what is next for the use of WGS in the area of food safety.

HIGHLIGHTS

Evaluating Completeness of Foodborne Outbreak Reporting in the United States, 1998-2019

Public health agencies routinely collect time-referenced records to describe and compare foodborne outbreak characteristics. Few studies provide comprehensive metadata to inform researchers of data limitations prior to conducting statistical modeling. We described the completeness of 103 variables for 22,792 outbreaks publicly reported by the United States Centers for Disease Control and Prevention’s (US CDC’s) electronic Foodborne Outbreak Reporting System (eFORS) and National Outbreak Reporting System (NORS). We compared monthly trends of completeness during eFORS (1998−2008) and NORS (2009−2019) reporting periods using segmented time series analyses adjusted for seasonality. We quantified the overall, annual, and monthly completeness as the percentage of outbreaks with blank records per our study period, calendar year, and study month, respectively. We found that outbreaks of unknown genus (n = 7401), Norovirus (n = 6414), Salmonella (n = 2872), Clostridium (n = 944), and multiple genera (n = 779) accounted for 80.77% of all outbreaks. However, crude completeness ranged from 46.06% to 60.19% across the 103 variables assessed. Variables with the lowest crude completeness (ranging 3.32−6.98%) included pathogen, specimen etiological testing, and secondary transmission traceback information. Variables with low (<35%) average monthly completeness during eFORS increased by 0.33−0.40%/month after transitioning to NORS, most likely due to the expansion of surveillance capacity and coverage within the new reporting system. Examining completeness metrics in outbreak surveillance systems provides essential information on the availability of data for public reuse. These metadata offer important insights for public health statisticians and modelers to precisely monitor and track the geographic spread, event duration, and illness intensity of foodborne outbreaks.

Surveillance and characteristics of food-borne outbreaks in the Netherlands, 2006 to 2019

Background

A wide variety of pathogens can cause disease in humans via consumption of contaminated food. Although food-borne outbreaks only account for a small part of the food-borne disease burden, outbreak surveillance can provide insights about the pathogens, food products implied as vehicle, points of contamination, and the settings in which transmission occurs.

Aim

To describe the characteristics of food-borne outbreaks registered between 2006 and 2019 in the Netherlands.

Methods

All reported outbreaks in which the first case occurred during 2006–19 were analysed. We examined the number of outbreaks, cases and setting by year, aetiology, type of evidence and food commodities.

Results

In total, 5,657 food-borne outbreaks with 27,711 cases were identified. The contaminated food product could be confirmed in 152 outbreaks (2.7%); in 514 outbreaks (9.1%), a pathogen was detected in cases and/or environmental swabs. Norovirus caused most outbreaks (205/666) and most related cases (4,436/9,532), followed by Salmonella spp. (188 outbreaks; 3,323 cases) and Campylobacter spp. (150 outbreaks; 601 cases). Bacillus cereus was most often found in outbreaks with a confirmed food vehicle (38/152). Additionally, a connection was seen between some pathogens and food commodities. Public eating places were most often mentioned as a setting where the food implicated in the outbreak was prepared.

Conclusion

Long-term analysis of food-borne outbreaks confirms a persistent occurrence. Control and elimination of food-borne illness is complicated since multiple pathogens can cause illness via a vast array of food products and, in the majority of the outbreaks, the pathogen remains unknown.

Phylogenetic Analysis Reveals Source Attribution Patterns for Campylobacter spp. in Tennessee and Pennsylvania

Campylobacteriosis is the most common bacterial foodborne illness in the United States and is frequently associated with foods of animal origin. The goals of this study were to compare clinical and non-clinical Campylobacter populations from Tennessee (TN) and Pennsylvania (PA), use phylogenetic relatedness to assess source attribution patterns, and identify potential outbreak clusters. Campylobacter isolates studied (n = 3080) included TN clinical isolates collected and sequenced for routine surveillance, PA clinical isolates collected from patients at the University of Pennsylvania Health System facilities, and non-clinical isolates from both states for which sequencing reads were available on NCBI. Phylogenetic analyses were conducted to categorize isolates into species groups and determine the population structure of each species. Most isolates were C. jejuni (n = 2132, 69.2%) and C. coli (n = 921, 29.9%), while the remaining were C. lari (0.4%), C. upsaliensis (0.3%), and C. fetus (0.1%). The C. jejuni group consisted of three clades; most non-clinical isolates were of poultry (62.7%) or cattle (35.8%) origin, and 59.7 and 16.5% of clinical isolates were in subclades associated with poultry or cattle, respectively. The C. coli isolates grouped into two clades; most non-clinical isolates were from poultry (61.2%) or swine (29.0%) sources, and 74.5, 9.2, and 6.1% of clinical isolates were in subclades associated with poultry, cattle, or swine, respectively. Based on genomic similarity, we identified 42 C. jejuni and one C. coli potential outbreak clusters. The C. jejuni clusters contained 188 clinical isolates, 19.6% of the total C. jejuni clinical isolates, suggesting that a larger proportion of campylobacteriosis may be associated with outbreaks than previously determined.

Novel Outbreak-Associated Food Vehicles, United States

Novel outbreak-associated food vehicles (i.e., foods not implicated in past outbreaks) can emerge as a result of evolving pathogens and changing consumption trends. To identify these foods, we examined data from the Centers for Disease Control and Prevention Foodborne Disease Outbreak Surveillance System and found 14,216 reported outbreaks with information on implicated foods. We compared foods implicated in outbreaks during 2007–2016 with those implicated in outbreaks during 1973–2006. We identified 28 novel food vehicles, of which the most common types were fish, nuts, fruits, and vegetables; one third were imported. Compared with other outbreaks, those associated with novel food vehicles were more likely to involve illnesses in multiple states and food recalls and were larger in terms of cases, hospitalizations, and deaths. Two thirds of novel foods did not require cooking after purchase. Prevention efforts targeting novel foods cannot rely solely on consumer education but require industry preventive measures.

Recency-Weighted Statistical Modeling Approach to Attribute Illnesses Caused by 4 Pathogens to Food Sources Using Outbreak Data, United States

Foodborne illness source attribution is foundational to a risk-based food safety system. We describe a method for attributing US foodborne illnesses caused by nontyphoidal Salmonella enterica, Escherichia coli O157, Listeria monocytogenes, and Campylobacter to 17 food categories using statistical modeling of outbreak data. This method adjusts for epidemiologic factors associated with outbreak size, down-weights older outbreaks, and estimates credibility intervals. On the basis of 952 reported outbreaks and 32,802 illnesses during 1998–2012, we attribute 77% of foodborne Salmonella illnesses to 7 food categories (seeded vegetables, eggs, chicken, other produce, pork, beef, and fruits), 82% of E. coli O157 illnesses to beef and vegetable row crops, 81% of L. monocytogenes illnesses to fruits and dairy, and 74% of Campylobacter illnesses to dairy and chicken. However, because Campylobacter outbreaks probably overrepresent dairy as a source of nonoutbreak campylobacteriosis, we caution against using these Campylobacter attribution estimates without further adjustment.

Monitoring the incidence and causes of diseases potentially transmitted by food in Australia: Annual report of the OzFoodNet network, 2013-2015

Abstract

This report summarises the incidence of diseases potentially transmitted by food in Australia, and details outbreaks associated with food that occurred during 2013-2015. OzFoodNet sites reported an increasing number of notifications of 12 diseases or conditions vthat may be transmitted by food (botulism; campylobacteriosis; cholera; hepatitis A; hepatitis E; haemolytic uraemic syndrome (HUS); listeriosis; Salmonella Paratyphi (paratyphoid fever) infection; salmonellosis; shigellosis; Shiga toxin-producing Escherichia coli (STEC) infection; and Salmonella Typhi (typhoid fever) infection), with a total of 28,676 notifications received in 2013; 37,958 in 2014; and 41,226 in 2015. The most commonly-notified conditions were campylobacteriosis (a mean of 19,061 notifications per year over 2013-2015) and salmonellosis (a mean of 15,336 notifications per year over 2013-2015). Over these three years, OzFoodNet sites also reported 512 outbreaks of gastrointestinal illness caused by foodborne, animal-to-person or waterborne disease, affecting 7,877 people, and resulting in 735 hospitalisations and 18 associated deaths. The majority of outbreaks (452/512; 88%) were due to foodborne or suspected foodborne transmission. The remaining 12% of outbreaks were due to waterborne or suspected waterborne transmission (57 outbreaks) and animal-to-human transmission (three outbreaks). Foodborne and suspected foodborne outbreaks affected 7,361 people, resulting in 705 hospitalisations and 18 deaths. Salmonella was the most common aetiological agent identified in foodborne outbreaks (239/452; 53%), and restaurants were the most frequently-reported food preparation setting (211/452; 47%). There were 213 foodborne outbreaks (47%) attributed to a single food commodity during 2013-2015, with 58% (124/213) associated with the consumption of eggs and egg-based dishes.

The human health burden of non-typhoidal Salmonella enterica and Vibrio parahaemolyticus foodborne gastroenteritis in Shanghai, east China

Information on the burden of disease due to foodborne pathogens in China is quite limited. To understand the incidence of foodborne gastroenteritis due to non-typhoidal Salmonella enterica and Vibrio parahaemolyticus, population survey and sentinel hospital surveillance were conducted during July 2010 to June 2011 in Shanghai, east China, and a model for calculating disease burden was established. The multiplier for gastroenteritis caused by these pathogens was estimated at 59 [95% confidence interval (CI) 30–102]. Annual incidence per 100,000 population in Shanghai was estimated as 48 (95% CI 24–83) and 183 (95% CI 93–317) cases for foodborne non-typhoidal salmonellosis and V. parahaemolyticus gastroenteritis, respectively, illustrating that bacterial gastroenteritis due to these two pathogens poses a substantial health burden. There is a significant difference between our simulated incidence and the data actually reported for foodborne diseases, indicating significant underreporting and underdiagnosis of non-typhoidal S. enterica and V. parahaemolyticus gastroenteritis in the surveillance area. The present research demonstrates basic situation of the health burden caused by major foodborne pathogens in the surveillance area. Enhanced laboratory-based sentinel hospital surveillance is one of the effective ways to monitor food safety in east China.

Seasonal synchronization of foodborne outbreaks in the United States, 1996-2017

Modern food systems represent complex dynamic networks vulnerable to foodborne infectious outbreaks difficult to track and control. Seasonal co-occurrences (alignment of seasonal peaks) and synchronization (similarity of seasonal patterns) of infections are noted, yet rarely explored due to their complexity and methodological limitations. We proposed a systematic approach to evaluate the co-occurrence of seasonal peaks using a combination of L-moments, seasonality characteristics such as the timing (phase) and intensity (amplitude) of peaks, and three metrics of serial, phase-phase, and phase-amplitude synchronization. We used public records on counts of nine foodborne infections abstracted from CDC's FoodNet Fast online platform for the US and ten representative states from 1996 to 2017 (264 months). Based on annualized and trend-adjusted Negative Binomial Harmonic Regression (NBHR) models augmented with the δ-method, we determined that seasonal peaks of Campylobacter, Salmonella, and Shiga toxin-producing Escherichia Coli (STEC) were tightly clustered in late-July at the national and state levels. Phase-phase synchronization was observed between Cryptosporidium and Shigella, Listeria, and Salmonella (ρ = 0.51, 0.51, 0.46; p < 0.04). Later peak timing of STEC was associated with greater amplitude nationally (ρ = 0.50, p = 0.02) indicating phase-amplitude synchronization. Understanding of disease seasonal synchronization is essential for developing reliable outbreak forecasts and informing stakeholders on mitigation and preventive measures.

An analecta of visualizations for foodborne illness trends and seasonality

Disease surveillance systems worldwide face increasing pressure to maintain and distribute data in usable formats supplemented with effective visualizations to enable actionable policy and programming responses. Annual reports and interactive portals provide access to surveillance data and visualizations depicting temporal trends and seasonal patterns of diseases. Analyses and visuals are typically limited to reporting the annual time series and the month with the highest number of cases per year. Yet, detecting potential disease outbreaks and supporting public health interventions requires detailed spatiotemporal comparisons to characterize spatiotemporal patterns of illness across diseases and locations. The Centers for Disease Control and Prevention's (CDC) FoodNet Fast provides population-based foodborne-disease surveillance records and visualizations for select counties across the US. We offer suggestions on how current FoodNet Fast data organization and visual analytics can be improved to facilitate data interpretation, decision-making, and communication of features related to trend and seasonality. The resulting compilation, or analecta, of 436 visualizations of records and codes are openly available online.

The ADP-Ribosylating Toxins of Salmonella

A number of pathogenic bacteria utilize toxins to mediate disease in a susceptible host. The foodborne pathogen Salmonella is one of the most important and well-studied bacterial pathogens. Recently, whole genome sequence characterizations revealed the presence of multiple novel ADP-ribosylating toxins encoded by a variety of Salmonella serovars. In this review, we discuss both the classical (SpvB) and novel (typhoid toxin, ArtAB, and SboC/SeoC) ADP-ribosylating toxins of Salmonella, including the structure and function of these toxins and our current understanding of their contributions to virulence.

Embracing Diversity: Differences in Virulence Mechanisms, Disease Severity, and Host Adaptations Contribute to the Success of Nontyphoidal Salmonella as a Foodborne Pathogen

Not all Salmonella enterica serovars cause the same disease. S. enterica represents an incredibly diverse species comprising >2,600 unique serovars. While some S. enterica serovars are host-restricted, others infect a wide range of hosts. The diseases that nontyphoidal Salmonella (NTS) serovars cause vary considerably, with some serovars being significantly more likely to cause invasive disease in humans than others. Furthermore, while genomic analyses have advanced our understanding of the genetic diversity of these serovars, they have not been able to fully account for the observed clinical differences. One overarching challenge is that much of what is known about Salmonella's general biology and virulence strategies is concluded from studies examining a select few serovars, especially serovar Typhimurium. As targeted control strategies have been implemented to control select serovars, an increasing number of foodborne outbreaks involving serovars that are less frequently associated with human clinical illness are being detected. Harnessing what is known about the diversity of NTS serovars represents an important factor in achieving the ultimate goal of reducing salmonellosis-associated morbidity and mortality worldwide. In this review we summarize the current understanding of the differences and similarities among NTS serovars, highlighting the virulence mechanisms, genetic differences, and sources that characterize S. enterica diversity and contribute to its success as a foodborne pathogen.

To Be Cytosolic or Vacuolar: The Double Life of Listeria monocytogenes

Intracellular bacterial pathogens are generally classified into two types: those that exploit host membrane trafficking to construct specific niches in vacuoles (i.e., "vacuolar pathogens"), and those that escape from vacuoles into the cytosol, where they proliferate and often spread to neighboring cells (i.e., "cytosolic pathogens"). However, the boundary between these distinct intracellular phenotypes is tenuous and may depend on the timing of infection and on the host cell type. Here, we discuss recent progress highlighting this phenotypic duality in Listeria monocytogenes, which has long been a model for cytosolic pathogens, but now emerges as a bacterium also capable of residing in vacuoles, in a slow/non-growing state. The ability of L. monocytogenes to enter a persistence stage in vacuoles might play a role during the asymptomatic incubation period of listeriosis and/or the carriage of this pathogen in asymptomatic hosts. Moreover, persistent vacuolar Listeria could be less susceptible to antibiotics and more difficult to detect by routine techniques of clinical biology. These hypotheses deserve to be explored in order to better manage the risks related to this food-borne pathogen.

Outbreak-Related Disease Burden Associated with Consumption of Unpasteurized Cow's Milk and Cheese, United States, 2009-2014

The growing popularity of unpasteurized milk in the United States raises public health concerns. We estimated outbreak-related illnesses and hospitalizations caused by the consumption of cow’s milk and cheese contaminated with Shiga toxin–producing Escherichia coli, Salmonella spp., Listeria monocytogenes, and Campylobacter spp. using a model relying on publicly available outbreak data. In the United States, outbreaks associated with dairy consumption cause, on average, 760 illnesses/year and 22 hospitalizations/year, mostly from Salmonella spp. and Campylobacter spp. Unpasteurized milk, consumed by only 3.2% of the population, and cheese, consumed by only 1.6% of the population, caused 96% of illnesses caused by contaminated dairy products. Unpasteurized dairy products thus cause 840 (95% CrI 611–1,158) times more illnesses and 45 (95% CrI 34–59) times more hospitalizations than pasteurized products. As consumption of unpasteurized dairy products grows, illnesses will increase steadily; a doubling in the consumption of unpasteurized milk or cheese could increase outbreak-related illnesses by 96%.

Attribution of global foodborne disease to specific foods: Findings from a World Health Organization structured expert elicitation

BACKGROUND

Recently the World Health Organization, Foodborne Disease Burden Epidemiology Reference Group (FERG) estimated that 31 foodborne diseases (FBDs) resulted in over 600 million illnesses and 420,000 deaths worldwide in 2010. Knowing the relative role importance of different foods as exposure routes for key hazards is critical to preventing illness. This study reports the findings of a structured expert elicitation providing globally comparable food source attribution estimates for 11 major FBDs in each of 14 world subregions.

METHODS AND FINDINGS

We used Cooke's Classical Model to elicit and aggregate judgments of 73 international experts. Judgments were elicited from each expert individually and aggregated using both equal and performance weights. Performance weighted results are reported as they increased the informativeness of estimates, while retaining accuracy. We report measures of central tendency and uncertainty bounds on food source attribution estimate. For some pathogens we see relatively consistent food source attribution estimates across subregions of the world; for others there is substantial regional variation. For example, for non-typhoidal salmonellosis, pork was of minor importance compared to eggs and poultry meat in the American and African subregions, whereas in the European and Western Pacific subregions the importance of these three food sources were quite similar. Our regional results broadly agree with estimates from earlier European and North American food source attribution research. As in prior food source attribution research, we find relatively wide uncertainty bounds around our median estimates.

CONCLUSIONS

We present the first worldwide estimates of the proportion of specific foodborne diseases attributable to specific food exposure routes. While we find substantial uncertainty around central tendency estimates, we believe these estimates provide the best currently available basis on which to link FBDs and specific foods in many parts of the world, providing guidance for policy actions to control FBDs.

Inferring source attribution from a multiyear multisource data set of Salmonella in Minnesota

Salmonella enterica is a global health concern because of its widespread association with foodborne illness. Bayesian models have been developed to attribute the burden of human salmonellosis to specific sources with the ultimate objective of prioritizing intervention strategies. Important considerations of source attribution models include the evaluation of the quality of input data, assessment of whether attribution results logically reflect the data trends and identification of patterns within the data that might explain the detailed contribution of different sources to the disease burden. Here, more than 12,000 non-typhoidal Salmonella isolates from human, bovine, porcine, chicken and turkey sources that originated in Minnesota were analysed. A modified Bayesian source attribution model (available in a dedicated R package), accounting for non-sampled sources of infection, attributed 4,672 human cases to sources assessed here. Most (60%) cases were attributed to chicken, although there was a spike in cases attributed to a non-sampled source in the second half of the study period. Molecular epidemiological analysis methods were used to supplement risk modelling, and a visual attribution application was developed to facilitate data exploration and comprehension of the large multiyear data set assessed here. A large amount of within-source diversity and low similarity between sources was observed, and visual exploration of data provided clues into variations driving the attribution modelling results. Results from this pillared approach provided first attribution estimates for Salmonella in Minnesota and offer an understanding of current data gaps as well as key pathogen population features, such as serotype frequency, similarity and diversity across the sources. Results here will be used to inform policy and management strategies ultimately intended to prevent and control Salmonella infection in the state.

Towards understanding clinical campylobacter infection and its transmission: time for a different approach?

Campylobacter spp. are among the most commonly diagnosed causes of human infection. Methods for detection of the 29 campylobacter species have mainly focused on cultivation of the thermophilic species. More than 99% of clinical campylobacter isolates notified in the UK in the recent past have been from faecal samples and associated with gastroenteritis. Campylobacter enteritis notifications in temperate zones show a seasonal increase during the summer months with a sharp decrease in the winter months, a pattern which remains incompletely understood. The striking seasonality in the expression of many human genes, some concerned with inflammation and immunity, suggests a need for further study of the host regarding the temporal distribution of many human infections, including campylobacteriosis. A tendency for campylobacter to enter a non-cultivable state under adverse conditions effects a reduction in the number of isolations. A Polymerase Chain Reaction (PCR)-based screening approach for the presence of the Campylobacter genus and followed by speciation has provided some insight into the limitations of cultivation for campylobacter, also allowing the discovery of new species. The increased sensitivity of the PCR-based approach over culture-based methods may make it difficult for the laboratory to differentiate asymptomatic campylobacter carriage from clinical campylobacter infection in non-sterile body sites. Campylobacter infection depends on a combination of host factors, and on acquisition of a suitably virulent strain with a tropism for human epithelium. The possibility of persistence of campylobacter in a viable but non-culturable latent form in the human body may also require further investigation. The scope of this review includes a discussion of current methods for diagnosing acute campylobacter infection and for detecting campylobacter in water and foodstuffs. The review also questions the prevailing view that poultry is the most common source of campylobacteriosis.