Foodborne Disease Surveillance Research Articles

Evaluation of REDCap to Supplement Foodborne Disease Surveillance Systems

ObjectiveThe objective of this study is to evaluate the use of a supplementary data management application to meet surveillance demands for foodborne disease in Tennessee and to highlight successes, challenges, and opportunities identified through this process.IntroductionThe Tennessee Department of Health (TDH) Foodborne Disease Program conducts routine surveillance for foodborne illnesses and enteric disease outbreaks and participates in statewide enhanced surveillance as part of the Foodborne Disease Center for Outbreak Response Enhancement (FoodCORE) and the Foodborne Diseases Active Surveillance Network (FoodNet) supported by the Centers for Disease Control and Prevention (CDC). TDH uses the CDC NEDSS Base System (NBS) application for routine disease surveillance. However, NBS serves multiple disease programs within TDH and modifications to the system for the rapidly changing data demands, grant requirements, and outbreak needs of the foodborne program, may not be a priority for the system as a whole. In 2014, the TDH Foodborne Disease Program began using the Research Electronic Data Capture (REDCap) application as a solution to changing surveillance needs. FoodCORE, FoodNet, and routine surveillance data elements are entered into REDCap to supplement NBS, depending on program specific needs and system capability.MethodsREDCap was queried for FoodCORE, FoodNet, and routine surveillance projects. Projects were categorized by surveillance activity type. Epidemiologists provided qualitative feedback on successes and challenges in using REDCap to supplement NBS, which were then categorized into attributes according to existing frameworks for evaluating public health surveillance systems.1, 2ResultsAs of August 2018, the TDH Foodborne program housed 45 individual REDCap databases dedicated to surveillance. Four primary database categories were identified: routine case-based surveillance (8), enhanced/active surveillance (6), aggregate outbreak/cluster surveillance tracking (6), and outbreak-specific databases (25). The REDCap application programming interface (API) and an open database connection to NBS within SAS 9.4 (Cary, NC) were used to create unilateral data flow from NBS to REDCap, where possible. Successes and challenges in using REDCap fell into six main surveillance system attributes: Flexibility, Ease of Data Management, Stability, Simplicity, Efficiency, and Acceptability. Successes included the high level of control over data and databases offered by REDCap, the flexibility to rapidly implement program-specific changes, and the accessibility and reliability of REDCap as a de facto back-up of NBS data. Challenges included lack of interoperability between REDCap databases and with NBS, leading to dual data entry, overuse of REDCap resulting in unnecessarily complex and decentralized data storage (Figure 1), and increased personnel time on data management and extraction for metrics and reports.ConclusionsUsing REDCap in Tennessee to supplement an existing disease surveillance application increased flexibility and functionality of the foodborne disease surveillance system, but also added complexity and time involved in data management. The Nationally Notifiable Diseases Surveillance System Modernization Initiative (NMI) is developing a standardized message mapping guide (MMG) in collaboration with states and CDC, which incorporates FoodNet data elements and would transition data collection tools in NBS for foodborne diseases to a more portable and flexible format. Implementation of this MMG could minimize case-based data entry into REDCap. Tools that offer increased interoperability between NBS and REDCap and between REDCap databases could also improve the efficiency of using complementary applications for rapidly changing foodborne disease surveillance needs.

Descriptive Study of Foodborne Disease Using Case Monitoring Data in Shandong Province, China, 2016-2017

In order to generate data on the burden of foodborne diseases in Shandong Province, we aimed to use the case monitoring data of foodborne diseases from 2016 to 2017 to estimate. Data were obtained from the foodborne disease surveillance reporting system with dates of onset from Jan 1, 2016, to Dec 31, 2017, in Shandong, China. The places of food exposure were categorized by settings as follows: private home, catering facility, collective canteens, retail markets, rural banquets and other. Exposed food is divided into 23 categories. Overall incidence rate and proportions by exposure categories, age, and sex-specific incidence rates were calculated and sex proportions compared. Approximately 75.00% of cases who had at least one exposure settings were in private homes. The most frequently reported exposed food was a variety of food (meaning more than two kinds of food). The two-year average incidence rate was 75.78/100,000, sex-specific incidence rate was much higher for females compared to males (78.23 vs. 74.69 cases per 100,000 population). An age-specific trend was observed in the cases reported (Chi-Square for linear trend, χ2=4.39, P=0.036<0.05). A preliminary estimate of 14 million cases of foodborne diseases in Shandong province each year. Future studies should focus on cross-sectional and cohort studies to facilitate the assessment of the distribution and burden of foodborne disease of the population in Shandong. Considering strengthening the burden of foodborne diseases in foodborne disease surveillance is also a feasible way.

Investigation of Listeriosis-Related Knowledge, Attitudes, and Practices Among Medical Staff in Fangshan, Beijing, China.

The aim of this study was to gain insight into the knowledge of, attitude toward, and practical experience with listeriosis among medical staff. In two hospitals in Fangshan, Beijing, 410 medical staff members were randomly selected using a random sampling method. Each selected staff member was invited to participate in a standardized questionnaire interview. In total, 397 valid questionnaires were collected. With regard to the staff members' general knowledge of listeriosis, they answered 65.96% of the items correctly. The knowledge scores among obstetricians and gynecologists were higher than those of other clinical doctors (p < 0.05); however, obstetricians and gynecologists were less knowledgeable about which drugs are effective against listeriosis than the other doctors (p = 0.007). The percentage of participants with a positive attitude about preventing listeriosis was 96.47%, the percentage with practice formation was 52.39%. The medical staff's mean score for knowledge of listeriosis was 4.61 ± 1.83. The mean score for attitude toward listeriosis was 9.71 ± 1.31. There was a significant association between attitude and knowledge of listeriosis (r = 0.221, p < 0.001). Medical staff obtained a mean score of 2.10 ± 1.07 for the practice formation. There was a significant association between practice formation and knowledge of listeriosis (r = 0.502, p < 0.001). The mean knowledge-attitude-practice (KAP) score for listeriosis among medical staff was 16.41 ± 3.19. The KAP scores were significantly correlated with age (r = 0.129, p = 0.011), occupation (r = -0.103, p = 0.041), department (r = -0.168, p = 0.001), and professional title (r = 0.166, p = 0.001). To improve medical outcomes and foodborne disease surveillance, medical staff should receive more training on listeriosis and the content of the training should be adjusted.

Listeria contamination in chevon and mutton from retail meat shops and slaughter house environment of Punjab, India.

Listeria monocytogenes is recognized as an emerging pathogen, with limited information or statistics on this pathogen. Moreover, poor hygienic practices in the unorganized meat sector favor its growth and survival. Therefore, the present study was carried out in Punjab, India to assess the prevalence of Listeria spp. in chevon and mutton samples, followed by its characterization. The prevalence of Listeria in chevon, mutton and swab samples collected from butchers' shops and slaughter houses was 1.82%, 3.21% and 6.66%, respectively. The 18 (2.67%) L. monocytogenes strains isolated from 786 samples carried one or more virulence-associated gene. Based on virulence genes, 6/18 isolates were potentially pathogenic. Serovar 4b (44.4%) was predominant, followed by serovars 1/2a (22.2%), 1/2b (22.2%) and 1/2c (11.1%). Detection of L. monocytogenes in meat and environment samples indicated poor hygiene, potential cross-contamination and risk of listeriosis to consumers and occupational workers. The findings of the study were also relevant to the fact that most of the slaughtering in Punjab, India is carried out in unorganized way, and this meat is not stored propery. Moreover, in the absence of a systematic foodborne disease surveillance and monitoring program, a database on foodborne diseases is absent, and needs to be established.

Changing epidemiology of Listeria monocytogenes outbreaks, sporadic cases, and recalls globally: A review of ProMED reports from 1996 to 2018

BackgroundThe purpose of this study was to identify global trends in Listeria monocytogenes epidemiology using ProMED reports. ProMED is a publicly available, global outbreak reporting system that uses both informal and formal sources. In the context of Listeria, ProMED reports on atypical findings such as higher than average case counts, events from unusual sources, and multinational outbreaks. MethodsKeywords “Listeria” and “listeriosis” were utilized in the ProMED search engine covering the years 1996–2018. Issue date, countries involved, source, suspected and confirmed case counts, and fatalities were extracted. Data unique to each event, including commentary by content experts, were evaluated. When multiple reports regarding the same outbreak or recall were obtained, the last report pertaining to that outbreak was utilized. Rates of Listeria events over time were compared using a normal approximation to the Poisson distribution; p < 0.05 was considered to be statistically significant. ResultsFrom 1996 through 2018, 123 Listeria events were identified in the ProMED database. Eighty-one events (65%) were associated with two or more human cases (outbreak events), 13 events (11%) were associated with only one human case (sporadic cases), and 29 events (24%) were precautionary food product recalls due to the presence of bacterial contamination without associated human cases. The implicated food vehicle was identified in 69 (85%) outbreak events and in 10 (77%) sporadic case events. Listeria contaminated foods were identified in all precautionary recall events. Overall, 28 events (23%) implicated novel food vehicles/sources. Events associated with novel food vehicles increased over the study period (p < 0.02), as did international events with more than one country involved (p < 0.02). Ten reports (8%) described hospital-acquired events. ConclusionsThis study demonstrates the use of publicly available data to document Listeria epidemiological trends, particularly in settings where foodborne disease surveillance is weak or non-existent. Over the last decade, an increasing number of events have been associated with foods not traditionally recognized as vehicles for Listeria transmission, and a rise in international events was noted. Informing high-risk individuals such as pregnant women and immunocompromised individuals of safe food handling practices is warranted. To ensure timely recall of contaminated food products, open data sharing and communication across borders is critical. Changes in food production and distribution, and improved diagnostics may have contributed to the observed changes.

Estimated Annual Deaths, Hospitalizations, and Emergency Department and Physician Office Visits from Foodborne Illness in Ontario.

Public Health Ontario is working to estimate the burden of disease from environmental hazards in Ontario, Canada. As part of this effort, we estimated deaths and health care utilization resulting from exposure to pathogens and toxic substances in food. We applied fractions for the proportion of illness attributable to foodborne transmission to the annual (2008–2012) counts of deaths, hospitalizations, emergency department (ED) visits, and physician office visits for 15 diseases (13 pathogen-specific diseases and 2 nonspecific syndromes) captured by administrative health data. Nonspecific gastroenteritis (causative agent unknown) was the dominant disease, accounting for 98% of ED visits, 94% of hospitalizations, and 88% of deaths annually attributed to the 15 diseases. We estimated that foodborne nonspecific gastroenteritis results in ∼137,000 physician office visits (1000/100,000 population), 40,000 ED visits (310/100,000), 6200 hospitalizations (47/100,000), and 59 deaths (0.45/100,000) in Ontario per year (mean estimates). Our results indicate that pathogen-specific approaches to foodborne disease surveillance can substantially underestimate the deaths and illness resulting from exposure to foodborne pathogens and other causes of foodborne illness.

Evaluation of whole-genome sequencing for outbreak detection of Verotoxigenic Escherichia coli O157:H7 from the Canadian perspective

BackgroundRapid and accurate identification of Verotoxigenic Escherichia coli (VTEC) O157:H7 is dependent on well-established, standardized and highly discriminatory typing methods. Currently, conventional subtyping tests for foodborne bacterial pathogen surveillance are rapidly being replaced with whole-genome sequencing (WGS) in public health laboratories. The capacity of WGS to revolutionize global foodborne disease surveillance has positioned this tool to become the new gold standard; however, to ensure evidence standards for public health decision making can still be achieved, the performance of WGS must be thoroughly validated against current gold standard methods prior to implementation. Here we aim to verify the performance of WGS in comparison to pulsed-field gel electrophoresis (PFGE) and multiple-locus variable-number tandem repeat analysis (MLVA) for eight retrospective outbreaks of VTEC O157:H7 from the Canadian perspective. Since real-time implementation and routine use of WGS in public health laboratories is highly reliant on standardized data analysis tools, we also provide a comparative analysis of two popular methodologies for WGS analyses; an in-house developed single nucleotide variant phylogenomics (SNVPhyl) pipeline and the BioNumerics whole genome multilocus sequence typing (wgMLST) tool. To provide a useful and consistent starting point for examining laboratory-based surveillance data for VTEC O157:H7 in Canada, we also aim to describe the number of genetic differences observed among outbreak-associated isolates.ResultsWGS provided enhanced resolution over traditional subtyping methods, and accurately distinguished outbreak-related isolates from non-outbreak related isolates with high epidemiological concordance. WGS also illuminated potential linkages between sporadic cases of illness and contaminated food, and isolates spanning multiple years. The topologies generated by SNVPhyl and wgMLST were highly congruent with strong statistical support. Few genetic differences were observed among outbreak-related isolates (≤5 SNVs/ < 10 wgMLST alleles) unless the outbreak was suspected to be multi-strain.ConclusionsThis study validates the superiority of WGS and indicates the BioNumerics wgMLST schema is suitable for surveillance and cluster detection of VTEC O157:H7. These findings will provide a useful and consistent starting point for examining WGS data for prospective laboratory-based surveillance of VTEC O157:H7, but however, the data will continue to be interpreted according to context and in combination with epidemiological and food safety evidence to inform public-health decision making in Canada.

Retrospective case analysis of crayfish-transmitted Haff disease in China during 2016–2017

Haff disease is an unexplained rhabdomyolysis syndrome occurring within 24 h of consumption of certain types of cooked fish or crustaceans. The current epidemiological status of crayfish-transmitted Haff disease in China was investigated by analyzing retrospective data linked with cases of the rhabdomyolysis syndrome recorded during the period 2016–2017. This information was acquired from the National Foodborne Disease Surveillance and Reporting System. These data were filtered, based on the disease definition and a markedly elevated serum creatine phosphokinase level, that is, fivefold or greater increase than normal levels. Data analysis indicated that crayfish-transmitted Haff disease was mainly concentrated in the middle and lower reaches of the Yangtze River Valley, and the current epidemiological curve was notable seasonal. Most patients were aged 20–49 years and the proportion of female patients was higher than male patients. Based on this initial study, it will be necessary to follow up the trace-back investigation of crayfish poisoning reports; further analyze the correlation between the aquatic environment of the associated crayfish together with establishing virulence factors of crayfish-transmitted Haff disease; and explore whether certain individuals have receptor pathways to trigger rhabdomyolysis syndrome.

Outbreak of Salmonella Chailey Infections Linked To Precut Coconut Pieces - United States and Canada, 2017.

Foodborne salmonellosis causes an estimated 1 million illnesses and 400 deaths annually in the United States (1). In recent years, salmonellosis outbreaks have been caused by foods not typically associated with Salmonella. On May 2, 2017, PulseNet, CDC's national molecular subtyping network for foodborne disease surveillance, identified a cluster of 14 Salmonella Chailey isolates with a rare pulsed-field gel electrophoresis (PFGE) pattern. On May 29, Canadian health officials informed CDC that they were also investigating a cluster of five Salmonella Chailey infections in British Columbia with the same PFGE pattern. Nineteen cases were identified and investigated by CDC, U.S. state health departments, the Public Health Agency of Canada, and the British Columbia Centre for Disease Control. Isolates from all cases were highly related by whole genome sequencing (WGS). Illness onset dates ranged from March 10 to May 7, 2017. Initial interviews revealed that infected persons consumed various fresh foods and shopped at grocery chain A; focused questionnaires identified precut coconut pieces from grocery chain A as a common vehicle. The Canadian Food Inspection Agency (CFIA) and the U.S. Food and Drug Administration (FDA) conducted a traceback investigation that implicated a single lot of frozen, precut coconut as the outbreak source. Grocery chain A voluntarily removed precut coconut pieces from their stores. This action likely limited the size and scope of this outbreak.

Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques.

BackgroundTraditional methods of monitoring foodborne illness are associated with problems of untimeliness and underreporting. In recent years, alternative data sources such as social media data have been used to monitor the incidence of disease in the population (infodemiology and infoveillance). These data sources prove timelier than traditional general practitioner data, they can help to fill the gaps in the reporting process, and they often include additional metadata that is useful for supplementary research.ObjectiveThe aim of the study was to identify and formally analyze research papers using consumer-generated data, such as social media data or restaurant reviews, to quantify a disease or public health ailment. Studies of this nature are scarce within the food safety domain, therefore identification and understanding of transferrable methods in other health-related fields are of particular interest.MethodsStructured scoping methods were used to identify and analyze primary research papers using consumer-generated data for disease or public health surveillance. The title, abstract, and keyword fields of 5 databases were searched using predetermined search terms. A total of 5239 papers matched the search criteria, of which 145 were taken to full-text review—62 papers were deemed relevant and were subjected to data characterization and thematic analysis.ResultsThe majority of studies (40/62, 65%) focused on the surveillance of influenza-like illness. Only 10 studies (16%) used consumer-generated data to monitor outbreaks of foodborne illness. Twitter data (58/62, 94%) and Yelp reviews (3/62, 5%) were the most commonly used data sources. Studies reporting high correlations against baseline statistics used advanced statistical and computational approaches to calculate the incidence of disease. These include classification and regression approaches, clustering approaches, and lexicon-based approaches. Although they are computationally intensive due to the requirement of training data, studies using classification approaches reported the best performance.ConclusionsBy analyzing studies in digital epidemiology, computer science, and public health, this paper has identified and analyzed methods of disease monitoring that can be transferred to foodborne disease surveillance. These methods fall into 4 main categories: basic approach, classification and regression, clustering approaches, and lexicon-based approaches. Although studies using a basic approach to calculate disease incidence generally report good performance against baseline measures, they are sensitive to chatter generated by media reports. More computationally advanced approaches are required to filter spurious messages and protect predictive systems against false alarms. Research using consumer-generated data for monitoring influenza-like illness is expansive; however, research regarding the use of restaurant reviews and social media data in the context of food safety is limited. Considering the advantages reported in this review, methods using consumer-generated data for foodborne disease surveillance warrant further investment.

Protracted Outbreak of Salmonella Newport Infections Linked to Ground Beef: Possible Role of Dairy Cows — 21 States, 2016–2017

In January 2017, CDC identified a cluster of Salmonella enterica serotype Newport infections with isolates sharing an indistinguishable pulsed-field gel electrophoresis (PFGE) pattern, JJPX01.0010 (pattern 10), through PulseNet, the national molecular subtyping network for foodborne disease surveillance. This report summarizes the investigation by CDC, state and local health and agriculture departments, and the U.S. Department of Agriculture's Food Safety and Inspection Service (USDA-FSIS) and discusses the possible role of dairy cows as a reservoir for strains of Salmonella that persistently cause human illness. This investigation combined epidemiologic and whole genome sequencing (WGS) data to link the outbreak to contaminated ground beef; dairy cows were hypothesized to be the ultimate source of Salmonella contamination.

Molecular ecology of Listeria spp., Salmonella, Escherichia coli O157:H7 and non-O157 Shiga toxin-producing E.coli in pristine natural environments in Northern Colorado.

Molecular subtyping is commonly used in foodborne disease surveillance and microbial source tracking. There is a knowledge gap regarding the molecular ecology of foodborne pathogens in non-food-associated environments. The objective of this study was to isolate and subtype foodborne pathogens from pristine natural environments with minimal anthropogenic inputs. Five locations (wilderness areas) in Northern Colorado were sampled during the spring, summer and fall over a 2-year period. Soil, water, sediment, surface soil and wildlife faecal samples were microbiologically analysed to detect Listeria, Salmonella and Shiga toxin-producing Escherichia coli (STEC), and resultant isolates were subtyped. Three samples tested positive for Listeria monocytogenes and 19 samples contained other Listeria spp. Salmonella was isolated from two samples, five samples contained non-O157 STEC, and E.coli O157:H7 was not detected. Two L. monocytogenes isolates from faecal samples collected from the same wilderness area over a year apart shared the same PFGE pattern, while all other isolates had a unique type. Our data indicate that (i) there was a rare presence of human foodborne pathogens in pristine natural environments in Northern Colorado, (ii) there was genetic diversity between organisms isolated within a given wilderness area, and (iii) the Northern Colorado climate and topography may contribute to the low occurrence of these organisms. Relatively little is known about the molecular ecology of foodborne pathogens in pristine natural environments. While foodborne pathogens were rarely detected in wildlife faecal and environmental samples from the wilderness areas in this study, some isolates shared DNA fingerprint types with human clinical isolates from same region during the same time frame, highlighting the need for environmental isolate subtype data. The availability of molecular subtyping data for non-food-associated foodborne pathogen isolates can facilitate epidemiological and microbial source tracking investigations.

National molecular tracing network for foodborne disease surveillance in China

To improve the early detection of geographically dispersed common-source foodborne outbreaks, a national foodborne disease molecular tracing network (TraNet) was launched in 2013 based on the existing laboratory-based foodborne disease surveillance system in China. TraNet consists of 32 provincial and many municipal Centers for Disease Control and Prevention that conduct molecular subtyping using pulsed-field gel electrophoresis (PFGE) on foodborne pathogens submitted by sentinel hospitals within their jurisdictions, and submit these PFGE profiles to a national database for further analysis. Currently, TraNet plays a significant role in the identification of etiologic causes and tracks contaminated food during foodborne outbreaks.

Trends of foodborne diseases in China: lessons from laboratory-based surveillance since 2011.

Foodborne disease is one of the most important public health issues worldwide. China faces various and unprecedented challenges in all aspects of the food chain. Data from laboratory-based foodborne disease surveillance systems from 2013 to 2016, as well as different regions and ages, can be found along with differences in the patterns of pathogens detected with diverse characteristics. Vibrio parahaemolyticus has been the leading cause of infectious diarrhea in China, especially among adults in coastal regions. Salmonella has been a serious and widely distributed pathogen responsible for substantial socioeconomic burden. Shigella was mostly identified in Northwest China and the inland province (Henan) with less-developed regions among children under 5 years. Data from foodborne disease outbreak reporting system from 2011 to 2016 showed that poisonous animals and plant factors responsible for most deaths were poisonous mushrooms (54.7%) in remote districts in southwest regions. The biological hazard that caused most cases reported (42.3%) was attributed to V. parahaemolyticus, the leading cause of foodborne outbreaks. In this review, we summarize the recent monitoring approach to foodborne diseases in China and compare the results with those in developed countries.

Estimating the Type II error of detecting changes in foodborne illnesses via public health surveillance

Many countries operate public health surveillance systems to monitor foodborne disease occurrence. The illness counts for pathogens of interest are monitored across time to assess if changes have occurred in case rates or the overall illness burden. Common to all of these systems is that only a fraction of all foodborne illnesses are reported and the relationship between observed and the total number of illnesses is uncertain.Food-safety policies intend to affect both the total and observed number of illnesses. Ideally, the surveillance system would be sufficiently sensitive to detect these changes, but the statistical power of these systems is generally not well understood. This study proposes two approaches for estimating the power of a foodborne illness surveillance system. These methods are then applied to assess the power of detecting specified changes in the total number of illnesses in an existing surveillance system.The findings suggest that the power of a national foodborne disease surveillance system to detect modest annual reductions in Salmonella illnesses may be limited. For example, a naïve presumptive model that assumes observed illnesses are reduced directly by 10% predicts that the power to discern this difference, from one year to the next, is 0.21. A Bayesian model, that accounts for uncertainty in projecting changes in total illnesses to the number of observed illnesses, predicts that the power to detect a true 10% reduction is 0.04 (i.e., 4% confidence of detecting this magnitude of reduction or 96% chance of a Type II error) one year after the change has taken effect. Although the power of a national surveillance system increases as the magnitude of reductions increases – or as the number of years the reduction is maintained increases – the Bayesian model demonstrates that power is less than 0.5 for reductions up to 50% for one year and is less than 0.53 for reductions of 30% that are maintained for four years.The limited power to detect intended changes in total annual illnesses of national public health surveillance systems may highlight the need for regulators to also monitor food contamination evidence to gauge progress towards achieving intended policy effects.

Whole genome sequencing analysis of Salmonella enterica serovar Weltevreden isolated from human stool and contaminated food samples collected from the Southern coastal area of China

Salmonella enterica serovar Weltevreden is the most common non-typhoid Salmonella found in South and Southeast Asia. It causes zoonoses worldwide through the consumption of contaminated foods and seafood, and is considered as an important food-borne pathogen in China, especially in the Southern coastal area. We compared the whole genomes of 44 S. Weltevreden strains isolated from human stool and contaminated food samples from Southern Coastal China, in order to investigate their phylogenetic relationships and establish their genetic relatedness to known international strains. ResFinder analysis of the draft genomes of isolated strains detected antimicrobial resistance (AMR) genes in only eight isolates, equivalent to minimum inhibitory concentration assay, and only a few isolates showed resistance to tetracycline, ciprofloxacin or ampicillin. In silico MLST analysis revealed that 43 out of 44 S. Weltevreden strains belonged to sequence type 365 (CC205), the most common sequence type of the serovars. Phylogenetic analysis of the 44 domestic and 26 international isolates suggested that the population of S. Weltevreden could be segregated into six phylogenetic clusters. Cluster I included two strains from food and strains of the “Island Cluster”, indicating potential inter-transmission between different countries and regions through foods. The predominant S. Weltevreden isolates obtained from the samples from Southern coastal China were found to be phylogenetically related to strains from Southern East Asia, and formed clusters II–VI. The study has demonstrated that WGS-based analysis may be used to improve our understanding of the epidemiology of this bacterium as part of a food-borne disease surveillance program. The methods used are also more widely applicable to other geographical regions and areas and could therefore be useful for improving our understanding of the international spread of S. Weltevreden on a global scale.

Surveillance for foodborne disease outbreaks in China, 2003 to 2008

Knowledge of implicated food vehicles and contributing factors derived from foodborne disease outbreak (FBDO) investigations allows consumers to be educated on decreasing high-risk behavior to reduce the risk of being affected by foodborne diseases. Food safety regulatory authorities also need summary of outbreak data, as these data indicate where the existing food supply system should be improved. To obtain information on epidemiology of FBDOs in China, FBDOs reported to the China National Foodborne Diseases Surveillance Network by 12 surveillance provinces that include 43% of the Chinese population was summarized. Between 2003 and 2008, 2795 FBDOs were reported, resulting in 62559 illnesses, 31261 hospitalizations, and 330 deaths. Outbreak size ranged from 2 to 464 cases, with a median of 14 cases. The outbreak rate had decreased from 1.37 per 1 million population in 2003 to 0.46 per 1 million population in 2008. Of the 2176 outbreaks with a single known etiology, bacteria (1051 outbreaks, 48%), man-made chemical hazards (550 outbreaks, 25%), and animal and plant toxins (536 outbreaks, 25%) were the main courses. Only one outbreak was caused by virus. Of the 1930 outbreaks with a single commodity, plant-based foods were the most common reported (930 outbreaks, 48%), followed by animal-based foods (590 outbreaks, 31%). Outbreaks most frequently occurred in private residences (32%), workplace cafeterias (21%), and restaurants (17%). The most common factor reported in the 2190 outbreaks with known contributing factors were improper cooking (510 outbreaks, 23%), contaminated ingredient (503 outbreaks, 23%), cross contamination (475 outbreaks, 22%) and improper storage (295 outbreaks, 13%). It is considered that FBDOs continue to be an important public health problem in China.

Molecular characterization genetic diversity of extended-spectrum β-lactamases-harboring conjugative plasmids identified in multi-drug resistant Escherichia coli isolated from food in China

Objective: The purpose of this study was to investigate the molecular characteristics of ESBL-encoding conjugative plasmid identified in muti-drug resistant Escherichia coli isolated from food. Methods: 465 Escherichia coli isolates were collected from national foodborne disease surveillance net from 2013 to 2014 (salad, n=159; meat, n=102; processed meat, n=95; cakes/rice, n=46; cooked dish, n=63). ESBLs strain was detected by Mueller-Hinton agar plate, and then its drug resistance was tested by agar dilution method. Polymerase chain reaction (PCR) and DNA sequencing were performed to identify the corresponding ESBL genes. Plasmids were typed by PCR-based replicon typing and their characteristics were determined by S1-nuclease pulsed-field gel electrophoresis method. Broth mating assays were carried out for all isolates to determine whether the ESBL marker could be transferred by conjugation. Results: 12 E. coli were found to be resistant to cefotaxime, and all of which were confirmed as ESBLs. The 12 isolates all carried different types of CTX-M genes resistant to drug, and 7 of which carried TEM type as well. All 12 isolates contained at least one plasmid and some had four plasmids, with size ranging from 47-to 220-kb by S1-PFGE anaylsis. Seven isolates demonstrated the ability to transfer their cefotaxime resistance marker to the recotper strain J53 by only one plasmid. Conclusion: This study highlights the diversity of the multi-drug resistant E. coli and also the diversity of ESBL genes in China. Plasmids carrying these genes poses a serious threat to food safety in China.

Metagenomics: The Next Culture-Independent Game Changer.

A trend towards the abandonment of obtaining pure culture isolates in frontline laboratories is at a crossroads with the ability of public health agencies to perform their basic mandate of foodborne disease surveillance and response. The implementation of culture-independent diagnostic tests (CIDTs) including nucleic acid and antigen-based assays for acute gastroenteritis is leaving public health agencies without laboratory evidence to link clinical cases to each other and to food or environmental substances. This limits the efficacy of public health epidemiology and surveillance as well as outbreak detection and investigation. Foodborne outbreaks have the potential to remain undetected or have insufficient evidence to support source attribution and may inadvertently increase the incidence of foodborne diseases. Next-generation sequencing of pure culture isolates in clinical microbiology laboratories has the potential to revolutionize the fields of food safety and public health. Metagenomics and other ‘omics’ disciplines could provide the solution to a cultureless future in clinical microbiology, food safety and public health. Data mining of information obtained from metagenomics assays can be particularly useful for the identification of clinical causative agents or foodborne contamination, detection of AMR and/or virulence factors, in addition to providing high-resolution subtyping data. Thus, metagenomics assays may provide a universal test for clinical diagnostics, foodborne pathogen detection, subtyping and investigation. This information has the potential to reform the field of enteric disease diagnostics and surveillance and also infectious diseases as a whole. The aim of this review will be to present the current state of CIDTs in diagnostic and public health laboratories as they relate to foodborne illness and food safety. Moreover, we will also discuss the diagnostic and subtyping utility and concomitant bias limitations of metagenomics and comparable detection techniques in clinical microbiology, food and public health laboratories. Early advances in the discipline of metagenomics, however, have indicated noteworthy challenges. Through forthcoming improvements in sequencing technology and analytical pipelines among others, we anticipate that within the next decade, detection and characterization of pathogens via metagenomics-based workflows will be implemented in routine usage in diagnostic and public health laboratories.

Multistate Outbreak of Salmonella Anatum Infections Linked to Imported Hot Peppers - United States, May-July 2016.

Foodborne salmonellosis causes an estimated 1 million illnesses and 400 deaths annually in the United States (1). Salmonella Anatum is one of the top 20 Salmonella serotypes in the United States. During 2013-2015 there were approximately 300-350 annual illnesses reported to PulseNet, the national molecular subtyping network for foodborne disease surveillance. In June 2016, PulseNet identified a cluster of 16 Salmonella Anatum infections with an indistinguishable pulsed-field gel electrophoresis (PFGE) pattern from four states.* In April 2016, the same PFGE pattern had been uploaded to PulseNet from an isolate obtained from an Anaheim pepper, a mild to medium hot pepper. Hot peppers include many pepper varieties, such as Anaheim, jalapeño, poblano, and serrano, which can vary in heat level from mild to very hot depending on the variety and preparation. This rare PFGE pattern had been seen only 24 times previously in the PulseNet database, compared with common PFGE patterns for this serotype which have been seen in the database hundreds of times. Local and state health departments, CDC, and the Food and Drug Administration (FDA) investigated to determine the cause of the outbreak. Thirty-two patients in nine states were identified with illness onsets from May 6-July 9, 2016. Whole-genome sequencing (WGS) was performed to characterize clinical isolates and the Anaheim pepper isolate further. The combined evidence indicated that fresh hot peppers were the likely source of infection; however, a single pepper type or source farm was not identified. This outbreak highlights challenges in reconciling epidemiologic and WGS data, and the difficulties of identifying ingredient-level exposures through epidemiologic investigations alone.