Foodborne Disease and the Need for Greater Foodborne Disease Surveillance in the Caribbean.
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ABSTRACT:
SUBMITTER: Lee B
PROVIDER: S-EPMC5644654 | biostudies-literature | 2017 Aug
REPOSITORIES: biostudies-literature
Publications
Foodborne Disease and the Need for Greater Foodborne Disease Surveillance in the Caribbean.
Veterinary sciences 20170811 3
The Caribbean is a net importer of food, and with billions of dollars' worth of food products being imported each year, territorial governments are now seeking to encourage local production of foods in an attempt to stem the loss of foreign exchange from these economies with little resilience. The Caribbean, however, lacks the comprehensive food safety system that should be a corollary to successful food production. Regional authorities underestimate the burden of foodborne diseases especially o ...[more]
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Project description:ObjectivesShigella sonnei is a globally important diarrhoeal pathogen tracked through the surveillance network PulseNet Latin America and Caribbean (PNLA&C), which participates in PulseNet International. PNLA&C laboratories use common molecular techniques to track pathogens causing foodborne illness. We aimed to demonstrate the possibility and advantages of transitioning to whole genome sequencing (WGS) for surveillance within existing networks across a continent where S. sonnei is endemic.MethodsWe applied WGS to representative archive isolates of S. sonnei (n = 323) from laboratories in nine PNLA&C countries to generate a regional phylogenomic reference for S. sonnei and put this in the global context. We used this reference to contextualise 16 S. sonnei from three Argentinian outbreaks, using locally generated sequence data. Assembled genome sequences were used to predict antimicrobial resistance (AMR) phenotypes and identify AMR determinants.ResultsS. sonnei isolates clustered in five Latin American sublineages in the global phylogeny, with many (46%, 149 of 323) belonging to previously undescribed sublineages. Predicted multidrug resistance was common (77%, 249 of 323), and clinically relevant differences in AMR were found among sublineages. The regional overview showed that Argentinian outbreak isolates belonged to distinct sublineages and had different epidemiologic origins.ConclusionsLatin America contains novel genetic diversity of S. sonnei that is relevant on a global scale and commonly exhibits multidrug resistance. Retrospective passive surveillance with WGS has utility for informing treatment, identifying regionally epidemic sublineages and providing a framework for interpretation of prospective, locally sequenced outbreaks.
| S-EPMC5667938 | biostudies-literature
Project description:BackgroundFoodborne diseases are a major cause of morbidity and mortality and a major public health problem worldwide. We aim to explore characteristics of foodborne disease outbreaks (FBDOs) in Zhejiang Province and to provide data support for foodborne disease prevention and control. To our knowledge, few such analyses have been published at the provincial level.MethodsDescriptive statistical methods were used to analyze the data reported by centers for disease control (CDC) at all levels in Zhejiang Province through Foodborne Disease Outbreaks Surveillance System (FDOSS) during 2015-2020.ResultsA total of 962 FBDOs were reported during this period, resulting in 8324 illnesses, 1028 hospitalizations, and 20 deaths. The number of outbreaks (410 outbreaks, 42.62%) and cases (4991 cases, 59.96%) caused by bacteria were the largest, followed by poisonous mushrooms (157 outbreaks, 587 cases), which was the main cause of death (15 deaths, 75%). The highest number of FBDOs occurred in households (381 outbreaks, 39.60%), followed by restaurants (219 outbreaks, 22.77%) and canteens (174 outbreaks, 18.08%). Animal-based foods were the most common single food reported (232 outbreaks, 24.12%), followed by poisonous mushrooms (162 outbreaks, 16.84%), and plant-based foods (133 outbreaks, 13.83%). Poisonous mushrooms took the first place in outbreaks in households (38.32%, 146/381), while bacteria took the first place in outbreaks outside households. Vibrio parahaemolyticus was responsible for the largest number of outbreaks (232 outbreaks, 24.12%), which mainly occurred in catering service units (93.10%, 216/232). Different types of bacteria tended to be found in different food categories, such as Vibrio parahaemolyticus, which was mainly found in aquatic products.ConclusionsAnalysis of FBDOs can provide insight into the most important pathogens and sources of foodborne disease, helping authorities identify high-risk etiologies, high-risk foods, and high-risk settings to guide policies that would reduce FBDOs.
| S-EPMC8769373 | biostudies-literature
Project description:Underreporting of foodborne illness makes foodborne disease burden estimation, timely outbreak detection, and evaluation of policies toward improving food safety challenging.The objective of this study was to present and evaluate Iwaspoisoned.com, an openly accessible Internet-based crowdsourcing platform that was launched in 2009 for the surveillance of foodborne illness. The goal of this system is to collect data that can be used to augment traditional approaches to foodborne disease surveillance.Individuals affected by a foodborne illness can use this system to report their symptoms and the suspected location (eg, restaurant, hotel, hospital) of infection. We present descriptive statistics of users and businesses and highlight three instances where reports of foodborne illness were submitted before the outbreaks were officially confirmed by the local departments of health.More than 49,000 reports of suspected foodborne illness have been submitted on Iwaspoisoned.com since its inception by individuals from 89 countries and every state in the United States. Approximately 95.51% (42,139/44,119) of complaints implicated restaurants as the source of illness. Furthermore, an estimated 67.55% (3118/4616) of users who responded to a demographic survey were between the ages of 18 and 34, and 60.14% (2776/4616) of the respondents were female. The platform is also currently used by health departments in 90% (45/50) of states in the US to supplement existing programs on foodborne illness reporting.Crowdsourced disease surveillance through systems such as Iwaspoisoned.com uses the influence and familiarity of social media to create an infrastructure for easy reporting and surveillance of suspected foodborne illness events. If combined with traditional surveillance approaches, these systems have the potential to lessen the problem of foodborne illness underreporting and aid in early detection and monitoring of foodborne disease outbreaks.
| S-EPMC5517822 | biostudies-other
Project description:INTRODUCTIONIn November 2015, the Centers for Disease Control and Prevention (CDC) sent a letter to state and territorial epidemiologists, state and territorial public health laboratory directors, and state and territorial health officials. In this letter, culture-independent diagnostic tests (CIDTs) for detection of enteric pathogens were characterized as "a serious and current threat to public health surveillance, particularly for Shiga toxin-producing Escherichia coli (STEC) and Salmonella" The document says CDC and its public health partners are approaching this issue, in part, by "reviewing regulatory authority in public health agencies to require culture isolates or specimen submission if CIDTs are used." Large-scale foodborne outbreaks are a continuing threat to public health, and tracking these outbreaks is an important tool in shortening them and developing strategies to prevent them. It is clear that the use of CIDTs for enteric pathogen detection, including both antigen detection and multiplex nucleic acid amplification techniques, is becoming more widespread. Furthermore, some clinical microbiology laboratories will resist the mandate to require submission of culture isolates, since it will likely not improve patient outcomes but may add significant costs. Specimen submission would be less expensive and time-consuming for clinical laboratories; however, this approach would be burdensome for public health laboratories, since those laboratories would need to perform culture isolation prior to typing. Shari Shea and Kristy Kubota from the Association of Public Health Laboratories, along with state public health laboratory officials from Colorado, Missouri, Tennessee, and Utah, will explain the public health laboratories' perspective on why having access to isolates of enteric pathogens is essential for public health surveillance, detection, and tracking of outbreaks and offer potential workable solutions which will allow them to do this. Marc Couturier of ARUP Laboratories and Melissa Miller of the University of North Carolina will explain the advantages of CIDTs for enteric pathogens and discuss practical solutions for clinical microbiology laboratories to address these public health needs.
| S-EPMC5228220 | biostudies-other
Project description:Traditional 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.The 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.Structured 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.The 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.By 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.
| S-EPMC6010836 | biostudies-other
Project description:The Greater Caribbean biogeographic region is the high-diversity heart of the Tropical West Atlantic, one of four global centers of tropical marine biodiversity. The traditional view of the Greater Caribbean is that it is limited to the Caribbean, West Indies, southwest Gulf of Mexico and tip of Florida, and that, due to its faunal homogeneity, lacks major provincial subdivisions. In this scenario the northern 2/3 of the Gulf of Mexico and southeastern USA represent a separate temperate, "Carolinian" biogeographic region. We completed a comprehensive re-assessment of the biogeography of the Greater Caribbean by comparing the distributions of 1,559 shorefish species within 45 sections of shelf waters of the Greater Caribbean and adjacent areas. This analysis shows that that the Greater Caribbean occupies a much larger area than usually thought, extending south to at least Guyana, and north to encompass the entire Carolinian area. Rather than being homogenous, the Greater Caribbean is divided into three major provinces, each with a distinctive, primarily tropical fauna: (1) a central, tropical province comprising the West Indies, Bermuda and Central America; (2) a southern, upwelling-affected province spanning the entire continental shelf of northern South America; and (iii) a northern, subtropical province that includes all of the Gulf of Mexico, Florida and southeastern USA. This three-province pattern holds for both reef- and soft bottom fishes, indicating a general response by demersal fishes to major variation in provincial shelf environments. Such environmental differences include latitudinal variation in sea temperature, availability of major habitats (coral reefs, soft bottom shorelines, and mangroves), and nutrient additions from upwelling areas and large rivers. The three-province arrangement of the Greater Caribbean broadly resembles and has a similar environmental basis to the provincial arrangement of its sister biogeographic region, the Tropical Eastern Pacific.
| S-EPMC4108436 | biostudies-literature
Project description:Background:As next generation sequence technology has advanced, there have been parallel advances in genome-scale analysis programs for determining evolutionary relationships as proxies for epidemiological relationship in public health. Most new programs skip traditional steps of ortholog determination and multi-gene alignment, instead identifying variants across a set of genomes, then summarizing results in a matrix of single-nucleotide polymorphisms or alleles for standard phylogenetic analysis. However, public health authorities need to document the performance of these methods with appropriate and comprehensive datasets so they can be validated for specific purposes, e.g., outbreak surveillance. Here we propose a set of benchmark datasets to be used for comparison and validation of phylogenomic pipelines. Methods:We identified four well-documented foodborne pathogen events in which the epidemiology was concordant with routine phylogenomic analyses (reference-based SNP and wgMLST approaches). These are ideal benchmark datasets, as the trees, WGS data, and epidemiological data for each are all in agreement. We have placed these sequence data, sample metadata, and "known" phylogenetic trees in publicly-accessible databases and developed a standard descriptive spreadsheet format describing each dataset. To facilitate easy downloading of these benchmarks, we developed an automated script that uses the standard descriptive spreadsheet format. Results:Our "outbreak" benchmark datasets represent the four major foodborne bacterial pathogens (Listeria monocytogenes, Salmonella enterica, Escherichia coli, and Campylobacter jejuni) and one simulated dataset where the "known tree" can be accurately called the "true tree". The downloading script and associated table files are available on GitHub: https://github.com/WGS-standards-and-analysis/datasets. Discussion:These five benchmark datasets will help standardize comparison of current and future phylogenomic pipelines, and facilitate important cross-institutional collaborations. Our work is part of a global effort to provide collaborative infrastructure for sequence data and analytic tools-we welcome additional benchmark datasets in our recommended format, and, if relevant, we will add these on our GitHub site. Together, these datasets, dataset format, and the underlying GitHub infrastructure present a recommended path for worldwide standardization of phylogenomic pipelines.
| S-EPMC5782805 | biostudies-literature
Project description:Pathogen monitoring is becoming more precise as sequencing technologies become more affordable and accessible worldwide. This transition is especially apparent in the field of food safety, which has demonstrated how whole-genome sequencing (WGS) can be used on a global scale to protect public health. GenomeTrakr coordinates the WGS performed by public-health agencies and other partners by providing a public database with real-time cluster analysis for foodborne pathogen surveillance. Because WGS is being used to support enforcement decisions, it is essential to have confidence in the quality of the data being used and the downstream data analyses that guide these decisions. Routine proficiency tests, such as the one described here, have an important role in ensuring the validity of both data and procedures. In 2015, the GenomeTrakr proficiency test distributed eight isolates of common foodborne pathogens to participating laboratories, who were required to follow a specific protocol for performing WGS. Resulting sequence data were evaluated for several metrics, including proper labelling, sequence quality and new single nucleotide polymorphisms (SNPs). Illumina MiSeq sequence data collected for the same set of strains across 21 different laboratories exhibited high reproducibility, while revealing a narrow range of technical and biological variance. The numbers of SNPs reported for sequencing runs of the same isolates across multiple laboratories support the robustness of our cluster analysis pipeline in that each individual isolate cultured and resequenced multiple times in multiple places are all easily identifiable as originating from the same source.
| S-EPMC6113870 | biostudies-literature
Project description:BackgroundSalmonellosis is one of the most common foodborne diseases worldwide. Although human infection by non-typhoidal Salmonella (NTS) enterica subspecies enterica is associated primarily with a self-limiting diarrhoeal illness, invasive bacterial infections (such as septicaemia, bacteraemia and meningitis) were also reported. Human outbreaks of NTS were reported in several countries all over the world including developing as well as high-income countries. Conventional laboratory methods such as pulsed field gel electrophoresis (PFGE) do not display adequate discrimination and have their limitations in epidemiological surveillance. It is therefore very crucial to use accurate, reliable and highly discriminative subtyping methods for epidemiological characterisation and outbreak investigation.MethodsHere, we used different whole genome sequence (WGS)-based subtyping methods for retrospective investigation of two different outbreaks of Salmonella Typhimurium and Salmonella Dublin that occurred in 2013 in UK and Ireland respectively.ResultsSingle nucleotide polymorphism (SNP)-based cluster analysis of Salmonella Typhimurium genomes revealed well supported clades, that were concordant with epidemiologically defined outbreak and confirmed the source of outbreak is due to consumption of contaminated mayonnaise. SNP-analyses of Salmonella Dublin genomes confirmed the outbreak however the source of infection could not be determined. The core genome multilocus sequence typing (cgMLST) was discriminatory and separated the outbreak strains of Salmonella Dublin from the non-outbreak strains that were concordant with the epidemiological data however cgMLST could neither discriminate between the outbreak and non-outbreak strains of Salmonella Typhimurium nor confirm that contaminated mayonnaise is the source of infection, On the other hand, other WGS-based subtyping methods including multilocus sequence typing (MLST), ribosomal MLST (rMLST), whole genome MLST (wgMLST), clustered regularly interspaced short palindromic repeats (CRISPRs), prophage sequence profiling, antibiotic resistance profile and plasmid typing methods were less discriminatory and could not confirm the source of the outbreak.ConclusionsFoodborne salmonellosis is an important concern for public health therefore, it is crucial to use accurate, reliable and highly discriminative subtyping methods for epidemiological surveillance and outbreak investigation. In this study, we showed that SNP-based analyses do not only have the ability to confirm the occurrence of the outbreak but also to provide definitive evidence of the source of the outbreak in real-time.
| S-EPMC7993512 | biostudies-literature
Project description:Precision medicine, currently a hotspot in mainstream medicine, has been strongly promoted in recent years. With rapid technological development, such as next-generation sequencing, and fierce competition in molecular targeted drug exploitation, precision medicine represents an advance in science and technology; it also fulfills needs in public health care. The clinical translation and application of precision medicine - especially in the prevention and treatment of tumors - is far from satisfactory; however, the aims of precision medicine deserve approval. Thus, this medical approach is currently in its infancy; it has promising prospects, but it needs to overcome numbers of problems and deficiencies. It is expected that in addition to conventional symptoms and signs, precision medicine will define disease in terms of the underlying molecular characteristics and other environmental susceptibility factors. Those expectations should be realized by constructing a novel data network, integrating clinical data from individual patients and personal genomic background with existing research on the molecular makeup of diseases. In addition, multi-omics analysis and multi-discipline collaboration will become crucial elements in precision medicine. Precision medicine deserves strong support, and its development demands directed momentum. We propose three kinds of impetus (research, application and collaboration impetus) for such directed momentum toward promoting precision medicine and accelerating its clinical translation and application.
| S-EPMC5537174 | biostudies-other