OBJECTIVE: Much has been written about the utility of genomic databases to public health. Within food safety these databases contain data from two types of isolates-those from patients (i.e., clinical) and those from non-clinical sources (e.g., a food manufacturing environment). A genetic match between isolates from these sources represents a signal of interest. We investigate the match rate within three large genomic databases (Listeria monocytogenes, Escherichia coli, and Salmonella) and the smaller Cronobacter database; the databases are part of the Pathogen Detection project at NCBI (National Center for Biotechnology Information).
RESULTS: Currently, the match rate of clinical isolates to non-clinical isolates is 33% for L. monocytogenes, 46% for Salmonella, and 7% for E. coli. These match rates are associated with several database features including the diversity of the organism, the database size, and the proportion of non-clinical BioSamples. Modeling match rate via logistic regression showed relatively good performance. Our prediction model illustrates the importance of populating databases with non-clinical isolates to better identify a match for clinical samples. Such information should help public health officials prioritize surveillance strategies and show the critical need to populate fledgling databases (e.g., Cronobacter sakazakii).

The wild boar, an impactful invasive species in Brazil, is subject to population control activities, which often include the use of hunting dogs. Hunters commonly consume wild boar meat, which is also used to feed their dogs, posing a risk of Toxoplasma gondii infection for humans and both T. gondii and Neospora caninum for dogs. The study aimed to investigate the prevalence of infection in wild boars (n = 127) and hunting dogs (n = 73) from São Paulo, Rio Grande do Sul, and Paraná states. We employed histopathological, serological (indirect fluorescent antibody test), and molecular techniques (endpoint polymerase chain reaction). Histopathology slides of wild boar tissue (central nervous system, heart, skeletal muscle, liver, spleen, kidney, gastrointestinal tract, pancreas, lymph nodes, and thyroid) sections revealed no T. gondii or N. caninum cysts (0/47). Antibodies anti-T. gondii were detected in 35/108 (32.4%) and anti-N. caninum in 45/108 (41.7%) wild boars. Only 2/18 (11.1%) wild boar tissue homogenate samples tested positive for T. gondii on endpoint PCR. Hunting dogs showed antibodies against T. gondii in 62/73 (85%) and against N. caninum in 31/73 (42%). The presence of antibodies against T. gondii and N. caninum in wild boars and hunting dogs, along with T. gondii DNA detection in wild boars, indicates the circulation of these parasites. Educating hunters on preventing these foodborne diseases, including zoonotic risks, is crucial.

Consumers can be exposed to many foodborne biological hazards that cause diseases with varying outcomes and incidence and, therefore, represent different levels of public health burden. To help the French risk managers to rank these hazards and to prioritize food safety actions, we have developed a three-step approach. The first step was to develop a list of foodborne hazards of health concern in mainland France. From an initial list of 335 human pathogenic biological agents, the final list of \"retained hazards\" consists of 24 hazards, including 12 bacteria (including bacterial toxins and metabolites), 3 viruses and 9 parasites. The second step was to collect data to estimate the disease burden (incidence, Disability Adjusted Life Years) associated with these hazards through food during two time periods: 2008-2013 and 2014-2019. The ranks of the different hazards changed slightly according to the considered period. The third step was the ranking of hazards according to a multicriteria decision support model using the ELECTRE III method. Three ranking criteria were used, where two reflect the severity of the effects (Years of life lost and Years lost due to disability) and one reflects the likelihood (incidence) of the disease. The multicriteria decision analysis approach takes into account the preferences of the risk managers through different sets of weights and the uncertainties associated with the data. The method and the data collected allowed to estimate the health burden of foodborne biological hazards in mainland France and to define a prioritization list for the health authorities.

Reducing foodborne disease incidence is a public health priority. This report summarizes preliminary 2023 Foodborne Diseases Active Surveillance Network (FoodNet) data and highlights efforts to increase the representativeness of FoodNet. During 2023, incidences of domestically acquired campylobacteriosis, Shiga toxin-producing Escherichia coli infection, yersiniosis, vibriosis, and cyclosporiasis increased, whereas those of listeriosis, salmonellosis, and shigellosis remained stable compared with incidences during 2016-2018, the baseline used for tracking progress towards federal disease reduction goals. During 2023, the incidence and percentage of infections diagnosed by culture-independent diagnostic tests (CIDTs) reported to FoodNet continued to increase, and the percentage of cases that yielded an isolate decreased, affecting observed trends in incidence. Because CIDTs allow for diagnosis of infections that previously would have gone undetected, lack of progress toward disease reduction goals might reflect changing diagnostic practices rather than an actual increase in incidence. Continued surveillance is needed to monitor the impact of changing diagnostic practices on disease trends, and targeted prevention efforts are needed to meet disease reduction goals. During 2023, FoodNet expanded its catchment area for the first time since 2004. This expansion improved the representativeness of the FoodNet catchment area, the ability of FoodNet to monitor trends in disease incidence, and the generalizability of FoodNet data.

CONCLUSIONS: The reliable and timely recognition of outbreaks is a key component of public health surveillance for foodborne diseases. Whole genome sequencing (WGS) offers high resolution typing of foodborne bacterial pathogens and facilitates the accurate detection of outbreaks. This detection relies on grouping WGS data into clusters at an appropriate genetic threshold. However, methods and tools for selecting and adjusting such thresholds according to the required resolution of surveillance and epidemiological context are lacking. Here we present DODGE (Dynamic Outbreak Detection for Genomic Epidemiology), an algorithm to dynamically select and compare these genetic thresholds. DODGE can analyse expanding datasets over time and clusters that are predicted to correspond to outbreaks (or \"investigation clusters\") can be named with established genomic nomenclature systems to facilitate integrated analysis across jurisdictions. DODGE was tested in two real-world Salmonella genomic surveillance datasets of different duration, 2 months from Australia and 9 years from the United Kingdom. In both cases only a minority of isolates were identified as investigation clusters. Two known outbreaks in the United Kingdom dataset were detected by DODGE and were recognized at an earlier timepoint than the outbreaks were reported. These findings demonstrated the potential of the DODGE approach to improve the effectiveness and timeliness of genomic surveillance for foodborne diseases and the effectiveness of the algorithm developed.
METHODS: DODGE is freely available at https://github.com/LanLab/dodge and can easily be installed using Conda.

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UNASSIGNED: Foodborne diseases, representing significant food safety and public health challenges globally, are not well-documented in terms of incidence, particularly for cases characterized by acute gastroenteritis (AGI) in China.
UNASSIGNED: This study developed a pyramid model to estimate the incidence of five pathogens, stratified by gender and age. The estimated incidences per 100,000 people with 95% uncertainty intervals (UI) are as follows: Norovirus, 3,188.28 (95% UI: 2,518.03, 7,296.96); Salmonella spp., 1,295.59 (95% UI: 1,002.62, 1,573.11); diarrheagenic E. coli (DEC), 782.62 (95% UI: 651.19, 932.05); Vibrio parahaemolyticus, 404.06 (95% UI: 342.19, 468.93); and Shigella spp., 26.73 (95% UI: 21.05, 33.46).
UNASSIGNED: This study elucidates the incidence rates across various gender and age groups, thereby identifying priority populations for targeted preventive interventions aimed at reducing disease burden. These insights are crucial for the development of public health policies and management of food safety risks.

UNASSIGNED: Hospital refrigerators as essential food storage can be important source of food contamination. We aimed to investigate the frequency and antibiotic susceptibility of the pathogenic bacteria in three hospital refrigerators in Tehran.
UNASSIGNED: This study was performed on 254 samples, collected from 60 refrigerators of the various wards of three hospitals, A, B, and C, in Tehran, Iran from 2020 to 2021. Following isolation and identification of isolates, the antibiotic susceptibility pattern was determined. PCR-based assays were used to screen the presence of antibiotic resistance genes of resistant isolates.
UNASSIGNED: From 254 collected samples, 236 samples (92.9%) were contaminated. Most strains were isolated from refrigerators with poorly cleaned, temperatures above 8 °C in non-critical wards. Most bacteria belonging to Enterobacteriaceae (68.8%), followed by Staphylococcus (11.9%), and Enterococcus (10.6%), while the frequency of non-Enterobacteriaceae isolates was 8.9%. The highest antibiotic resistant bacteria were in extended spectrum beta-lactamase (ESBL) 9.7%, vancomycin-resistant enterococci (VRE) 5.3%, methicillin-resistant S. epidermidis (MRSE) 0.4%, and methicillin-resistant S. aureus (MRSA) 0.4%, respectively. The bla OXA-48, bla CTX, and bcla TEM genes were found only in 10% of Enterobacteriaceae isolates. The bla OXA-51 gene was found in all non-Enterobacteriaceae isolates. The vanA and mecA genes were detected in antibiotic-resistant Enterococcus and Staphylococcus.
UNASSIGNED: Our findings suggests major concern about cross-contamination and the emergence of antibiotic-resistant isolates as a potential health threat with hospital refrigerators origin. More attention to hospital refrigerators cleaning is necessary to prevent foodborne diseases and nosocomial infections.

UNASSIGNED: In 2023, two fatalities attributed to the ingestion of uncooked morels (Morchella spp.) were reported in the United States; both patients developed severe gastrointestinal symptoms. Morel-induced gastrointestinal toxicity is well recognized, but no deaths had been reported until 2023, suggesting a potential shift in the severity of morel poisoning.
UNASSIGNED: Using the Poisoning Severity Score, we analyzed the severity of symptomatic cases of morel ingestion recorded in the French National Database of Poisonings from 2010 to 2020.
UNASSIGNED: We found 446 cases of exposure in which morels were the sole mushroom species involved. Of these, 83.6 per cent and 53.3 per cent developed gastrointestinal and neurological symptoms, respectively. Eight patients developed shock attributed to severe gastrointestinal symptoms, resulting in two deaths.
UNASSIGNED: Morel ingestion can lead to severe complications. As in the United States, the deaths reported in this study were attributed to imported cultivated morels. The shift, since 2006, towards a predominance of cultivated over wild morel sales may have played a role in the reporting of severe cases of morel poisoning.
UNASSIGNED: Reports of severe morel poisoning highlight the need for cautious consumption, particularly of raw or undercooked preparations. Emerging complications signal potential changes in toxicity. Surveillance and awareness are key to reducing the risks of consuming morels.

Foodborne viruses remain the largest cause of human gastroenteritis and one of the largest contributors to foodborne illnesses worldwide. Currently, quantitative reverse transcription PCR (qRT-PCR) or real-time qPCR are the detection methods commonly used for quantification of foodborne viruses, but those methods have several disadvantages, such as relying on standard curves for quantification and the background noise from a bulk reaction. ddPCR uses an oil-water emulsion to form multiple droplets that partition small amounts of viral genetic material (DNA or RNA) into each of the droplets. These droplets then undergo amplification cycles and are analyzed using Poisson distributions. This allows for absolute quantification without the need for a standard curve, which makes ddPCR a precise tool in surveillance of foodborne viruses. Herein, we describe the process of detecting foodborne viruses using RNA isolated from various matrices. Up to 96 samples including the positive and negative controls can be analyzed on a single plate by ddPCR.