Listeria monocytogenes, a ubiquitous bacterium in nature, can lead to human listeriosis through food consumption. Listeriosis is a rare, preventable, and treatable foodborne disease but can cause hospitalizations and fatalities. We reviewed the literature published in China to better understand the prevalence of L. monocytogenes in food products, incidence of human listeriosis, and characteristics of L. monocytogenes strains in China. The average prevalence of L. monocytogenes in Chinese food products in 28 provinces was 4.42%, with the highest prevalence of 8.91% in meat-poultry products, followed by aquatic animals, Chinese salad and salad, rice and flour products, and so on. Two hundred fifty-three invasive listeriosis cases were reported from 2011 to 2016 in 19 provinces, and the overall case-fatality rate was 25.7% with no deaths reported of pregnant women and children. L. monocytogenes strains were generally susceptible to most antibiotics, with ampicillin and penicillin G still effective in treatment. The predominant sequence types (STs) in food were ST9 and ST8, while clinically ST87 was most common ST in China. The national human listeriosis pilot surveillance started in 2013, and a total of 133 listeriosis cases have been collected until now. On the basis of the surveillance program, further research should be conducted to uncover the reason for the prevalence and pathogenic mechanism of the highly epidemiological hypervirulent ST87 strains in China.

Introduction : Mushroom poisoning was the leading cause of foodborne disease outbreaks and outbreak-associated deaths in China. Mushroom poisoning outbreak surveillance can provide insight into the epidemiological characteristics of mushroom poisonings and guide policymaking and health education to reduce illnesses and deaths. Methods : Foodborne Disease Outbreak Surveillance System was upgraded in 2011 to collect foodborne disease outbreaks in China. Mushroom poisoning outbreaks during 2010–2020 were selected to analyze geographical distribution, seasonal distribution, and setting of food preparation. Results : A total of 10,036 outbreaks, which resulted in 38,676 illnesses and 788 deaths, were reported in this period. Mushroom poisonings occurred all over the country, but with highest incidence in the southwest and central China. Overall, 84.6% outbreaks were associated with food prepared in households, followed by 8.7% in street stalls, and 2.5% in canteens. Mushroom poisoning outbreaks clearly exhibited seasonality, and the peak season was summer through autumn. Outbreaks occurring between May and October accounted for 94.1% of total outbreaks, 92.4% illnesses, and 97.2% deaths. Conclusions : Mushroom poisoning is a food safety issue of higher concern in China. Targeted health education is essential to reduce mushroom poisoning, especially in southwest China. Citizens are advised to not collect or eat wild mushrooms.

Background: Foodborne diseases, as a type of disease with a high global incidence, place a heavy burden on public health and social economy. Foodborne pathogens, as the main factor of foodborne diseases, play an important role in the treatment and prevention of foodborne diseases; however, foodborne diseases caused by different pathogens lack specificity in clinical features, and there is a low proportion of clinically actual pathogen detection in real life. Objective: We aimed to analyze foodborne disease case data, select appropriate features based on analysis results, and use machine learning methods to classify foodborne disease pathogens to predict foodborne disease pathogens that have not been tested. Methods: We extracted features such as space, time, and exposed food from foodborne disease case data and analyzed the relationship between these features and the foodborne disease pathogens using a variety of machine learning methods to classify foodborne disease pathogens. We compared the results of 4 models to obtain the pathogen prediction model with the highest accuracy. Results: The gradient boost decision tree model obtained the highest accuracy, with accuracy approaching 69% in identifying 4 pathogens including Salmonella, Norovirus, Escherichia coli, and Vibrio parahaemolyticus. By evaluating the importance of features such as time of illness, geographical longitude and latitude, and diarrhea frequency, we found that they play important roles in classifying the foodborne disease pathogens. Conclusions: Data analysis can reflect the distribution of some features of foodborne diseases and the relationship among the features. The classification of pathogens based on the analysis results and machine learning methods can provide beneficial support for clinical auxiliary diagnosis and treatment of foodborne diseases.

Salmonella is widely known as one of the most common foodborne pathogens, and antibiotics remain effective in clinical therapies against its infections. To guide better clinical antibiotic treatment, we analyzed the antimicrobial resistance (AMR) profiles of a nation-wide collection of 36,822 Salmonella isolates derived from sporadic diarrhea cases in China from 2014 to 2021. A panel of 15 antibiotics, including 10 critically important and 5 highly important antimicrobial agents for human medicine based on the WHO CIA List, was selected for AMR surveillance. Salmonella enterica serovar Typhimurium, Enteritidis, I 4,[5],12:i:-, London, and Stanley were turns to be the top five serotypes from human diarrhea cases in China. Antimicrobial susceptibility testing revealed that the majority of the isolates (87.2%) were resistant to at least one antimicrobial agent, and 66.5% were multidrug resistant (MDR). Salmonella isolates were found to be highly resistant to ampicillin (73.4%) while sensitive to imipenem (98.73%). Over the eight years, the isolates were demonstrated generally an increase in resistance to ampicillin, chloramphenicol, trimethoprim-sulfamethoxazole, and azithromycin, but displayed varied resistance profiles in terms of serotypes. Stanley (0.66–27.18%) and Agona (0.78–45.30%) had lower resistance rates compared to Typhimurium (1.11–85.6%), Enteritidis (1.55–91.29%), and I 4,[5],12:i:- (1.02–94.28%). In conclusion, our results provide systematic data on the resistance characteristics of Salmonella isolates from human diarrhea cases in China. Furthermore, this data identifies priorities for the clinical treatments of antibiotics.

Sentinel Listeriosis Surveillance, China