A foodborne acute gastroenteritis outbreak caused by GII.P16-GII.2 norovirus in a boarding high school, Beijing, China: a case-control study

Measures for preventing norovirus outbreaks on campus in economically underdeveloped areas and countries: evidence from rural areas in Western China

Background

The outbreak of norovirus represents a significant public health emergency within densely populated, impoverished, and underdeveloped areas and countries. Our objective is to conduct an epidemiology study of a norovirus outbreak that occurred in a kindergarten located in rural western China. We aim to raise awareness and garner increased attention towards the prevention and control of norovirus, particularly in economically underdeveloped regions.

Methods

Retrospective on-site epidemiological investigation results, including data on school layout, case symptoms, onset time, disposal methods and sample testing results, questionnaire surveys, and case-control study were conducted in a kindergarten to analyze the underlying causes of the norovirus outbreak.

Results

A total of 15 cases were identified, with an attack rate of 44.12% (15/34). Among them, 10 cases were diagnosed through laboratory tests, and 5 cases were diagnosed clinically. Vomiting (100%, 15/15) and diarrhea (93.33%, 14/15) were the most common symptoms in the outbreak. Case control study revealed that cases who had close contact (<1 m) with the patient's vomitus (OR = 5.500) and those who had close contact with similar patients (OR = 8.000) had significantly higher ORs compared to the control participants. The current study demonstrated that improper handling of vomitus is positively associated with norovirus outbreak. The absence of standardized disinfection protocols heightens the risk of norovirus outbreaks.

Conclusion

To our knowledge, this study represents the first investigation into a norovirus outbreak in rural areas of western China. We aspire that amidst rapid economic development, a greater emphasis will be placed on the prevention and control of infectious diseases in economically underdeveloped areas and countries.

Detection of Norovirus Recombinant GII.2[P16] Strains in Oysters in Thailand

Human norovirus causes sporadic and epidemic acute gastroenteritis worldwide, and the predominant strains are genotype GII.4 variants. Recently, a novel GII.17[P17] and a recombinant GII.2[P16] strain have been reported as the causes of gastroenteritis outbreaks. Outbreaks of norovirus are frequently associated with foodborne illness. In this study, each of 75 oyster samples processed by a proteinase K extraction method and an adsorption-elution method were examined for noroviruses using RT-nested PCR with capsid primers. Thirteen (17.3%) samples processed by either method tested positive for norovirus genogroup II (GII). PCR amplicons were characterized by DNA sequencing and phylogenetic analysis as GII.2 (n = 6), GII.4 (n = 1), GII.17 (n = 3), and GII.unclassified (n = 3). Norovirus-positive samples were further amplified by semi-nested RT-PCR targeting the polymerase-capsid genes. One nucleotide sequence revealed GII.17[P17] Kawasaki strain. Five nucleotide sequences were identified as belonging to the recombinant GII.2[P16] strains by recombination analysis. The collected oyster samples were quantified for norovirus GII genome copy number by RT-quantitative PCR. Using the proteinase K method, GII was found in 13/75 (17.3%) of samples with a range of 8.83-1.85 × 10⁴ genome copies/g of oyster. One sample (1/75, 1.3%) processed by the adsorption-elution method was positive for GII at 5.00 × 10¹ genome copies/g. These findings indicate the circulation of a new variant GII.17 Kawasaki strain and the recombinant GII.2[P16] in oyster samples corresponding to the circulating strains reported at a global scale during the same period of time. The detection of the recombinant strains in oysters emphasizes the need for continuing systematic surveillance for control and prevention of norovirus gastroenteritis.

Natural Host-Environmental Media-Human: A New Potential Pathway of COVID-19 Outbreak

Identifying the first infected case (patient zero) is key in tracing the origin of a virus; however, doing so is extremely challenging. Patient zero for coronavirus disease 2019 (COVID-19) is likely to be permanently unknown. Here, we propose a new viral transmission route by focusing on the environmental media containing viruses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or RaTG3-related bat-borne coronavirus (Bat-CoV), which we term the "environmental quasi-host." We reason that the environmental quasi-host is likely to be a key node in helping recognize the origin of SARS-CoV-2; thus, SARS-CoV-2 might be transmitted along the route of natural host-environmental media-human. Reflecting upon viral outbreaks in the history of humanity, we realize that many epidemic events are caused by direct contact between humans and environmental media containing infectious viruses. Indeed, contacts between humans and environmental quasi-hosts are greatly increasing as the space of human activity incrementally overlaps with animals' living spaces, due to the rapid development and population growth of human society. Moreover, viruses can survive for a long time in environmental media. Therefore, we propose a new potential mechanism to trace the origin of the COVID-19 outbreak.

Recalibration of the Grunow-Finke Assessment Tool to Improve Performance in Detecting Unnatural Epidemics

Successful identification of unnatural epidemics relies on a sensitive risk assessment tool designed for the differentiation between unnatural and natural epidemics. The Grunow-Finke tool (GFT), which has been the most widely used, however, has low sensitivity in such differentiation. We aimed to recalibrate the GFT and improve the performance in detection of unnatural epidemics. The comparator was the original GFT and its application in 11 historical outbreaks, including eight confirmed unnatural outbreaks and three natural outbreaks. Three steps were involved: (i) removing criteria, (ii) changing weighting factors, and (iii) adding and refining criteria. We created a series of alternative models to examine the changes on the parameter likelihood of unnatural outbreaks until we found a model that correctly identified all the unnatural outbreaks and natural ones. Finally, the recalibrated GFT was tested and validated with data from an unnatural and natural outbreak, respectively. A total of 238 models were tested. Through the removal of criteria, increasing or decreasing weighting factors of other criteria, adding a new criterion titled "special insights," and setting a new threshold for likelihood, we increased the sensitivity of the GFT from 38% to 100%, and retained the specificity at 100% in detecting unnatural epidemics. Using test data from an unnatural and a natural outbreak, the recalibrated GFT correctly classified their etiology. The recalibrated GFT could be integrated into routine outbreak investigation by public health institutions and agencies responsible for biosecurity.