Environmental indicators for human norovirus outbreaks

The impact of increasing temperatures due to climate change on infectious diseases

Global temperatures will continue to rise due to climate change, with high temperature periods expected to increase in intensity, frequency, and duration. Infectious diseases, including vector-borne diseases such as dengue fever and malaria, waterborne diseases such as cholera, and foodborne diseases such as salmonellosis are influenced by temperature and other climatic variables, thus contributing to higher disease burden and associated healthcare costs, particularly in socioeconomically disadvantaged regions. Targeted efforts and investments are therefore needed to support low and middle income countries to prepare for and respond to the increasing infectious disease threats posed by rising temperatures. This can be facilitated by the development and refinement of robust disease and entomological surveillance and early warning systems with integration of climatic information that promote enhanced understanding of the geographic distribution of disease risk. To enhance healthcare workforce capacity and capability to respond to these public health threats, medical curricula and continuing professional education programmes for healthcare providers must include evidence based components on the impacts of climate change on infectious diseases.

Prevalence and associated factors of norovirus infections among patients with diarrhea in the Amhara national regional state, Ethiopia

BACKGROUND

Noroviruses (NoVs) are the leading cause of diarrheal disease among all age groups worldwide, with an increased burden in developing countries. As there is no surveillance, epidemiological data is limited in Ethiopia. Hence, this study aimed to investigate the prevalence and associated factors of NoV infection among patients with diarrhea in the Amhara National Regional State, Ethiopia.

METHODS

A prospective health facility-based cross-sectional study was conducted from May 2021 to November 2021. A total of 550 study participants of all age groups with symptoms of diarrhea were proportionately assigned to the four study areas, area with three health facilities. Study participants were systematically sampled in each health facility. A fecal sample from each case was collected. The RNA was extracted and tested for NoV by one-step RT-PCR. Sociodemographic and other variables were gathered using a pre-tested questionnaire. A descriptive analysis was performed. Both binary and multiple logistic regressions were utilized to identify factors associated with NoV infection. Variables with a p-value < 0.05 in the final model were considered statistically significant.

RESULTS

Five hundred nineteen out of 550 samples were analyzed (94.4% response rate). The overall prevalence of NoV was 8.9% (46/519). The positivity rates were higher among the elderly (33.3%) and under-5 children (12.5%). Both genogroup I and genogroup II (GII) were identified, with GII being the predominant, at 82.6% (38/46). Of all participants, only 20% reported a history of vomiting. Norovirus infection was more prevalent among participants from Debre Tabor (AOR = 4, 95%CI: 1.2-14) and Bahir Dar areas (AOR = 3.6, 95%CI: 1.04-11) compared to Debre Markos. Additionally, older adults (AOR = 7, 95% CI: 2-24) and under-5 children (AOR = 3.5, 95% CI: 2.8-12) were disproportionately affected compared to adults. The previous history of diarrhea (AOR = 3.6, 95% CI: 1.7-7) was a significant factor contributing to NoV infections. Moreover, the odds of NoV infection were higher among individuals with a high frequency of diarrhea (AOR = 15.3, 95%CI: 7.6-43) and vomiting (AOR = 3.5, 95%CI: 1.5-8).

CONCLUSIONS

The prevalence of NoV was considerably high, with the predominance of NoV-GII. The positivity rate was higher among the extreme age groups and varied across the study areas. To obtain a comprehensive understanding of the virus`s epidemiology and its genetic diversity, further research is warranted.

Prediction of Foodborne Norovirus Outbreaks in Coastal Areas in China in 2008-2018

Foodborne norovirus outbreak usually poses high risks in coastal areas in China. Owing to the influence of multiple climatic factors, it demonstrates typical seasonality and the hotspots gradually expanded northwards from 2008 to 2018. However, the complex mechanism of the onset of outbreaks makes accurate prediction difficult. Thus, it is in necessity to construct a predictive model for foodborne norovirus outbreaks in coastal areas based on environmental and geographical variables. A novel predictive nonlinear autoregressive model with exogenous inputs model was developed using 11 years of environmental and foodborne norovirus outbreak data collected from coastal areas in China. Five input variables (temperature, precipitation, elevation, latitude, and longitude) were screened through stepwise regression analysis. The predicted model developed in this study was able to reproduce 88.53% of outbreaks reported to the National Public Health Emergency Event Surveillance System (PHEESS) in the model development and 100% of outbreaks reported in the independent cross-validation since the system was first launched in China. In particular, foodborne norovirus outbreaks might occur when the probability is >0.6. The findings of this study suggest that foodborne norovirus outbreaks could be accurately predicted in coastal areas in China using the developed predictive model on a daily basis. The model output is most sensitive to temperature, followed by precipitation, and locations. The application of this predictive model is promising to improve local hygiene management levels, prevent foodborne norovirus outbreaks, and reduce the disease and economic costs in coastal areas in China.

Investigation of two norovirus outbreaks linked to drinking water contaminated with multiple GII strains in a rural county-Chongqing, China, 2021

Backgrounds

Norovirus is leading cause of non-bacterial gastroenteritis outbreaks globally, characterized by different strains prevalent in different countries and regions.

Methods

Cases were defined as individuals experiencing diarrhea ≥3 times/24 h, and/or vomiting ≥2 times/24 h in two villages between January 28 and February 9, 2021. Investigations were conducted to identify causes. Cases were interviewed using a standardized in-person form to collect data on potential risk factors. A retrospective cohort study was conducted to investigate the role of the spring water supply as the outbreak source. Residents from neighboring villages with different water sources served as the unexposed population. Stool specimens, rectal swabs, and water samples were tested using quantitative real-time Polymerase Chain Reaction, with subsequent sequencing performed on pathogen-positive specimens.

Results

Village-specific attack rates were 21.93% (123/561) and 26.99% (88/326), respectively. Evidence from both epidemiological and laboratory tests was consistent. Drinking spring water was statistically associated with the two outbreaks (RR = 41.8 and 79.2, respectively). In both outbreaks, stool specimens, rectal swabs, and water samples tested positive for norovirus. Specifically, GII.2 (P16) and GII.17 (P17) were identified in outbreak A, and GII.4 Sydney (P16) and GII.1 (P16) in outbreak B.

Conclusion

These two independent gastroenteritis outbreaks share similarities, both being linked to norovirus GII strains. The contaminated spring drinking water was identified as the probable source and was promptly closed and subjected to disinfection procedures. These findings reinforce the importance of implementing sanitation and environmental disinfection measures in rural areas, especially during the periods of increased rainfall.

Molecular Characterization of Gastroenteric Viruses in Wastewater from Cities in Uruguay

Group A Rotavirus, Human Astrovirus, and Norovirus (RVA, HAstV, and NoV) are recognized as the major causative agents of acute gastroenteritis in children and adults worldwide. The aim of this study was to determine the prevalence and molecular epidemiology of RVA, HAstV, and NoV in wastewater from three cities in Uruguay. Thirty-six samples from Bella Unión, Salto, and Fray Bentos cities were analyzed using quantitative and qualitative PCR. RVA was the most frequently detected virus (50%), followed by HAstV (39%), NoV GII (36%), and NoV GI (25%). RVA strains were characterized as P[8] and G3 based on the VP4 and VP7 genes, respectively. Among NoV-positive samples, genotypes GI.2, GI.3, GI.5, GI.6, GI.7, GII.2, GII.6, and GII.4 were detected, and only one HAstV genotype (MLB1) was found. Our wastewater-based epidemiological approach provides a snapshot of the overall genetic diversity of these viruses in three cities of the Uruguay River basin during 2017-2018. These findings reinforce the importance of this environmental surveillance tool for monitoring epidemiological trends of enteric viruses circulating in the population, which can be used to guide public health intervention.

Molecular epidemiology and genetic diversity of norovirus among hospitalized patients with acute gastroenteritis in Shandong, China, 2016-2018

Norovirus (NoV) infection is a leading cause of acute gastroenteritis (AGE) for people of all ages. Here, we reported the molecular epidemiology and genetic diversity of NoVs among hospitalized patients with AGE between 2016 and 2018 in Shandong Province, China. Two thousand sixty-nine AGE patients from sentinel hospitals were enrolled. The stool samples were collected and tested for NoVs by real-time RT-PCR. The RNA-dependent RNA polymerase (RdRp) and capsid gene of 163 strains were amplified and sequenced for genotyping. Phylogenetic analyses and genomic characterization were conducted with the VP1 and RdRp region of the full genome sequences. Four hundred seventy two (21.76%) samples were NoV-positive. The positive rate in 2016 was higher than those of 2017 and 2018. We observed diverse NoV genotypes. GII.2[P16] emerged in January 2017 and became the dominant genotype between May and June 2017. Phylogenetic analyses showed that our GII.2[P16] genomes clustered in the SC1 in VP1 region, while they belonged to the Emerging GⅡ.P16 (2015-2017) clade in RdRp region. Our GⅡ.4 strains displayed two amino acid mutations, positions R297H and D372N, in epitope A of the VP1 region. Our study highlighted that NoV is an important pathogen of viral AGE in Shandong and, therefore, it is necessary to strengthen its surveillance.

Research Progress on Biological Accumulation, Detection and Inactivation Technologies of Norovirus in Oysters

Noroviruses (NoVs) are major foodborne pathogens that cause acute gastroenteritis. Oysters are significant carriers of this pathogen, and disease transmission from the consumption of NoVs-infected oysters occurs worldwide. The review discusses the mechanism of NoVs bioaccumulation in oysters, particularly the binding of histo-blood group antigen-like (HBGA-like) molecules to NoVs in oysters. The review explores the factors that influence NoVs bioaccumulation in oysters, including temperature, precipitation and water contamination. The review also discusses the detection methods of NoVs in live oysters and analyzes the inactivation effects of high hydrostatic pressure, irradiation treatment and plasma treatment on NoVs. These non-thermal processing treatments can remove NoVs efficiently while retaining the original flavor of oysters. However, further research is needed to reduce the cost of these technologies to achieve large-scale commercial applications. The review aims to provide novel insights to reduce the bioaccumulation of NoVs in oysters and serve as a reference for the development of new, rapid and effective methods for detecting and inactivating NoVs in live oysters.

Seasonal variation of diarrhoeal pathogens among Guinea-Bissauan children under five years of age

BACKGROUND

Diarrhoea remains a major cause of childhood morbidity and mortality in low-income countries (LICs). The frequency of diarrhoeal episodes may vary by season, yet few prospective cohort studies have examined seasonal variation among various diarrhoeal pathogens using multiplex qPCR to analyse bacterial, viral and parasitic pathogens.

METHODS

We combined our recent qPCR data of diarrhoeal pathogens (nine bacterial, five viral and four parasitic) among Guinea-Bissauan children under five years old with individual background data, dividing by season. The associations of season (dry winter and rainy summer) and the various pathogens were explored among infants (0-11 months) and young children (12-59 months) and those with and without diarrhoea.

RESULTS

Many bacterial pathogens, especially EAEC, ETEC and Campylobacter, and parasitic Cryptosporidium, prevailed in the rainy season, whereas many viruses, particularly the adenovirus, astrovirus and rotavirus proved common in the dry season. Noroviruses were found constantly throughout the year. Seasonal variation was observed in both age groups.

CONCLUSION

In childhood diarrhoea in a West African LIC, seasonal variation appears to favour EAEC, ETEC, and Cryptosporidium in the rainy and viral pathogens in the dry season.

High Burden of Co-Infection with Multiple Enteric Pathogens in Children Suffering with Diarrhoea from Rural and Peri-Urban Communities in South Africa

Infectious diarrhoea contributes to high morbidity and mortality in young children from sub-Saharan Africa. The aim of this study was to assess the prevalence of single and multiple diarrhoeal-causing pathogen combinations in children suffering from diarrhoea from rural and peri-urban communities in South Africa. A total of 275 diarrhoea stool specimens were collected between 2014 and 2016 from Hospitals and Primary Health Care clinics. The BioFire^® FilmArray^® Gastrointestinal panel was used to simultaneously detect 22 diarrhoea pathogens (viruses, bacteria, parasites) known to cause diarrhoea. A total of 82% (226/275) enteric pathogens were detected in the stool specimens. The two most detected bacterial, viral and parasitic pathogens each included: EAEC (42%), EPEC (32%), Adenovirus F40/41 (19%), Norovirus (15%), Giardia (8%) and Cryptosporidium (6%), respectively. Single enteric pathogen infections were recorded in 24% (65/275) specimens with EAEC, and Norovirus was found in 26% (17/65) and 14% (9/65) of the specimens, respectively. Multiple enteric pathogen combinations were recorded in 59% (161/275) of the stool specimens with 53% (85/161) containing two pathogens, 22% (35/161) containing three pathogens and 25% (41/161) containing four or more pathogens. The results from this study demonstrated the complex nature of pathogen co-infections in diarrhoeal episodes which could have an impact on treatment effectiveness.

Norovirus outbreaks in China, 2000-2018: A systematic review

To understand epidemiological characteristics of norovirus outbreaks in China from 2000 to 2018 the literature on norovirus outbreaks was identified by searching WANFANG, CNKI, PubMed, and Web of Science databases before 31 December 2018. Statistical analyses were performed using Statistical Product Service Solutions software. RStudio1.4.1717 and ArcGIS trial version were used for plotting bar graphs and maps. A total of 419 norovirus outbreaks were reported in the 394 included articles, which occurred between June 2000 and October 2018, showing an overall increasing trend. The majority of outbreaks occurred in schools (52.28%, 218/417) and kindergartens (55/417, 13.19%). Person-to-person transmission (41.64%, 137/329) was most common, followed by food-borne transmission (75/329, 22.80%) and water-borne transmission (72/329, 21.88%). GII was the most predominant norovirus genogroup, with GII.4, GII.17 and GII.2 being the dominant genotypes in 2007-2013, 2014-2015, 2016-2017, respectively. Increased outbreaks were associated with the prevalence of new variants. Most norovirus outbreaks were reported in the southeast of the country. The number of norovirus outbreaks was positively associated with the per capita gross domestic product and the year-end resident population. Norovirus outbreaks have become an important public health problem in China. It is necessary to establish surveillance in hospitals and nursing homes. Genotyping of noroviruses is important for monitoring the circulating strains and improving the vaccine design, so it should be carried out in more regions.

Norovirus detection in wastewater and its correlation with human gastroenteritis: a systematic review and meta-analysis

Norovirus (NoV) is a major cause of sporadic cases and outbreaks of acute gastroenteritis (AGE), thereby imposing threat to health globally. It is unclear how quantitation of wastewater NoV reflects the incidence of human AGE infections; therefore, we conducted this systematic review and meta-analysis of published NoV wastewater surveillance studies. A literature search was performed, and all studies on NoV wastewater surveillance were identified. Quantitative results were evaluated. The results showed that the overall detection rate of NoV in wastewater was 82.10% (95% confidence interval [CI]: 74.22-89.92%); NoV concentration was statistically significant in terms of season (P < 0.001), with higher concentration in spring and winter. There were positive correlations between NoV GII concentration in wastewater and GII AGE cases (rs = 0.51, 95% CI: 0.18-0.74, I2 = 0%), total AGE cases (rs = 0.40, 95% CI: 0.15-0.61, I2 = 23%) and NoV outbreaks (rs = 0.47, 95% CI: 0.30-0.62, I2 = 0%). Results of cross-correlation analysis of partial data indicated that variations in GII concentration were consistent with or ahead of those in the number of AGE cases. The diversity of NoV genotypes in wastewater was elucidated, and the dominant strains in wastewater showed a consistent temporal distribution with those responsible for human AGE. Our study demonstrated the potential association of NoV detected in wastewater with AGE infections, and further studies are needed to confirm this conclusion.

Effects of climatic factors and particulate matter on Rotavirus A infections in Cheonan, Korea, in 2010-2019

Rotavirus A is the most common cause of infectious diarrhea worldwide. This study aimed to retrospectively study and analyze 4009 stool samples that were tested for viruses causing diarrhea, using multiplex reverse transcription PCR at Dankook University Hospital between 2010 and 2019. Furthermore, we determined the correlation between these factors and various climatic factors, including wind-chill temperature, relative humidity, rate of sunshine, and particulate matter. Rotavirus A infections occurred frequently in February, March, and April on an annual basis. Furthermore, during the study, the detection rate was highest at 17.0% (n=61/359) in 2011. Based on an analysis of weather big data, patient age, and period-specific infection during the summer, when the wind-chill temperature and relative humidity were high, the Rotavirus A infection rate was very low. Relative humidity (p=0.020) and particulate matter (p=0.049) were associated with the average number of monthly cases of Rotavirus A infection. However, wind chill temperature (p=0.074) and rate of sunshine (p=0.993) were not associated with the average monthly distribution of Rotavirus A cases. These results indicate that Rotavirus A infection was correlated with relative humidity and particulate matter during the study period and further the current understanding of the distribution of Rotavirus A infections resulting from climatic factors and particulate matter. This could help establish climate-related health policies to reduce the incidence of diarrhea and guide the development of vaccines against Rotavirus A.

Hybrid modeling and prediction of oyster norovirus outbreaks

This paper presents a hybrid model for predicting oyster norovirus outbreaks by combining the Artificial Neural Networks (ANNs) and Principal Component Analysis (PCA) methods and using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote-sensing data. Specifically, 10 years (2007-2016) of cloud-free MODIS Aqua data for water leaving reflectance and environmental data were extracted from the center of each oyster harvest area. Then, the PCA was utilized to compress the size of the MODIS Aqua data. An ANN model was trained using the first 4 years of the data from 2007 to 2010 and validated using the additional 6 years of independent datasets collected from 2011 to 2016. Results indicated that the hybrid PCA-ANN model was capable of reproducing the 10 years of historical oyster norovirus outbreaks along the Northern Gulf of Mexico coast with a sensitivity of 72.7% and specificity of 99.9%, respectively, demonstrating the efficacy of the hybrid model.

The Effect of Ambient Temperature on Infectious Diarrhea and Diarrhea-like Illness in Wuxi, China

Background:

The disease burden of infectious diarrhea cannot be underestimated. Its seasonal patterns indicate that weather patterns may play an important role and have an important effect on it. The objective of this study was to clarify the relationship between temperature and infectious diarrhea, and diarrhea-like illness.

Methods:

Distributed lag non-linear model, which was based on the definition of a cross-basis, was used to examine the effect.

Results:

Viral diarrhea usually had high incidence in autumn-winter and spring with a peak at -6°C; Norovirus circulated throughout the year with an insignificant peak at 8°C, while related bacteria usually tested positive in summer and peaked at 22°C. The lag-response curve of the proportion of diarrhea-like cases in outpatient and emergency cases revealed that at -6°C, with the lag days increasing, the proportion increased. Similar phenomena were observed at the beginning of the curves of virus and bacterial positive rate, showing that the risk increased as the lag days increased, peaking on days 16 and 9, respectively. The shape of lag-response curve of norovirus positive rate was different from others, presenting m-type, with 2 peaks on day 3 and day 18.

Conclusion:

Weather patterns should be taken into account when developing surveillance programs and formulating relevant public health intervention strategies.

Effects of Weather and Environmental Factors on the Seasonal Prevalence of Foodborne Viruses in Irrigation Waters in Gyeonggi Province, Korea

This study aimed to investigate the prevalence of foodborne viruses in reservoirs (an important resource of irrigation water) and its correlation with environmental and weather factors. From May 2017 to November 2018, we visited ten reservoirs and a river in the Anseong region of South Korea and collected a total of 192 samples in accordance with the environment protection agency guidelines. We recorded the weather factors (temperature, humidity, and accumulated precipitation) and investigated the surrounding environment factors (livestock, fishing site, the catchment area of reservoirs, etc.). Our research results show that from the river and reservoirs, the detection rates of human norovirus GII, adenovirus, rotavirus, human norovirus GI, and astrovirus were 27.1, 10.4, 10.4, 4.16, and 3.1%, respectively. Their viral load ranged from -1.48 to 1.55 log₁₀ genome copies/l. However, hepatitis A virus was not detected in any irrigation water sample. Although no sampling was performed in winter, foodborne viruses and male-specific coliphages were frequently found during spring (40.78%) and autumn (39.47%). Interestingly, the significant correlation between the accumulative precipitation and the number of detected norovirus and adenovirus was confirmed by linear regression analysis. Furthermore, when the accumulative precipitation ranged from 20 to 60 mm, it significantly affected the viral load and prevalence. Among the environmental factors, recreational facilities such as fishing sites and bungalow fishing spots were identified as contamination sources by correlation analysis. Our research results confirmed the correlations between environmental contamination factors in the reservoir and weather factors with the prevalence of foodborne viruses in the reservoir. These facilitates the assessment of potential foodborne virus contamination during crop irrigation. In addition, predictive models including environmental and weather factors should be developed for monitoring and controlling the safety of irrigation waters in reservoirs.

A Prospective Cohort Study of Bedroom Warming With a Heating System and Its Association With Common Infectious Diseases in Children During Winter in Japan

Background

Customarily, bedrooms in Japan are left unheated. Although several studies have reported that the use of a heating system has positive outcomes on respiratory infection and asthma, the preventive effect of heating systems against infectious diseases in children is not well known.

Methods

We conducted a cohort study using two questionnaire surveys, one before the winter season in November, 2018 and the second after winter in March, 2019. Participants were 155 children who did not use a heating system in the bedroom and 156 children who did.

Results

Having a heated bedroom with a heating system was associated with decreased odds for the frequency of cold (≥3 times) (adjust odds ratio [AOR] 0.35; 95% confidence interval [CI], 0.19–0.65), duration of fever (≥3 days) (AOR 0.38; 95% CI, 0.22–0.66), duration of medicine for a cold (≥3 days) (AOR 0.91; 95% CI, 0.87–0.95), hospital visit due to cold (≥3 days) (AOR 0.54; 95% CI, 0.31–0.94), absence from school or nursery (≥3 days) (AOR 0.43; 95% CI, 0.27–0.70), influenza infection (AOR 0.43; 95% CI, 0.26–0.71), and gastroenteritis (AOR 0.39; 95% CI, 0.21–0.72). Influenza vaccination reduced the odds of influenza infection (AOR 0.36; 95% CI, 0.22–0.59) and absence from school or nursery (≥3 days) (AOR 0.62; 95% CI, 0.39–0.99).

Conclusion

This study implies that the heating of bedrooms may have a preventive effect against infections among children. Broader dissemination of this knowledge in Japan will require cultural change through public health awareness.

Development of genetic programming-based model for predicting oyster norovirus outbreak risks

Oyster norovirus outbreaks pose increasing risks to human health and seafood industry worldwide but exact causes of the outbreaks are rarely identified, making it highly unlikely to reduce the risks. This paper presents a genetic programming (GP) based approach to identifying the primary cause of oyster norovirus outbreaks and predicting oyster norovirus outbreaks in order to reduce the risks. In terms of the primary cause, it was found that oyster norovirus outbreaks were controlled by cumulative effects of antecedent environmental conditions characterized by low solar radiation, low water temperature, low gage height (the height of water above a gage datum), low salinity, heavy rainfall, and strong offshore wind. The six environmental variables were determined by using Random Forest (RF) and Binary Logistic Regression (BLR) methods within the framework of the GP approach. In terms of predicting norovirus outbreaks, a risk-based GP model was developed using the six environmental variables and various combinations of the variables with different time lags. The results of local and global sensitivity analyses showed that gage height, temperature, and solar radiation were by far the three most important environmental predictors for oyster norovirus outbreaks, though other variables were also important. Specifically, very low temperature and gage height significantly increased the risk of norovirus outbreaks while high solar radiation markedly reduced the risk, suggesting that low temperature and gage height were associated with the norovirus source while solar radiation was the primary sink of norovirus. The GP model was utilized to hindcast daily risks of oyster norovirus outbreaks along the Northern Gulf of Mexico coast. The daily hindcasting results indicated that the GP model was capable of hindcasting all historical oyster norovirus outbreaks from January 2002 to June 2014 in the Gulf of Mexico with only two false positive outbreaks for the 12.5-year period. The performance of the GP model was characterized with the area under the Receiver Operating Characteristic curve of 0.86, the true positive rate (sensitivity) of 78.53% and the true negative rate (specificity) of 88.82%, respectively, demonstrating the efficacy of the GP model. The findings and results offered new insights into the oyster norovirus outbreaks in terms of source, sink, cause, and predictors. The GP model provided an efficient and effective tool for predicting potential oyster norovirus outbreaks and implementing management interventions to prevent or at least reduce norovirus risks to both the human health and the seafood industry.

Environmental indicators of oyster norovirus outbreaks in coastal waters

This paper presents an artificial intelligence-based approach to identifying environmental indicators of oyster norovirus outbreaks in coastal waters. It was found that oyster norovirus outbreaks are generally linked to the extreme combination of antecedent environmental conditions characterized by low water temperature, low solar radiation, low gage height, low salinity, strong wind, and heavy precipitation. Among the six environmental indicators, the most important three indicators, including water temperature, solar radiation and gage height, are capable of explaining 77.7% of model-predicted oyster norovirus outbreaks while the extremely low temperature alone may explain 37.2% of oyster norovirus outbreaks. It is, therefore, recommended that water temperature in oyster harvesting areas be monitored in the cold season and particularly the extremely low temperature during a low gage height be used as the primary indicator of oyster norovirus outbreaks. The findings are of profound significance to reducing the public health risk of norovirus outbreaks associated with consumption of oysters.

Clinical Characteristics and Risk Factors for Seizures Associated With Norovirus Gastroenteritis in Childhood

Norovirus has become increasingly recognized as causing viral gastroenteritis in children. Few data are available on the characteristics of children admitted to pediatric emergency departments with norovirus gastroenteritis and accompanying seizures. Our aim in this study was to describe the clinical features of, and risk factors for, seizures accompanying norovirus gastroenteritis. We collected 6359 stool samples from patients with gastroenteritis, of whom 1444 (22.71%) had laboratory-confirmed norovirus gastroenteritis. Of all patients, 108 (7.48%) children exhibited norovirus gastroenteritis and seizures; 49 (45.4%) were febrile, and 59 (54.6%) afebrile. The mean patient age was 2.31 ± 2.12 years; most were <5 years of age (92.6%). The afebrile group had a significantly higher incidence of 2 or more seizures than the febrile subjects ( P = .004). Early recognition and prompt treatment of convulsions associated with norovirus gastroenteritis in children are important. Future studies might explore the long-term prognoses of these patients.