Detection and forecasting of oyster norovirus outbreaks: recent advances and future perspectives

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.

Human Norovirus Detection: How Much Are We Prepared?

Norovirus (NoV) is known to be the second nonbacterial enteric pathogen after rotavirus that causes acute gastroenteritis. They can be spread from person to person through fecal-oral routes. Infection can lead to severe diarrhea, causing stomach pain, vomiting, and nausea. Rapid detection of NoV can control huge economic and productive losses. Genotyping various emerging NoV strains is important to compare the severity among different strains. Conventional immunological and molecular methods have evolved and contributed to developing detection techniques. Immunological (enzyme-linked immunosorbent assay) and molecular detection (reverse transcriptase polymerase chain reaction [RT-PCR], RT-quantitative PCR, loop-mediated isothermal amplification, nucleic acid sequence-based alignment, recombinase polymerase amplification) methods have been mainly used. The development of biosensors using aptasensor, affinity peptides, nanoparticles, microfluidics, and so on, are currently the most researched topics. The availability of next-generation sequencing technologies has greatly influenced the diagnosis of NoV. The complementation of advanced technologies is helpful in identification of new variants. In this study, techniques that are useful in detecting NoV are discussed. This review has investigated the availability of recent methods used in the detection, present status, and futuristic plan of action in case of outbreak and pandemic.

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.

Evaluation of Alternative Colony Hybridization Methods for Pathogenic Vibrios

Vibrios, such as Vibrio parahaemolyticus, are naturally occurring halophilic bacteria that are a major cause of foodborne illness. Because of their autochthonous nature, managing vibrio levels in marine and estuarine environments is impossible. Instead, it is crucial to reliably enumerate their abundance to minimize human exposure. One method of achieving this is the direct plating/colony hybridization (DP/CH) method, which has been used to efficiently quantify pathogenic vibrios in oysters and other seafood products. Although successful, the method relies on proprietary resources. We examined alternative approaches, assessed the influence of the reagent suppliers’ source on enumeration accuracy, and made experimental adjustments that maximized efficiency, sensitivity, and specificity. We report here that in-house conjugation via Cell Mosaic is a viable alternative to the previously available sole-source distributor of the alkaline phosphatase-conjugated probes used to enumerate vibrios in oysters. We also report that milk was a viable alternative as a blocking reagent, pH must be eight, an orbital shaker was a viable alternative to a water bath, and narrow polypropylene containers were a viable alternative to Whirl-Pak bags. These modifications will be crucial to scientists enumerating vibrios and other pathogens in food products.

A Deterministic Model for Understanding Nonlinear Viral Dynamics in Oysters

Contamination of oysters with a variety of viruses is one key pathway to trigger outbreaks of massive oyster mortality as well as human illnesses, including gastroenteritis and hepatitis. Much effort has gone into examining the fate of viruses in contaminated oysters, yet the current state of knowledge of nonlinear virus-oyster interactions is not comprehensive because most studies have focused on a limited number of processes under a narrow range of experimental conditions. A framework is needed for describing the complex nonlinear virus-oyster interactions. Here, we introduce a mathematical model that includes key processes for viral dynamics in oysters, such as oyster filtration, viral replication, the antiviral immune response, apoptosis, autophagy, and selective accumulation. We evaluate the model performance for two groups of viruses, those that replicate in oysters (e.g., ostreid herpesvirus) and those that do not (e.g., norovirus), and show that this model simulates well the viral dynamics in oysters for both groups. The model analytically explains experimental findings and predicts how changes in different physiological processes and environmental conditions nonlinearly affect in-host viral dynamics, for example, that oysters at higher temperatures may be more resistant to infection by ostreid herpesvirus. It also provides new insight into food treatment for controlling outbreaks, for example, that depuration for reducing norovirus levels is more effective in environments where oyster filtration rates are higher. This study provides the foundation of a modeling framework to guide future experiments and numerical modeling for better prediction and management of outbreaks.

IMPORTANCE The fate of viruses in contaminated oysters has received a significant amount of attention in the fields of oyster aquaculture, food quality control, and public health. However, intensive studies through laboratory experiments and in situ observations are often conducted under a narrow range of experimental conditions and for a specific purpose in their respective fields. Given the complex interactions of various processes and nonlinear viral responses to changes in physiological and environmental conditions, a theoretical framework fully describing the viral dynamics in oysters is warranted to guide future studies from a top-down design. Here, we developed a process-based, in-host modeling framework that builds a bridge for better communications between different disciplines studying virus-oyster interactions.

A Longitudinal Study on Enteric Virus Contamination in Bivalves along the Coast of Ibaraki Prefecture, Japan

ABSTRACT

During the 2014 to 2018 seasons, we conducted a longitudinal study involving enteric virus surveillance in bivalves, including natural oysters and clams harvested in Ibaraki Prefecture, Japan. Some norovirus (NoV) contaminations were detected in natural oysters, whereas no enteric virus was found in clams. NoVs detected in oysters were of the genotypes GII.4 and GII.6, both of which are closely related genetically to the NoV strains prevalent in humans. We found low level of enteric virus contamination in bivalves collected along the coast of Ibaraki Prefecture. The possibility of food poisoning caused by these viruses appears low, and few cases of infectious disease have been observed in the surrounding area. The harvest timing was more related to contamination quantity than the harvest area in many enteric viruses. Our results highlight that contamination of bivalves by enteric viruses may depend upon the prevalence of human diarrhea and illness.

HIGHLIGHTS

Molecular Detection of Norwalk Virus in Carp Fish and Shrimp Ponds in Khuzestan Province, Iran by RT-PCR Method

Background: Norwalk virus is one of the most common causes of viral gastroenteritis. The aquatic products are potential sources of contamination with this virus. Objectives: The main objective of the study was to investigate the presence of the Norwalk virus in different aquatic animals in Khuzestan provinces, Iran. Materials and Methods: A total of 40 pieces of fish (silver carp, common carp, big head, and grass carp species) and 10 pieces of shrimps were caught from ponds, and the samples were transferred to the laboratory in ice bags. After the separation of the intestine, the content of the intestine was extracted using two sterile filters. Then, the supernatant was used for reverse transcription polymerase chain reaction (RT-PCR) using Calicivirus-specific primers (p289/ p290). Then, Norwalk virus-specific primers (NVp36/NVp35) were detected in Calicivirus positive samples. Results: The results showed 8% (4 samples) and 6% (3 samples) of the samples were infected with Calicivirus (p289/p290 genes) and Norwalk virus (NVp36/NVp35 genes), respectively. Calicivirus positive samples included 2 common carp, 1 silver carp, and 1 shrimp. Norwalk virus-positive samples included 2 common carp and 1 shrimp. In other words, the highest prevalence of virus was observed in aquatic fish feeding from the bottom of the pool. Due to the fact that this species is bred with other species and considering that this virus lives in the gastrointestinal tract, the ingestion of feces of other infected organisms can lead to the increase of this virus in the digestive system of carp. Conclusion: Therefore, due to the importance of Norwalk as a zoonotic agent and the possibility of human infection through consumption of aquatic products, preventive measures such as not using animal manure for fertilization and preventing the growth of phytoplankton in aquaculture ponds and cooking meat properly are suggested.

Norovirus outbreaks on college and university campuses

Objective: To describe norovirus outbreaks at colleges and universities. Participants: None. Conducted September 2016 to March 2018. Methods: College and university norovirus outbreaks reported to the US National Outbreak Reporting System (NORS, 2009-2016) or published and indexed by EMBASE, PubMed, and Web of Science (1985-2017) were analyzed. Results: Seventy-seven norovirus outbreaks were reported to NORS and 23 were identified in the systematic literature review. Outbreaks occurred more frequently during the beginning of the school year (September-February). NORS outbreaks were more often spread by person-to-person transmission (61%) and, in published outbreaks, by food (57%). The reported exposures of published outbreaks were campus dining (n = 8) and ill food service workers (n = 7). Higher attack rates were associated with smaller on-campus population size, social networks or residences, and specific food exposures. Common control measures were communal area disinfection and health/hygiene education. Conclusions: Recommendations summarized to prevent and control norovirus outbreaks at colleges or universities.

Nucleotide composition and synonymous codon usage of open reading frames in Norovirus GII.4 variants

Norovirus GII.4 variants, a genotype in genogroup II belonging to the genus Norovirus, is a single-strand positive sense RNA containing three open reading frames (ORF1, ORF2 and ORF3) and is the most important pathogen causing nonbacterial gastroenteritis outbreaks. By using bioinformatic softwares such as Codon W, SPSS and so on, a total of 292 strains of the viruses isolated from 1974 to 2016 were analyzed for nucleotide composition and synonymous codon usage in each ORF. The result shows that it is enriched for A over the other bases in nucleotide composition, G behind the other bases in the 3^rd site of all synonymous codons in the three ORFs. The patterns of nucleotide composition and codon bias of ORF2 are similar to those of ORF3 and different from those of ORF1. There are generally UpA motif and CpG motif in the codons with the lowest proportion. Correspondence analysis indicates that the codon usage may be changing over a certain time period for ORF1 in 2006 and 2012, ORF2 in 2012, and ORF3 in 2013. ENC (effective number of codons) plot and other analyses indicate that both natural selection and mutational pressure play partly roles in the ORFs, but natural selection is more important for ORF2 and ORF3. Besides, we also found all optimal codons in the ORFs. The study provides a basic understanding of the mechanism for norovirus GII.4 codon usage bias. AbbreviationsORFOpen Reading FrameENCEffective Number of CodonsCOAcorrespondence analysisRSCURelative Synonymous Codon UsageCAICodon Adaptation IndexCBICodon Bias IndexFopfrequency of optimal codonsL_symnumber of synonymous codonsL_aalength amino acidsGRAVYgrand average of hydropathicityAromaaromaticityCommunicated by Ramaswamy H. Sarma.

Synergistic Effects of Combined Chlorine and Vitamin B1 on the Reduction of Murine Norovirus-1 on the Oyster (Crassostrea gigas) Surface

This study investigated the synergistic effects of combined chlorine (200, 500, 700, and 1000 ppm) and vitamin B₁ (1000, 2000, and 3000 ppm) on the murine norovirus-1 (MNV-1), a human norovirus (NoV) surrogate, on oyster surface. Vitamin B₁ slightly reduced MNV-1 (0.04-0.3 log-reduction), whereas chlorine significantly reduced MNV-1 (0.4-1.0 log-reduction). The combined chlorine and vitamin B₁ resulted in a 0.52-1.97 log-reduction of MNV-1. The synergistic reduction in the MNV titer was not dependent on the concentrations of chlorine and vitamin B₁, and it ranged between 0.08 and 1.03 log₁₀ PFU/mL. The largest synergistic reduction observed was for the combined 700 ppm chlorine and 1000 ppm vitamin B₁. The pH and mechanical texture of the oysters were not significantly changed by the combined 0-1000 ppm chlorine and 3000 ppm vitamin B₁. The overall sensory acceptability were significantly (P < 0.05) reduced in oysters treated with 1000 ppm chlorine and 3000 ppm vitamin B₁ than in those treated with 0-700 ppm chlorine and 3000 ppm vitamin B₁. This study suggests that the combined 700 ppm chlorine and 3000 ppm vitamin B₁ could potentially be used to reduce NoV on oyster surface without causing concomitant changes in the mechanical texture, pH, or sensory qualities of the oysters.

Animals as Reservoir for Human Norovirus

Norovirus is the most common cause of non-bacterial gastroenteritis and is a burden worldwide. The increasing norovirus diversity is currently categorized into at least 10 genogroups which are further classified into more than 40 genotypes. In addition to humans, norovirus can infect a broad range of hosts including livestock, pets, and wild animals, e.g., marine mammals and bats. Little is known about norovirus infections in most non-human hosts, but the close genetic relatedness between some animal and human noroviruses coupled with lack of understanding where newly appearing human norovirus genotypes and variants are emerging from has led to the hypothesis that norovirus may not be host restricted and might be able to jump the species barrier. We have systematically reviewed the literature to describe the diversity, prevalence, and geographic distribution of noroviruses found in animals, and the pathology associated with infection. We further discuss the evidence that exists for or against interspecies transmission including surveillance data and data from in vitro and in vivo experiments.

Presence and Distribution of Histo-Blood Group Antigens in Pacific Oysters and the Effects of Exposure to Noroviruses GI.3 and GII.4 on Their Expression

Noroviruses (NoVs) are one of the most important foodborne viral pathogens worldwide. Oysters are common carriers of NoVs and are responsible for their transmission. NoVs recognize human histo-blood group antigens (HBGAs) as receptors. Recent studies indicate that HBGA-like molecules also exist in oyster tissues and that they may play a key role in the binding of NoVs. However, the mechanism by which different genotypes of NoV accumulate in different oyster tissues is unknown. In this study, the presence and distribution of different types of HBGA-like molecules were evaluated in 240 oysters collected from the Shandong Peninsula of People's Republic of China for 1 year. The HBGA-like molecules were detected at various rates and expressed at different levels in different tissues. Immunohistochemistry confirmed the diversity of HBGA-like molecules in four oyster tissues. Eight types of HBGA-like molecules (types A, B, H1, Lewis x, Lewis y, Lewis a, Lewis b, and precursor) were assessed in different tissues. Of these, the type A HBGA-like molecule was consistently expressed in the gills, digestive tissue, and mantle, while types H1 and Lewis b HBGA-like molecules were expressed in the digestive tissues. The expression of HBGA-like molecules in response to the NoV challenge was investigated. The levels of types A, H1, and Lewis x increased significantly in specific oyster tissues after exposure to genogroup II, genotype 4 (GII.4) or genogroup I, genotype 3 (GI.3) NoV. The real-time reverse transcription PCR assays indicated that GI.3 NoV mainly accumulated in the digestive tissues of oysters, whereas GII.4 NoV accumulated in the gills, mantle, and digestive tissues. These results provide new insights into the mechanism of NoV bioaccumulation in oysters and suggest that NoV accumulation in oysters may be related to the expression of HBGA-like molecules.

Oyster Contamination with Human Noroviruses Impacted by Urban Drainage and Seasonal Flooding in Vietnam

This study investigated the level of norovirus contamination in oysters collected at a lagoon receiving urban drainage from Hue City for 17 months (August 2015-December 2016). We also investigated the genetic diversity of norovirus GI and GII in oyster and wastewater samples by using pyrosequencing to evaluate the effect of urban drainage on norovirus contamination of oysters. A total of 34 oyster samples were collected at two sampling sites (stations A and B) in a lagoon. Norovirus GI was more frequently detected than GII (positive rate 79 vs. 41%). Maximum concentrations of GI and GII were 2.4 × 10⁵ and 2.3 × 10⁴ copies/g, respectively. Co-contamination with GI and GII was observed in 35% of samples. Norovirus GII concentration was higher at station A in the flood season than in the dry season (P = 0.04, Wilcoxon signed-rank test). Six genotypes (GI.2, GI.3, GI.5, GII.2, GII.3, and GII.4) were identified in both wastewater and oyster samples, and genetically similar or identical sequences were obtained from the two types of samples. These observations suggest that urban drainage and seasonal flooding contribute to norovirus contamination of oysters in the study area.

Development of artificial intelligence approach to forecasting oyster norovirus outbreaks along Gulf of Mexico coast

This paper presents an artificial intelligence-based model, called ANN-2Day model, for forecasting, managing and ultimately eliminating the growing risk of oyster norovirus outbreaks. The ANN-2Day model was developed using Artificial Neural Network (ANN) Toolbox in MATLAB Program and 15-years of epidemiological and environmental data for six independent environmental predictors including water temperature, solar radiation, gage height, salinity, wind, and rainfall. It was found that oyster norovirus outbreaks can be forecasted with two-day lead time using the ANN-2Day model and daily data of the six environmental predictors. Forecasting results of the ANN-2Day model indicated that the model was capable of reproducing 19years of historical oyster norovirus outbreaks along the Northern Gulf of Mexico coast with the positive predictive value of 76.82%, the negative predictive value of 100.00%, the sensitivity of 100.00%, the specificity of 99.84%, and the overall accuracy of 99.83%, respectively, demonstrating the efficacy of the ANN-2Day model in predicting the risk of norovirus outbreaks to human health. The 2-day lead time enables public health agencies and oyster harvesters to plan for management interventions and thus makes it possible to achieve a paradigm shift of their daily management and operation from primarily reacting to epidemic incidents of norovirus infection after they have occurred to eliminating (or at least reducing) the risk of costly incidents.

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.

Foodborne Norovirus State of Affairs in the EU Rapid Alert System for Food and Feed

The European Union Rapid Alert System for Food and Feed (EU RASFF) database is an invaluable instrument for analyzing notifications involving norovirus in food. The aim of this work was to carry out a thorough research of the alert and border rejection notifications submitted in the RASFF database from its onset until 31 August 2017. Some conclusions of interest were: (i) Denmark, France, Italy, the Netherlands and Norway have contributed the majority of alert notifications as notifying countries, (ii) France and Serbia have been cited more often in alert notifications as countries of origin, (iii) Italy and Spain have submitted the majority of border rejection notifications, (iv) Third Countries implicated more frequently in border rejection notifications for norovirus in bivalve molluscs were Vietnam and Tunisia, whereas in fruits and vegetables were China and Serbia, (v) "risk dispersion" from norovirus-contaminated food was narrow since, in just over half of all alert notifications and all of the border rejection notifications, only up to three countries were involved, and (vi) both raw (oysters and berries) and cooked (mussels) food products can present a health risk to consumers. The information retrieved from the RASFF database on norovirus-contaminated food could prove helpful in the planning of future norovirus risk analysis endeavors.

Molecular screening of blue mussels indicated high mid-summer prevalence of human genogroup II Noroviruses, including the pandemic "GII.4 2012" variants in UK coastal waters during 2013

This molecular study is the first report, to the best of our knowledge, on identification of norovirus, NoV GII.4 Sydney 2012 variants, from blue mussels collected from UK coastal waters. Blue mussels (three pooled samples from twelve mussels) collected during the 2013 summer months from UK coastal sites were screened by RT-PCR assays. PCR products of RdRP gene for noroviruses were purified, sequenced and subjected to phylogenetic analysis. All the samples tested positive for NoVs. Sequencing revealed that the NoV partial RdRP gene sequences from two pooled samples clustered with the pandemic "GII.4 Sydney variants" whilst the other pooled sample clustered with the NoV GII.2 variants. This molecular study indicated mussel contamination with pathogenic NoVs even during mid-summer in UK coastal waters which posed potential risk of NoV outbreaks irrespective of season. As the detection of Sydney 2012 NoV from our preliminary study of natural coastal mussels interestingly corroborated with NoV outbreaks in nearby areas during the same period, it emphasizes the importance of environmental surveillance work for forecast of high risk zones of NoV outbreaks.

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.

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

Modeling and Prediction of Oyster Norovirus Outbreaks along Gulf of Mexico Coast

BACKGROUND

Oyster norovirus outbreaks often pose high risks to human health. However, little is known about environmental factors controlling the outbreaks, and little can be done to prevent the outbreaks because they are generally considered to be unpredictable.

OBJECTIVE

We sought to develop a mathematical model for predicting risks of oyster norovirus outbreaks using environmental predictors.

METHODS

We developed a novel probability-based Artificial Neural Network model, called NORF model, using 21 years of environmental and norovirus outbreak data collected from Louisiana oyster harvesting areas along the Gulf of Mexico coast, USA. The NORF model involves six input variables that were selected through stepwise regression analysis and sensitivity analysis.

RESULTS

We found that the model-based probability of norovirus outbreaks was most sensitive to gage height (the depth of water in an oyster bed) and water temperature, followed by wind, rainfall, and salinity, respectively. The NORF model predicted all historical oyster norovirus outbreaks from 1994 through 2014. Specifically, norovirus outbreaks occurred when the NORF model probability estimate was > 0.6, whereas no outbreaks occurred when the estimated probability was < 0.5. Outbreaks may also occur when the estimated probability is 0.5-0.6.

CONCLUSIONS

Our findings require further confirmation, but they suggest that oyster norovirus outbreaks may be predictable using the NORF model. The ability to predict oyster norovirus outbreaks at their onset may make it possible to prevent or at least reduce the risk of norovirus outbreaks by closing potentially affected oyster beds.

CITATION

Wang J, Deng Z. 2016. Modeling and prediction of oyster norovirus outbreaks along Gulf of Mexico coast. Environ Health Perspect 124:627-633; http://dx.doi.org/10.1289/ehp.1509764.

Detection and Genetic Analysis of Noroviruses and Sapoviruses in Sea Snail

An outbreak of acute gastroenteritis occurred at a restaurant in Yokohama in December 2011. Because many of the customers had consumed raw sea snail, sea snail was suspected to be the source of this outbreak. To determine whether sea snail contains Norovirus (NoV) or Sapovirus (SaV), we analyzed 27 sea snail samples collected over 5 months (May, June, August, October, and December 2012) and 59.3% were positive for NoV and/or SaV. The levels of NoV ranged from 1.5 × 10(3) to 1.5 × 10(5) copies/g tissue, and those of SaV from 1.5 × 10(2) to 1.3 × 10(3) copies/g tissue. The highest levels were observed in sea snails collected in December. A phylogenetic analysis of the NoVs showed that the viral strains were NoV genotypes GI.4, GI.6, GII.4, GII.12, GII.13, and GII.14, and the SaV strains were genotypes GI.2 and GI.3. The NoV GII.4 Sydney 2012 variants were only detected in December. This variant was a major source of gastroenteritis in Japan in the winter of 2012/2013. In contrast, the NoV GII.4 strains detected in May and June 2012 were not the Sydney 2012 variant. This study demonstrates that sea snail contains multiple genogroups and genotypes of NoV and SaV strains. We conclude that the sea snail presents a risk of gastroenteritis when consumed raw.

Modeling system for predicting enterococci levels at Holly Beach

This paper presents a new modeling system for nowcasting and forecasting enterococci levels in coastal recreation waters at any time during the day. The modeling system consists of (1) an artificial neural network (ANN) model for predicting the enterococci level at sunrise time, (2) a clear-sky solar radiation and turbidity correction to the ANN model, (3) remote sensing algorithms for turbidity, and (4) nowcasting/forecasting data. The first three components are also unique features of the new modeling system. While the component (1) is useful to beach monitoring programs requiring enterococci levels in early morning, the component (2) in combination with the component (1) makes it possible to predict the bacterial level in beach waters at any time during the day if the data from the components (3) and (4) are available. Therefore, predictions from the component (2) are of primary interest to beachgoers. The modeling system was developed using three years of swimming season data and validated using additional four years of independent data. Testing results showed that (1) the sunrise-time model correctly reproduced 82.63% of the advisories issued in seven years with a false positive rate of 2.65% and a false negative rate of 14.72%, and (2) the new modeling system was capable of predicting the temporal variability in enterococci levels in beach waters, ranging from hourly changes to daily cycles. The results demonstrate the efficacy of the new modeling system in predicting enterococci levels in coastal beach waters. Applications of the modeling system will improve the management of recreational beaches and protection of public health.

Evaluation of Immunomagnetic Separation Method for the Recovery of Hepatitis A Virus and GI.1 and GII.4 Norovirus Strains Seeded on Oyster and Mussel

Outbreaks of viral diseases are frequently associated with the consumption of minimally processed shellfish. Among the viruses in these outbreaks, hepatitis A virus (HAV) and human norovirus (NoV) have been increasingly reported as the most common food-borne pathogens. These viruses must be concentrated in tested samples in order to be detected. In this study, a method for the detection of NoV and HAV in shellfish using an immuno-magnetic separation (IMS) procedure combined with reverse transcriptase (RT)-PCR was developed. The IMS/RT-PCR method was applied to investigate the recovery rates of HAV, NoV GI.1, and GII.4 from oyster and mussel. Based on IMS/RT-PCR results, recovery rates for HAV from oyster and mussel test samples were 2.4 and 1.1%, respectively. The NoV GI.1 recovery rates from oyster and mussel samples were 4.9-9.2% (mean 6.9%) and 4.3-8.6% (mean 6.2%), respectively, and the NoV GII.4 recovery rates were 8.8 and 8.5%, respectively. These results verified that HAV, NoV GI.1, and GII.4 can be detected in all the test samples using the IMS/RT-PCR method, although the three inoculated viruses were recovered with low efficiency. In conclusion, the IMS/RT-PCR method can be used to efficiently and rapidly detect viruses such as HAV and NoV in shellfish such as oyster and mussel.

Detection and quantification of hepatitis A virus and norovirus in Spanish authorized shellfish harvesting areas

An 18-month survey was conducted in ten class "B" harvesting areas from two Galician Rias (NW of Spain), the most important bivalve production area in Europe, to determine the prevalence of hepatitis A virus (HAV) and human norovirus (NoV), including genogroups I (GI) and II (GII). Quantification was performed by reverse transcription real-time PCR (RT-qPCR), according to the recently developed standard method ISO/TS 15216-1:2013. Four bivalve species were studied, including wild and cultured mussels (Mytilus galloprovincialis), clams (Venerupis philippinarum and Venerupis decussata) and cockles (Cerastoderma edule). Overall, 55.4% of samples were contaminated by at least one of the studied viruses, being detected the simultaneous presence of two or three viruses in 11.3% of the cases. NoV GI was the most prevalent virus (32.1%), followed by NoV GII (25.6%) and HAV (10.1%). Cultured mussels showed the highest percentage of positive samples (61.4%), followed by cockles (59.4%), wild mussels (54.3%) and clams (38.7%). Viral contamination levels for most of the positive samples ranged from 10(2) to 10(3) RNA copies/g of digestive tissue (RNAc/g DT). The presence of viral contamination was statistically higher (P<0.0001) in warm months (April to September) than in cold months (October to March). The data presented here may contribute to the development of more representative sampling strategies, in monitoring and management of shellfish growing areas as well as being useful in a future scenario in which viral critical values are adopted in legislation.

Hand-foot-and-mouth disease and weather factors in Guangzhou, southern China

Hand-foot-and-mouth disease (HFMD) is becoming one of the common airborne and contact transmission diseases in Guangzhou, southern China, leading public health authorities to be concerned about its increased incidence. In this study, we aimed to examine the effect of weather patterns on the incidence of HFMD in the subtropical city of Guangzhou for the period 2009–2012, and assist public health prevention and control measures. A negative binomial multivariable regression was used to identify the relationship between meteorological variables and HFMD. During the study period, a total of 166 770 HFMD-confirmed cases were reported, of which 11 died, yielding a fatality rate of 0·66/10 000. Annual incidence rates from 2009 to 2012 were 132·44, 311·40, 402·76, and 468·59/1 000 00 respectively. Each 1°C rise in temperature corresponded to an increase of 9·38% (95% CI 8·17–10·51) in the weekly number of HFMD cases, while a 1 hPa rise in atmospheric pressure corresponded to a decrease in the number of cases by 6·80% (95% CI −6·99 to −6·65), having an opposite effect. Similarly, a 1% rise in relative humidity corresponded to an increase of 0·67% or 0·51%, a 1 m/h rise in wind velocity corresponded to an increase of 4·01% or 2·65%, and a 1 day addition in the number of windy days corresponded to an increase of 24·73% or 25·87%, in the weekly number of HFMD cases, depending on the variables considered in the model. Our findings revealed that the epidemic status of HFMD in Guangzhou is characterized by high morbidity but low fatality. Weather factors had a significant influence on occurrence and transmission of HFMD.

Progress towards the prevention and treatment of norovirus infections

Noroviruses are now recognized as the major cause of acute gastroenteritis in the developed world, yet our ability to prevent and control infection is limited. Recent work has highlighted that, while typically an acute infection in the population, immunocompromised patients often experience long-term infections that may last many years. This cohort of patients and those regularly exposed to infectious material, for example, care workers and others, would benefit greatly from the development of a vaccine or antiviral therapy. While a licensed vaccine or antiviral has yet to be developed, work over the past 10 years in this area has intensified and trials with a vaccine candidate have proven promising. Numerous antiviral targets and small molecule inhibitors that have efficacy in cell culture have now been identified; however, further studies in this area are required in order to make these suitable for clinical use.