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Appl Environ Microbiol. 2011 May; 77(9): 2968–2974.
PMCID: PMC3126400

Year-Round Prevalence of Norovirus in the Environment of Catering Companies without a Recently Reported Outbreak of Gastroenteritis[down-pointing small open triangle]

Abstract

Food handlers play an important role in the transmission of norovirus (NoV) in food-borne outbreaks of gastroenteritis (GE). In a year-round prevalence study, the prevalence of NoV in catering companies without recently reported outbreaks of GE was investigated and compared to the observed prevalence in catering companies with recently reported outbreaks. Swab samples were collected from surfaces in the kitchens and (staff) bathrooms in 832 randomly chosen companies and analyzed for the presence of NoV RNA. In total, 42 (1.7%) out of 2,496 environmental swabs from 35 (4.2%) catering companies tested positive. In contrast, NoV was detected in 147 (39.7%) of the 370 samples for 44 (61.1%) of the 72 establishments associated with outbreaks of gastroenteritis. NoV-positive swabs were more frequently found in winter, in specific types of companies (elderly homes and lunchrooms), and in establishments with separate bathrooms for staff. We found a borderline association with population density but no relation to the number of employees. Sequence analysis showed that environmental strains were interspersed with strains found in outbreaks of illness in humans. Thus, the presence of NoV in catering companies seemed to mirror the presence in the population but was strongly increased when associated with food-borne GE. Swabs may therefore serve as a valuable tool in outbreak investigations for the identification of the causative agent, although results should be interpreted with care, taking into account all other epidemiological data.

INTRODUCTION

Noroviruses (NoV) have emerged as the most common cause of outbreaks, as well as sporadic cases of acute nonbacterial gastroenteritis in children and adults. These viruses are easily transmitted from person to person by the fecal-oral route, either directly or indirectly, via contaminated surfaces, water, or food (18), often involving food workers. The role of food handlers in the transmission of NoV has been shown by epidemiological studies and/or molecular diagnostics in fecal specimens from both patients and food handlers (11). Transmission by food handlers most likely occurs through contact of bare hands or contaminated surfaces with food, which has been studied in experimental settings (1, 2). In a series of 3 recent papers reviewing published data from 816 food worker-related outbreaks occurring between 1927 and 2006, food service facilities, e.g., restaurants and hotels, were the settings most often implicated (15, 26), and bare-hand contact with food followed by failure to properly wash hands was the factor associated with the involvement of the infected worker (27).

Food workers epidemiologically implicated as a source of an outbreak of gastroenteritis may deny illness because of fears of job loss and forced time off without pay. Denial of illness may complicate identification of the source of the outbreak, as do the absence of leftover food items, the absence of clinical specimens, or difficulties encountered when analyzing food items, as discussed previously (5, 11, 27). Environmental swab samples have been used to make advantage of the fact that excreted pathogens will likely be present adjacent to the site of excretion or left on inanimate surfaces after excretion. This has been demonstrated for both viral (13, 25) and bacterial (7, 10, 12) pathogens, and also for NoV in institutional settings (8, 14, 31).

Recently, environmental swabs have been applied to determine the presence of NoV on surfaces in settings associated with food-borne outbreaks. NoV RNA was detected in about one-third of the swab samples taken from kitchen surfaces and in about two-thirds of swab samples from the (staff) bathrooms associated with the outbreaks (5). The relevance of the NoV sequences detected was demonstrated by the finding of identical sequences in fecal and/or food samples or even on the hand of a food worker (5, 6).

From these studies, the question arose as to whether NoV can also be detected in catering companies without recently reported outbreaks of gastroenteritis. To answer this question, environmental swab samples were collected from surfaces in the kitchens and (staff) bathrooms in 832 randomly chosen catering companies in the Netherlands visited in 2008 and 2009 and were subsequently analyzed for the presence of NoV RNA. The outcomes of these analyses were compared with the outcomes of laboratory investigations, using the same techniques, initiated after 72 (food-borne) outbreaks of gastroenteritis in the period from January 2006 to January 2009. In addition, risk factor analysis was performed to investigate whether the presence of NoV on surface samples was related to the company type, number of employees, or hand washing facilities, as well as seasonal and geographical aspects. Finally, NoV sequences detected in catering companies were compared to those derived from diagnostic fecal samples using phylogenetic analyses in combination with epidemiological data in an attempt to find clues to linkages between catering companies that tested positive for NoV and reported human outbreaks.

MATERIALS AND METHODS

Statistical-power analysis.

It was calculated that a sample volume of 1,056 companies without recent outbreaks of gastroenteritis would be required to find an expected prevalence of NoV in catering companies of at least 1%, with a power of 95% confidence and an error of the final estimation of 0.6%. For this reason, the study aimed at sampling at least 1,000 catering companies within the study period.

Sampling-prevalence study.

During routine inspections, inspectors from the Dutch Food and Consumer Product Safety Authority (nVWA) completed a questionnaire to obtain information on the number of employees and the presence or absence of separate staff bathrooms and/or hand-washing facilities. In addition, environmental swabs were collected as described previously (5). Inspections were scheduled so that sampling was distributed evenly throughout the whole study period (January 2008 to February 2009). Sampling was proportional to the number of catering companies within each of the working regions of the five VWA departments in the Netherlands (Fig. 1), and sampling occurred in companies not associated with recently reported outbreaks of gastroenteritis. Three swabs were collected as follows. The first swab was used to collect a surface sample from the grip of a refrigerator, the grip of the knife used to cut bread, and the handles of a cutting or mixing machine. The second swab was used to collect a surface sample from the pepper-and-salt set and from the soap dispenser in the kitchen. The third swab was used to collect a surface sample from the flushing chain or knob and the toilet seat (both upper and under surfaces) in the men's (employees') bathroom only. Samples were stored at 5°C until analyses were performed.

Fig. 1.
Geographical regions of the Netherlands, showing the working regions of the five VWA departments. Scale bar, 50 km.

Outbreak investigation.

Inspectors collected 1 to 10 environmental swab samples for the analyses of the presence of NoV at each site involved in an outbreak investigation reported in the period from January 2006 to January 2009.

Environmental swab samples were either kept at 4°C or kept frozen at −20°C during transport and stored frozen at −20°C until they were processed at the laboratory of the nVWA.

Viral extraction and detection.

Nucleic acids were extracted from the swabs as described previously (5). RNA samples were analyzed for the presence of NoV GI types using the N1cap nested real-time PCR assay (5) and were analyzed for the presence of NoV GII types using a two-step real-time reverse transcription (RT)-PCR format modified from the previously described N2pol nested real-time RT-PCR assay (4). In brief, a mixture of 3 μl of RNA (5% of total extracted RNA), 1 μM JV13I RT primer (28), 1 U/μl of Moloney murine leukemia virus (M-MuLV) RNase H+ reverse transcriptase (DyNAmo cDNA synthesis kit; Finnzymes), and 1× RT buffer (DyNAmo cDNA synthesis kit; Finnzymes) in a volume of 10 μl was incubated at 46°C for 1 h, and the enzyme was inactivated at 85°C for 5 min. Subsequently, 2.5 μl of cDNA was amplified using the N2pol real-time PCR assay as described previously (4).

Sequence analyses.

NoV presumptive positive samples, as judged by the presence of a typical S curve in the amplification plot, were reamplified and sequenced as described previously (5). In brief, for GI-positive samples, 2.5 μl of the completed JJV1F/SR1-1R RT-PCR (4) was added to 22.5 μl PCR mixture consisting of 1× FastStart PCR buffer, 0.6 U FastStart Taq DNA polymerase, 2.0 mM MgCl2, 0.25 mM each deoxynucleoside triphosphate (dNTP) (all Roche Diagnostics, Almere, Netherlands), and 0.5 μM primers SR1-2F and SR1-3R (16). The PCR amplification consisted of an initial 5-min denaturation at 94°C followed by 40 cycles of denaturation at 94°C for 60 s, annealing at 37°C for 90 s, and extension at 72°C for 1 min, with a 7-min final extension at 72°C (3). For sequence analyses of GII-positive samples, 2.5 μl of the completed GII cDNA synthesis reaction mixture was added to 22.5 μl PCR mixture and amplified as described above, the only exception being the choice of primers (JV12Y and NoroII-R) (3).

Amplification products were analyzed by gel electrophoresis, and bands of PCR products were extracted and purified using the High Pure PCR Product Purification kit (Roche Diagnostics) and subsequently sent for sequence analyses to an external commercial laboratory (BaseClear, Leiden, Netherlands). Genotypes were assigned on the basis of their similarity to reference strains representing known genotypes using the public NoV-typing library (http://www.rivm.nl/mpf/norovirus/typingtool).

Phylogenetic analysis.

NoV sequences detected in the prevalence study were compared with sequences from strains detected during outbreak investigations by the nVWA in the period from January 2008 to February 2009. In addition, all sequences were compared with NoV outbreak strains detected in humans involved in outbreaks and for which clinical samples had been sent in for diagnosis at the Institute for Public Health and the Environment in the Netherlands from January 2008 through September 2009 (n = 231). For the latter, the target regions differ slightly from the nVWA target region, as described previously (4, 6). Sequences were selected if comparison resulted in an overlapping region of at least 100 nucleotides (nt). Selected sequences (n = 255) were aligned and analyzed using unweighted-pair group method using average linkages (UPGMA) cluster analysis, multiple comparisons, and global clustering in Bionumerics 5.1 (Applied Maths, Belgium).

Data analysis.

The frequencies of NoV presence in swab samples found in the prevalence study were compared with those during outbreak investigations. To determine whether the prevalence of NoV was significantly different between seasons and types of companies, P values were calculated using χ2. To evaluate the use of swabs as a diagnostic tool during outbreaks, the sensitivity and specificity were calculated using the following definitions. Sensitivity, or true positives, of swabs as a diagnostic method for possible involvement of a food establishment in an outbreak was defined as the proportion of positive tested outbreaks among all suspected food-borne outbreaks reported to the nVWA, i.e., based on the outbreak investigations. Specificity, or true negatives, of swabs as a diagnostic method for possible involvement of a food establishment in an outbreak was defined as the proportion of negative tested establishments among all tested establishments not involved in a food-borne outbreak, i.e., based on the prevalence study.

Univariate logistic regression analysis was performed to identify possible risk factors for the presence of NoV in establishments not involved in food-borne outbreaks, knowing that odds ratios (OR) from these analyses can be interpreted as risk ratios if the prevalence is <10% (32). First, catering companies were divided into NoV-positive companies and NoV-negative companies. Subsequently, the following potential risk factors were analyzed: sampling season, geographic region, company size, presence of staff facilities, and company type. The sampling season was categorized as high (norovirus season, November, December, January, February, and March) versus low (norovirus off-season, April to October) based on frequencies as found in a European outbreak surveillance of nonepidemic seasons (20); the geographic region was analyzed separately in 5 regions and defined as high-population-density regions (>4 × 102 inhabitants/km2; regions 2, 4, and 5 in Fig. 1) versus low-population-density regions (<4 × 102 inhabitants/km2; regions 1 and 3 in Fig. 1); company size was defined as small companies, with less than 10 employees, versus companies with 10 or more employees. Staff facilities included the presence or absence of a separate toilet, hand-washing facilities, and hand-drying facilities for staff only. Company types included canteen, take-out food, elderly home, snack bar, cafeteria, lunchroom, bakery, pension or hotel, and restaurant.

Because a logistic regression model can be considered valid only if the number of parameters is ≤10% of the number of companies in the smallest group, the data allowed a maximum of 4 categories to be analyzed. For this reason, the 9 categories of “company type” were analyzed as one variable, as well as 9 separate variables for each setting. In addition, in order to identify the most prominent risk factors among company characteristics likely to be correlated, we performed multivariate analysis for the following variables of company characteristics: company size and the presence of separate staff facilities. Variables remained in the multivariate model if P values were <0.10, while the backward selection procedure was used.

All risk factors were considered significant for P values of <0.05 and borderline significant for 0.05 < P value < 0.10. All results are presented, including the 95% confidence interval (CI) or P value.

RESULTS

Prevalence study: detection of NoV on environmental swabs in companies without recently reported outbreaks.

In the period from January 2008 to February 2009, a total of 2,496 swab samples were collected for analyses of the presence of NoV at 832 catering companies without a recently reported outbreak of gastroenteritis. Due to external factors that were beyond the control of the investigators, the goal of 1,000 companies could not be reached, and the number of inspections per months also showed some variation in time. In total 42 (1.7%) out of 2,496 environmental swabs from 35 (4.2%) catering companies tested positive for NoV (Tables 1 and and2),2), with threshold cycle (CT) values between 15.7 and 32.8 for GI types and CT values between 28.0 and 42.1 for GII types. At five catering companies, multiple samples tested positive. Of the 42 positive swab samples, 26 (61.9%) samples were taken from surfaces in the bathroom and 16 (38.1%) were taken from surfaces in the kitchen. Overall, NoV was detected three times more often on surfaces in the bathroom (26/832; 3.1%) than on surfaces in the kitchen (16/1,664; 0.96%). Assuming that swab testing would be used as a diagnostic method for possible involvement of a food establishment in an outbreak, this indicated a specificity of 95.8% (797/832) overall.

Table 1.
Detection of NoV in environmental samples from catering companies with and without association with recently reported gastroenteritis
Table 2.
Distribution of NoV-positive environmental samples over different types of catering companies

Outbreak study: detection of NoV on environmental swabs collected during an outbreak.

In the period from January 2006 to January 2009, 370 environmental swab samples were collected for analyses of the presence of NoV at 72 sites implicated in a viral gastroenteritis outbreak investigation where food-borne transmission was suspected. The presence of NoV was demonstrated for 44 (61.1%) of the 72 sites under investigation and in 147 (39.7%) of the 370 samples analyzed (Table 1). As observed in the prevalence survey, NoV was more frequently detected if the samples had been taken from surfaces in bathrooms (52.9%) than if they had been taken from surfaces in the kitchen (29.4%). Assuming that swab testing would be used as a diagnostic method to predict involvement of a food establishment in an outbreak, this indicated a sensitivity of 61.1% (44/72) overall.

Effect of seasons on the prevalence of NoV in catering industries.

NoV was detected 4 times more frequently on swabs collected from companies inspected in the norovirus season, November to March (28/480; 5.8%), than on swabs collected from companies inspected in the typical norovirus off-season, April to September (7/352; 2.0%) (P = 0.006). In univariate analysis, the risk of NoV presence was found to be significantly higher during the high season (OR, 3.1; 95% CI, 1.3 to 7.1) (Table 3). These findings indicate a seasonal difference in the above-mentioned specificity for swabs as a diagnostic method for possible involvement of a food establishment in an outbreak, i.e., a specificity of 94.2% (452/480) in the high season compared to 98% (345/352) in the off-season.

Table 3.
Significant and borderline risk factors for the presence of NoV in catering industries

Effects of characteristics of catering industries on the prevalence of NoV.

During the prevalence study, most of the inspections were performed in restaurants (n = 446), followed by lunchrooms (n = 112). To a lesser extent, other types of companies, for example, food establishments/kitchens for elderly homes or hotels, were also visited for inspection. The prevalence of NoV on surfaces among these different types of catering companies varied significantly (P = 0.015), although the numbers for some of the company types were low (Tables 2 and and3).3). In univariate analysis, the 9-category variable resulted in an invalid model. When all company types were entered as separate variables in multivariate logistic regression models to enable identification of a potential difference between company types, the elderly home (OR, 8.7; 95% CI, 2.7 to 28.8) and lunch rooms (OR, 2.4; 95% CI, 1.0 to 5.4) showed statistically significant risk of NoV presence. A risk (OR, 6.1; 95% CI, 0.7 to 54.7) was also found for hotels and pensions, showing a borderline significant risk of NoV presence.

The presence of NoV on surfaces appeared not to be significantly related to the number of employees, including serving, dishwashing, and cleaning employees (data not shown). However, the prevalence of NoV was twice as high in catering companies with separate staff bathrooms (5.6%) as in catering companies without separate staff bathrooms (2.8%), resulting in significant univariate risk (OR, 2.1; 95% CI, 1.0 to 4.2) (Tables 2 and and3).3). This finding was irrespective of the company size or whether hand-washing facilities were present, absent, or only in the near vicinity and irrespective of hands being dried by blowers, towels, or paper.

The distribution of sampling over the five regions was scheduled to be in relation to the number of catering companies in each region (Fig. 1). When the 5 regions were compared separately, no statistical differences were found in the norovirus prevalence. When low- and high-density regions were clustered together, the data suggested that regions with a lower population density had a lower NoV prevalence than regions with a higher population density (Tables 2 and and3),3), which appeared borderline statistically significant (P < 0.09), showing that this prevalence seems to follow the density of population in these regions.

Typing of NoV RNA detected on environmental surfaces.

In the prevalence study, GI NoV strains were detected in samples collected from two companies, whereas GII NoV strains were detected in samples collected from 33 companies. Sequence analyses were not always successful, as for some GII presumptive positive samples, the signal was too weak. GII strains that were sequenced had been detected by real-time assay at a CT value between 28.0 and 41.2, whereas strains that could not be sequenced had been detected at a CT value between 40.2 and 42.1. For 25 of the 35 positive catering companies, the genotypes of the positive samples could be successfully determined (Fig. 2, top). GII.4 was the most frequently detected genotype, including various GII.4 variants, whereas genotypes GI.2, GI.4, GIIb, and GII.2 were detected only once or twice. For three companies with multiple positive samples, identical sequences were obtained for the two or three samples.

Fig. 2.
NoV genotypes detected on environmental swabs. Shown are the different NoV genotypes detected on environmental swabs during the prevalence study (top) and during outbreak investigations (bottom). The number of companies with NoV on swabs per number of ...

During the year-round prevalence study, NoV strains were also detected in samples collected from surfaces in companies with a reported outbreak, including 4 GI NoV strains and 9 GII NoV strains (Fig. 2, bottom). In the 3-year period from January 2006 to January 2009, NoV was detected in 44 (61.1%) out of 72 companies associated with a reported outbreak. In 38 of these outbreaks, sequences were obtained, including 31 GII strains, with GII.4 the most frequently detected genotype, and 7 GI strains. The finding of multiple GI.3 food-borne outbreaks within a 3- to 4-month period (October 2007 to February 2008), all with GI.3-positive swab samples and one with a GI.3-positive food sample (salami) (data not shown), was remarkable.

Comparison of background sequences and sequences from clinical specimens.

Phylogenetic analyses (150 nt) using data obtained from the clinical samples collected showed that the sequences of strains present in catering companies were interspersed with those circulating in Dutch patients. Comparative sequence analysis was performed to identify possible clustering using sequences detected during the prevalence study in catering companies (n = 25) or during food-borne outbreak investigations (n = 13) (either food or swab samples, both in the period from January 2008 to January 2009) and sequences obtained from reported outbreaks of gastroenteritis, i.e., clinical samples collected in the period January 2008 through September 2009 (n = 231).

Thirty-five clusters were identified, all consisting of 100% identical sequences. Most clusters (22 GII.4 and 3 GIIe) consisted of clinical samples only. Four clusters (two GII.4 and two GIIb) consisted of sequences obtained from clinical samples and from environmental samples (e.g., oysters or swabs) collected during food-borne outbreaks without established epidemiological associations. The remaining 6 clusters (5 GII.4 and 1 GIIb) all consisted of at least one sequence detected during the prevalence study and were elaborated to present the divergence in time and location between matching catering companies and outbreak events (Table 4). For some clusters (no. 2, 4, and 5 [Table 4]), the strains first appeared in the catering companies before being reported in outbreaks, whereas in other cases (no. 1 and 3), the reverse was the case. The most striking was the GIIb cluster (no. 1), with a temporal spacing of as little as 12 days and a geographical spacing of only 18 km. No GI clusters were identified.

Table 4.
Clusters of 100% identical sequences through surveillance in food establishments and reported outbreaks of gastroenteritis

DISCUSSION

The present study demonstrated that NoV can be detected on environmental surfaces in catering companies associated with NoV outbreaks and at much lower frequency in companies without a reported outbreak. The occurrence of NoV on surfaces in the prevalence study also showed strong seasonality, and the strains were similar to those identified in humans, suggesting that the presence of NoV in catering companies mirrors its presence in the population. The prevalence of NoV on surfaces in companies without recently reported outbreaks (4.2%) was significantly lower than that in outbreak settings (61.1%). Environmental swabs may therefore serve as a valuable tool in outbreak investigations for the identification of the causative agent, with a sensitivity of 61.1% and a specificity of 95.8%, although results should be interpreted with caution, taking into account all other epidemiological data.

Combining epidemiological and sequence data has allowed the linking of suspected foods and outbreaks (11). In a previous study, the value of swab analyses was demonstrated by the higher detection rate of NoV in environmental samples than in food testing alone, whereas the relevance of the NoV sequences detected on the swabs was demonstrated by finding identical sequences in fecal and food samples for seven outbreaks (5) or on the hands of a staff member (6). In our study, six clusters of identical sequences were identified. The temporal and geographical divergence within clusters was determined using data on the moments and the locations of sampling of the clinical and environmental swab samples. However, no conclusive data on transmission routes could be elucidated, because of the short sequence and because the data were linked retrospectively, precluding extensive follow-up. It appeared to be impossible to reamplify and subsequently type all presumptive positive samples using a different set of primers. This was likely due to the extremely low viral load present in these samples, as suggested by high CT values, between 40.2 and 42.1. As the corresponding amplification plots of the real-time signals still met the criterion of an S curve and could clearly be distinguished from low background noise, and because target-specific oligonucleotides had been used, these surface samples should be regarded as indicative of the presence of NoV.

GI strains were also found in the catering companies, which is remarkable, as most food handler-associated NoV outbreak strains belong to GII (5, 17, 30), while in a few studies, GI strains have a stronger association with shellfish or water-related outbreaks than with person-to-person outbreaks (17).

Logistic regression of the characteristics of the catering companies in this study allowed identification of several risk factors for the presence of NoV in catering companies. Norovirus was present significantly more often in catering companies with a recently reported outbreak of gastroenteritis, but also when inspections were performed during NoV season (November to March) in high-population-density regions. Risk factors related to seasonality had been anticipated, as NoV infections are regarded as a winter vomiting disease (21), a finding that also was concluded from analysis of combined European virological and epidemiological data (20). With regard to population density, a higher population density facilitates person-to-person transmission of NoV, which may consequently increase the risk for food-handlers to become infected, which increases the risk of kitchen surfaces becoming contaminated with NoV. In agreement with outbreak data collected between 2003 and 2009 by inspectors from the Dutch Food and Consumer Product Safety Authority, the number of outbreak investigations in high-population-density areas was 3 to 4 times higher than in low-density areas (P < 0.001) (data not shown).

Although based on small numbers, an elevated risk for the presence of NoV on surfaces in elderly homes was observed compared to restaurants. Norovirus outbreaks commonly occur in (semi-) closed settings, such as institutions (19) and cruise ships (9, 29), where crowding and possibly lower standards of hygiene may enhance NoV transmission. Contamination of surfaces with NoV has been demonstrated to be widespread in these settings (8, 14, 31), serving as a source of infection, including for the kitchen staff. As it is undesirable to have NoV present in areas where food is prepared for fragile persons in institutions, the elevated risk for the presence of NoV on surfaces in elderly homes warrants further investigation.

Immunocompetent persons may shed NoV without clinical symptoms for up to 3 weeks, whereas shedding may be even longer for persons with impaired immunity (14, 23, 24). A recent paper reported that the age-adjusted prevalence of asymptomatic NoV infection in England was 12%, and it displayed winter seasonality (22). Shedding in combination with inappropriate personal hygienic measures may easily lead to contamination of surfaces or food, which also applies when hands are not properly washed after staff clean bathrooms or change diapers. Education of food handlers and consistent enforcement of measures such as strict hand hygiene and use of effective environmental disinfectants are therefore badly needed to reduce transmission within these catering companies. To our surprise, having separate bathroom facilities for staff was shown to be an increased risk for the presence of NoV in catering companies, which may be associated with different cleaning programs for staff and guest facilities, but for which no evidence is yet present.

In conclusion, the presence of NoV in the Dutch population is reflected by the presence of NoV on environmental surfaces in catering companies not associated with a recently reported outbreak of gastroenteritis. The higher prevalence of environmental contamination during outbreaks suggests that swabs may be used as an adjunct to clinical diagnosis of NoV during outbreaks.

ACKNOWLEDGMENTS

We thank all officers of the Food and Consumer Product Safety Authority and regional Public Health Services involved in collecting samples and Harry Vennema for advice on the phylogenetic analyses.

Footnotes

[down-pointing small open triangle]Published ahead of print on 4 March 2011.

REFERENCES

1. Bidawid S., Farber J. M., Sattar S. A. 2000. Contamination of foods by food handlers: experiments on hepatitis A virus transfer to food and its interruption. Appl. Environ. Microbiol. 66:2759–2763 [PMC free article] [PubMed]
2. Bidawid S., Malik N., Adegbunrin O., Sattar S. A., Farber J. M. 2004. Norovirus cross-contamination during food handling and interruption of virus transfer by hand antisepsis: experiments with feline calicivirus as a surrogate. J. Food Prot. 67:103–109 [PubMed]
3. Boxman I. L. A., et al. 2006. Detection of noroviruses in shellfish in the Netherlands. Int. J. Food Microbiol. 108:391–396 [PubMed]
4. Boxman I. L. A., et al. 2007. An efficient and rapid method for recovery of norovirus from food associated with outbreaks of gastroenteritis. J. Food Prot. 70:504–508 [PubMed]
5. Boxman I. L. A., et al. 2009. Environmental swabs as a tool in outbreak investigation, including outbreaks on cruise ships. J. Food Prot. 72:111–119 [PubMed]
6. Boxman I. L. A., et al. 2009. Norovirus on swabs taken from hands illustrate route of transmission, a case study. J. Food Prot. 72:1753–1755 [PubMed]
7. Carrique-Mass J. J., Davies R. H. 2008. Sampling and bacteriological detection of Salmonella in poultry and poultry premises: a review. Rev. Sci. Tech. 27:665–677 [PubMed]
8. Cheesbrough J. S., Green J., Gallimore C. I., Wright P. A., Brown D. W. 2000. Widespread environmental contamination with Norwalk-like viruses (NLV) detected in a prolonged hotel outbreak of gastroenteritis. Epidemiol. Infect. 125:93–98 [PubMed]
9. Cramer E. H., Gu D. X., Durbin R. E. 2003. Vessel Sanitation Program Environmental Health Inspection Team. Diarrheal disease on cruise ships, 1990–2000: the impact of environmental health programs. Am. J. Prev. Med. 24:227–233 [PubMed]
10. Dorsa W. J., Cutter C. N., Siragusa G. R. 1996. Evaluation of six sampling methods for recovery of bacteria from beef carcass surfaces. Lett. Appl. Microbiol. 22:39–41 [PubMed]
11. Duizer E., Koopmans M. 2006. Tracking emerging pathogens: the case of noroviruses, p. 77–110 In Motarjemi Y., Adams M., editors. (ed.), Emerging foodborne pathogens. Woodhead Publishing Ltd., Cambridge, England
12. Edmonds J. M. 2009. Efficient methods for large-area surface sampling of sites contaminated with pathogenic microorganisms and other hazardous agents: current state, needs, and perspectives. Appl. Microbiol. Biotechnol. 84:811–816 [PubMed]
13. Forslund O., Ly H., Reid C., Higgins G. 2003. A broad spectrum of human papillomavirus types is present in the skin of Australian patients with non-melanoma skin cancers and solar keratosis. Br. J. Dermatol. 149:64–73 [PubMed]
14. Gallimore C. I., et al. 2006. Environmental monitoring for gastroenteric viruses in a pediatric primary immunodeficiency unit. J. Clin. Micriobiol. 44:395–399 [PMC free article] [PubMed]
15. Greig J. D., Todd E. C. D., Bartleson C. A., Michaels B. S. 2007. Outbreaks where food workers have been implicated in the spread of foodborne disease. Part 1. Description of the problem, methods, and agents involved. J. Food Prot. 70:1752–1761 [PubMed]
16. Häfliger D., Gilgen M., Lüthy J., Hübner P. 1997. Seminested RT-PCR systems for small round structured viruses and detection of enteric viruses in seafood. Int. J. Food Microbiol. 37:27–36 [PubMed]
17. Kageyama T., et al. 2004. Coexistence of multiple genotypes, including newly identified genotypes, in outbreaks of gastroenteritis due to norovirus in Japan. J. Clin. Microbiol. 42:2988–2995 [PMC free article] [PubMed]
18. Koopmans M., Duizer E. 2004. Foodborne viruses: an emerging problem. Int. J. Food Microbiol. 90:23–41 [PubMed]
19. Koopmans M. 2009. Noroviruses in healthcare settings: a challenging problem. J. Hosp. Infect. 73:331–337 [PubMed]
20. Kroneman A., et al. 2008. Analysis of integrated virological and epidemiological reports of norovirus outbreaks collected within the Foodborne Viruses in Europe network from 1 July 2001 to 30 June 2006. J. Clin. Microbiol. 46:2959–2965 [PMC free article] [PubMed]
21. Mounts A. W., et al. 2000. Cold weather seasonality of gastroenteritis associated with Norwalk-like viruses. J. Infect. Dis. 181(Suppl. 2):S284–S287 [PubMed]
22. Philips G., Tam C. C., Lopman B. 2010. Prevalence and characteristics of asymptomatic norovirus infection in the community in England. Epidemiol. Infect. 3:1–5 [PubMed]
23. Rockx B., et al. 2002. Natural history of human calicivirus infection: a prospective cohort study. Clin. Infect. Dis. 35:246–253 [PubMed]
24. Siebenga J. J., et al. 2008. High prevalence of prolonged norovirus shedding and illness among hospitalized patients: a model for in vivo molecular evolution. J. Infect. Dis. 198:994–1001 (Erratum, 198:1575.) [PubMed]
25. Thiry E., et al. 2009. H5N1 avian influenza in cats. ABCD guidelines on prevention and management. J. Feline Med. Surg. 11:615–618 [PubMed]
26. Todd E. C. D., Greig J. D., Bartleson C. A., Michaels B. S. 2007. Outbreaks where food workers have been implicated in the spread of foodborne disease. Part 2. Description of outbreaks by size, severity, and settings. J. Food Prot. 70:1975–1993 [PubMed]
27. Todd E. C. D., Greig J. D., Bartleson C. A., Michaels B. S. 2007. Outbreaks where food workers have been implicated in the spread of foodborne disease. Part 3. Factors contributing to outbreaks and description of outbreak categories. J. Food Prot. 70:2199–2217 [PubMed]
28. Vennema H., de Bruin E., Koopmans M. 2002. Rational optimization of generic primers used for Norwalk-like virus detection by reverse transcriptase polymerase chain reaction. J. Clin. Virol. 25:233–235 [PubMed]
29. Verhoef L., et al. 2008. Emergence of new norovirus variants on spring cruise ships and prediction of winter epidemics. Emerg. Infect. Dis. 14:238–243 [PMC free article] [PubMed]
30. Verhoef L., et al. 2010. Use of norovirus genotype profiles to differentiate origins of foodborne outbreaks. Emerg. Infect. Dis. 16:617–624 [PMC free article] [PubMed]
31. Wu H. M., et al. 2005. A norovirus outbreak at a long-term-care facility: the role of environmental surface contamination. Infect. Control Hosp. Epidemiol. 26:802–810 [PubMed]
32. Zhang J., Yu K. F. 1998. What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280:1690–1691 [PubMed]

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