Epidemiology of norovirus infections among diarrhea outpatients in a diarrhea surveillance system in Shanghai, China: a cross-sectional study
Xue et al. BMC Infectious Diseases
Epidemiology of norovirus infections among diarrhea outpatients in a diarrhea surveillance system in Shanghai, China: a cross-sectional study
Ying Xue 0
Hao Pan 0
Jiayu Hu 0
0 Equal contributors Department of Infectious Disease Control and Prevention, Shanghai Municipal Center for Disease Control and Prevention , No. 1380, West Zhongshan Road, Shanghai 200336 , China
Background: Norovirus is an important cause of gastroenteritis both in children and adults. In China, few studies have been conducted on adult populations. This study aimed to determine the contribution of norovirus to gastroenteritis, characterize the features of norovirus infections, compare them with other pathogens, and test the effectiveness of the surveillance system. Methods: A citywide surveillance network on diarrhea patients was established. Samples were collected with intervals from both children and adults among diarrhea outpatients in hospitals and tested for viruses using rRT-PCR and for bacteria in CDCs. Patient information was acquired through interviews and recorded into a dedicated online system. The Pearson2 test, multivariate logistic regression models and discriminant models were fitted into its comparisons with the non-norovirus group and other pathogens. Results: Norovirus was detected in 22.91% of sampled diarrhea patients. The seasonal distribution of norovirus infections was different from non-norovirus patients (p < 0.001), with a half-year peak. Higher proportions of males (p = 0.001, OR = 1.303, 95% CI = 1.110-1.529), local citizens (p < 0.001) and officials/clerks (p = 0.001, OR = 1.348, 95% CI = 1.124-1.618) were affected with norovirus when compared with non-norovirus patients. Diarrhea patients affected with norovirus featured nausea (p < 0.001, OR = 1.418, 95% CI = 1.176-1.709) and vomiting (p < 0.001, OR = 1.969, 95% CI = 1.618-2.398), while fewer manifested fever (p = 0.046, OR = 0.758, 95% CI = 0.577-0.996) and abdominal pain (p = 0.018, OR = 0.815, 95% CI = 0.689-0.965). Children were more vulnerable to rotavirus (p = 0.008, OR = 1.637, 95% CI = 1.136-2.358) and bacteria (p = 0.027, OR = 1.511, 95% CI = 1.053-2.169) than norovirus. There was a seasonal difference between the GI and GII genotypes (p < 0.001). Officials or clerks were more easily affected with GI than GII (p = 0.006, OR = 1.888, 95% CI = 1.205-2.958). Conclusions: This study was based on a citywide hospital-sentinel surveillance system with multiple enteric pathogens included. Norovirus was recognized as the most prevalent enteric pathogen in Shanghai. The seasonal peak was from October to April. Males had a higher prevalence than females. Local citizens and officials/clerks were more vulnerable to norovirus than other pathogens. Compared with rotavirus and bacteria, children were less frequently affected by norovirus. Nausea and vomiting were typical of norovirus, whereas fever and abdominal pain were uncommon symptoms of this pathogen. GI and GII infections were centered in different seasons. Officials and clerks were more easily affected by GI than GII.
Human norovirus; Diarrhea; Surveillance; Epidemiology; Sporadic; All age groups; rRT-PCR
Diarrheal disease morbidity and mortality have been in
decline globally, but around 1.7-5 billion cases of
diarrhea  and nearly 1.7 million diarrheal deaths still
occur each year , the great majority of which are
among young children in developing countries .
Norovirus is a leading cause of non-bacterial
gastroenteritis in both developed and developing countries 
and is increasingly appreciated as an important cause of
gastroenteritis. Norovirus is also considered to be the
second most frequent cause of severe childhood
gastroenteritis after rotavirus . Its prevalence in children
with acute gastroenteritis is in the range of 648% .
The development of molecular techniques in diagnosing
has brought its epidemiological impact into sight . It
was concluded that an average of 570800 deaths,
56,000-71,000 hospitalizations, 1.7-1.9 million
outpatients visits, and 1921 million total illnesses occurin
the United States each year as a result of norovirus
infections . Although previous studies indicated that the
disease was mild and self-limiting, recent studies have
revealed its ability to cause more severe complications
than previously expected [9,10]. In addition to human
losses, the economic costs caused by norovirus
infections were considerable. It is estimated that the
economic burden of norovirus infections approached or
exceeded US$284 million annually in health care charges
in the United States .
The increasing number of global public health
concerns caused by norovirus in recent years has largely
been driven by an abundance of reported outbreaks .
A systematic literature review identified >900 published
reports of laboratory-confirmed norovirus outbreaks
during 1993 ~ 2011 . However, the predominance of
outbreak reports was mainly due to deficient sporadic
data, because norovirus is not routinely tested in clinical
settings due to high molecular method requirements.
Because of this, the characterization of norovirus
epidemiology has been primarily performed through the
analysis of outbreak data .
In China, acute nonbacterial gastroenteritis is also
considered a severe public health problem . However,
very few studies have been focused on adult populations
so as to illustrate the relative importance of norovirus
and other enteric pathogens. In some developed
countries, the typical age pattern of diarrhea mortality is
reversed; diarrhea-associated deaths are 5 times more
common in elderly individuals than in children .
Owing to the overrepresentation of studies merely in
children and a lack of sporadic data on norovirus
infections [9,13,15], the role of norovirus as the etiological
agent in acute diarrhea needs to be further defined. The
objectives of this study were to determine the infection
rate of norovirus among diarrhea patients in Shanghai
and describe the epidemiological characteristics of
norovirus infections in an attempt to test the effectiveness of
the surveillance system and make progress towards its
Shanghai is a metropolis with a population of more than
23 million as of 2010. Of the total population, 62.61%
were locals  and the sex ratio (male: female) of the
city was 1.06:1. The population of the elderly (>60y) was
3.47 million (15.07%) and for the elderly, the sex ratio
(male: female) was 0.92:1. The average life expectancy in
2010 was 82.13 years old . There are 17
administrative districts in Shanghai. All of the hospitals in the
surveillance system have enteric disease clinics for diarrhea
patients for quarantine purposes.
The surveillance first began with 6 adult hospital
sentinels in May 2012, with a child sentinel (specialized city
hospital) joining in October 2012, and 16 additional
adult hospital sentinels in August 2013.
The surveillance system consisted of three levels:
hospital sentinels for case finding, sampling and information
collection; district-level centers for disease control and
prevention (CDCs) for sample testing; and the municipal
CDC for management and quality control. The three
levels could share information through a dedicated
Surveillance subjects were defined as those who visited
the enteric disease clinics of sentinel hospitals, with 3 or
more loose or liquid stools per day [the definition of
diarrhea by the World Health Organization (WHO) .
Norovirus-affected patients were defined as those whose
stool samples were norovirus-positive, including patients
with sole-infections and co-infections.
To date, a total of 23 hospital sentinels were sampled
using Probability Proportionate to Size (PPS) Sampling
across all hospital types and spread over all 17 districts
in Shanghai. The total sample size was calculated on the
basis of the number of diarrhea patients of sampled
hospitals in Shanghai and previous local studies on enteric
pathogens. Systematic sampling was used for sample
collection. Different intervals were allocated to different
sentinel hospitals under a comprehensive calculation of
the hospitals location, classification and annual number
of diarrhea patients.
All surveillance subjects were interviewed by doctors.
General, epidemiological and medical information was
obtained and recorded into the online system. Outbreak
sources were excluded as much as possible via inquiry.
Stool samples were collected from surveillance subjects
in designated intervals by trained medical staff.
Approximately 8 ~ 10 g (mL) of stool was collected and then
dispensed into two containers: a tube with Cary-Blair (C-B)
culture medium for bacteria testing and a sterile box for
virus testing. Nucleic Acid was extracted from fecal
specimens (20% wt/vol or vol/vol suspensions) using the
QIAamp Viral RNA Kit (Qiagen, Hilden, Germany).
Norovirus detection was performed using a real-time
Reverse Transcription -Polymerase Chain Reaction
(rRT-PCR) method. The viral RNA was reverse
transcribed using M-MLV (Promega, Madison, WI) according
to the manufacturers instructions. The primers (Cog1F/
Cog1R) and the probes (Ring1A/Ring1B) were used to
detect norovirus GI, and the primers (Cong2F/Cog2R) and
probe (Ring2) were used to detect norovirus GII .
Probes Ring1A/Ring1B and Ring2 were each labeled with
FAM and HEX at 50 extremities. The final reaction
volume was 20 l, consisting of 1 l RNA and 19 l RT-PCR
master mix. The concentrations of the primers and probes
were as follows: for the GI assay, 0.2 M probe and
0.4 M each primer; for the GII assay, 0.4 M probe and
0.4 M each primer. The thermal cycling conditions: RT
for 30 min at 55C, followed by denaturation at 95C for
30s, amplification for 45 cycles, followed by denaturation
at 95C for 10s, and annealing-extension at 60C for 60s.
A negative control containing diethyl pyrocarbonate
(DEPC) water and two positive controls containing the
RNA of norovirus GI and GII were included in each PCR
run. Samples were scored as positive if cycle threshold
values were less than 40 and positive and negative controls
showed the expected values.
Apart from norovirus detection, all of the samples
were also screened for other viruses (astrovirus,
sapovirus, rotavirus and enteric adenovirus), and for bacteria
[Vibrio cholerae, Shigella, Salmonella, Vibrio
parahemolyticus, Campylobacter jejuni (C. jejuni), Yersinia
enterocolitica, Campylobacter coli (C. coli), Enteropathogenic
escherichia coli (EPEC), Enterotoxigenic escherichia coli
(ETEC), Enterohemorrhagic escherichia coli (EHEC),
Enteroaggregative escherichia coli (EAggEC),
Enteroinvasive escherichia Coli (EIEC)]. Astrovirus, sapovirus
and rotavirus were detected using rRT-PCR and enteric
adenovirus was detected using real-time PCR, all of
which was performed using the appropriate respective
commercial kits (Shanghai Zhijiang Biotechonology Co.,
Ltd.) according to the instructions provided by the
manufacturer. Bacteria were isolated using different
mediums at proper temperatures after preparation. The
mediums included ChromID Vibrio and TCBS for Vibrio
cholera and Vibrio parahemolyticus, MAC for
Escherichia coli, XLD for Shigella and Salmonella, etc.. Bacteria
were identified using biochemical tests. An automatic
biochemical identification system was used for
Escherichia coli. Serum agglutination tests were employed to
subtype Shigella, Salmonella, Vibrio cholera and
Samples were taken as a part of standard medical care.
All laboratory results were recorded and viewed using
the online system.
The study protocol was reviewed and approved by the
Human Research Ethics Committee of the Shanghai
Municipal Center for Disease Control and Prevention.
Data analyzed in the study were from May 1, 2012 to
April 30, 2014 (date of visit) and downloaded on May
26, 2014. The division of age groups conforms to the
Convention on the Rights of the Child and WHO
standards. The definition of seasons was determined by
the climatic characteristics of Shanghai. Differences
in discrete variable levels were examined using the
Pearson2 test. Fishers test was used when the expected
value was less than 5 or when the p value was close to
the level of the test. A multivariate logistic regression
model was used to seek characteristic differences as
integrated in a clinical setting (NoV+ vs NoV-; NoV+ vs
RV+; NoV+ vs bacteria+; genotype GI vs GII).
Discriminant analysis was used to identify the symptom complex
of norovirus infections. Two-tailed P < 0.05 was
considered statistically significant. Version 17.0 of the SPSS
software package was used for all analyses (SPSS, Inc.,
During the 2-year study period, a total of 44595 diarrhea
patients were studied. The mean (SD) age of the study
subjects was 43.51 (19.06 ) years and 21657 (48.56%)
were male. Among the surveillance subjects, a total of
3941 samples (8.84%) were detected (duplicated samples
excluded). There were 2114 positive samples detected
(positive rate 53.64%) and 903 (detection rate 22.91%)
patients were positive for norovirus (referred to as
NoV + ), consisting of GI (94, 10.41%), GII (769, 85.16%)
and co-infections of GI and GII (40, 4.43%). Co-infections
of norovirus and other viruses or bacteria were confirmed
in 91 cases (2.31%). Excluding co-infection samples, 2947
samples (74.78%) were confirmed as negative for all tested
pathogens or positive for other enteric pathogens (referred
to as NoV -). The positive rates of other enteric
pathogens were as follows (excluding co-infections): Shigella
0.51%, Salmonella 3.63%, Vibrio parahemolyticus 3.93%,
C. jejuni 0.66%, Yersinia enterocolitica 0.05%, C. coli 0.08%,
EPEC 0.74%, ETEC 0.86%, EAggEC 0.10%, EIEC 0.03%,
astrovirus 2.54%, rotavirus 10.05%, sapovirus 2.36%, and
enteric adenovirus 0.53%.
NoV(+) sample features and comparison with NoV()
Norovirus was detected throughout the year, and the
prevailing season lasted as long as half a year (from
October to April) (See Figure 1). The seasonal
distribution of NoV(+) detection was different from NoV()
(p < 0.001), but no difference was found between
autumn (September-November) and winter
(DecemberFebruary) (p = 0.117). Norovirus spanned all ages, from
0 to 94 years old. The proportion of the child
population of NoV(+) patients seemed smaller than that of
NoV() ones (See Figure 2), but the difference was
not statistically significant in a logistic regression
model. The sex ratio (male: female) was 1.18:1, with a
higher male proportion in the NoV(+) group (p = 0.001,
OR = 1.303, 95% CI = 1.110-1.529). The proportion of local
citizens infected with norovirus was higher than that of
non-norovirus patients (p < 0.001). Norovirus had a
higher chance of appearing in: officials/clerks (p = 0.001,
OR = 1.348, 95% CI = 1.124-1.618) and a lower chance
of appearing in farmers/migrant laborers (p = 0.007,
OR = 0.243, 95% CI = 0.087-0.680).
In an age stratification analysis, it was discovered that
NoV(+) and NoV() patients had statistically
different seasonal distributions for each age group (0 ~ 4y,
p = 0.017; 5 ~ 18y, p = 0.005; 19 ~ 44y, 45 ~ 59y, >60y,
all p < 0.001) (See Figure 3), and a significant
seasonal difference among NoV(+) patients of different
age groups could also be determined (p 0.027).
While a difference in the proportions of male and
female NoV(+) patients could be found among
different age groups (p = 0.016): in the children and youth
groups (<44y), males were dominant, and in the
middleaged and elderly groups (>45y), vice versa (p < 0.001,
OR = 1.586, 95% CI = 1.216-2.067), the gender
distribution did not differ much from NoV() patients,
except in the youth (19-44y) group, where male
patients had a higher proportion of infections (p = 0.024,
OR = 1.302, 95% CI = 1.041-1.629).
Analysis of exposure history
When compared with NoV(), a higher proportion of
NoV(+) patients had a history of consuming suspicious
food within 5 days before onset (p = 0.001, OR = 1.319,
95% CI = 1.124-1.550), while a lower proportion had
an enteric disease history 6 months prior (p = 0.048,
OR = 0.341, 95% CI = 0.117-0.992).Although a large
percentage (53.09%) of the children (<18y) group
kept or had contact with pets, in a univariate 2 test,
there was no statistically significant difference
between NoV(+) and NoV() patients (p = 0.451) within
5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4
Figure 1 Monthly infection percentage of NoV(+), NoV(), RV(+) and bacteria. The percentage of the infections detected in this particular month
out of the whole study period was calculated.
Figure 2 Age distribution of NoV(+), NoV(), RV(+) and bacteria patients. From May 2012 to September 2012, only 6 sentinels were under
surveillance. A child sentinel joined in October 2012. In August 2013, the number of sentinels expanded to 23.
Clinical feature analysis
NoV(+) diarrhea patients featured nausea (p < 0.001,
OR = 1.418, 95% CI = 1.176-1.709) and vomiting (p < 0.001,
OR = 1.969, 95% CI = 1.618-2.398), while fewer reported
fever (p = 0.046, OR = 0.758, 95% CI = 0.577-0.996) and
abdominal pain (p = 0.018, OR = 0.815, 95% CI = 0.689-0.965)
when compared with NoV() patients. In a discriminant
analysis, the relationship between symptoms and norovirus
infections was also studied. The combination of nausea
and vomiting (especially lasting over three days) was typical
of norovirus infections, while fever (especially high fever)
and abdominal pain were adverse determining factors
(p < 0.001). General, epidemiological and clinical
comparisons are listed (see Additional file 1).
Comparisons with rotavirus and bacterial infections
A total of 396 samples were confirmed to have rotavirus
infections (10.05%), and 432 samples had bacterial
infections (10.96%) (co-infections excluded). Comparisons
with norovirus regarding their general, epidemiological
and clinical features with norovirus are listed (see
Additional files 2 and 3).
The seasonal difference between norovirus and
rotavirus detection was obvious (p < 0.001): rotavirus mainly
occurred in the coldest seasons (from November to
February) (See Figure 1). There was also a difference in
age distribution between the two viruses (p = 0.002):
rotavirus affected children more (p = 0.008, OR = 1.637,
95% CI = 1.136-2.358) (See Figure 2). The proportion of
males (p = 0.004, OR = 1.475, 95% CI = 1.133-1.919) and
local citizens (p < 0.001) with confirmed norovirus was
higher than those with rotavirus. Norovirus and
rotavirus were detected from hospitals of different types
(p = 0.006). Rotavirus-affected patients had a higher
proportion of suspicious food history (p < 0.001, OR = 2.006,
95% = 1.447-2.781). Patients affected with norovirus were
more likely to manifest vomiting (p < 0.001, OR = 1.860,
95% CI = 1.373-2.520), but less likely to manifest fever
(p = 0.034, OR = 0.626, 95% CI = 0.406-0.964).
The seasonal difference between norovirus and
bacteria was more obvious (p < 0.001): bacteria were mostly
found in warm seasons (from July to September) (See
Figure 1). Age was also an influencing factor p = 0.037):
a higher proportion of children were infected with
bacteria than norovirus (p = 0.027, OR = 1.511, 95%
CI = 1.053-2.169) (See Figure 2). Local citizens had a
higher proportion of norovirus infections (p = 0.003).
For the following occupations, there was a lower
prevalence of norovirus than of bacteria:
kindergarten/home-stay children (p = 0.033, OR = 0.090, 95%
CI = 0.010-0.822) and farmers/migrant laborers (p = 0.008,
OR = 0.180, 95% CI = 0.051-0.643). Norovirus-affected
patients had a higher proportion of suspicious food history
(p < 0.001, OR = 1.686, 95% CI = 1.266-2.244). Compared
with bacteria, norovirus patients less frequently manifested
fever (p < 0.001, OR = 0.428, 95% CI = 0.288-0.635) and
abdominal pain (p < 0.001, OR = 0.405, 95% CI =
0.2990.549), but more frequently manifested nausea (p = 0.001,
OR = 1.735, 95% CI = 1.247-2.412) and vomiting (p = 0.006,
OR = 1.620, 95% CI = 1.149-2.286).
Features of GI and GII genotypes
769 GII strains were detected concomitant with 94 GI
ones. The Pearson2 test indicated that the seasonal
distribution of two genotypes was different (p < 0.001), with
GI highest in spring (March to May) (44.68%) and GII
highest in autumn (September to November) (40.44%).
Those who work as officials or clerks had a higher
possibility of being affected by GI (42.55%) than GII (25.75%)
(p = 0.001, OR = 2.136, 95% CI = 1.368-3.289). GI-affected
patients seemed to have eaten in a restaurant more often
(3.19%) than GII-affected patients (0.65%) (p = 0.047,
OR = 5.037, 95% CI = 1.185-21.277). The rate of
patients who had consumed contaminated seafood within
five days before onset was higher in GI (17.02%) than
in GII (10.92%) patients (p = 0.019, OR = 2.294, 95%
CI = 1.164-4.525). There were also slight differences
in the clinical features of the two genotypes: nausea
(54.26% of GI and 42.65% of GII, p = 0.037, OR = 1.595,
95% CI = 1.031-2.439), diarrhea lasting less than three days
(87.23% of GI and 81.14% of GII, p = 0.035, OR = 4.008,
95% CI = 0.959-16.667), and hyperactive bowel sounds
(37.23% of GI and 23.28% of GII, p = 0.003, OR = 1.955,
95% CI = 1.250-3.077).
In a logistic regression model, officials or clerks
were more easily affected with GI than GII (p = 0.006,
OR = 1.888, 95% CI = 1.205-2.958). Seasonal differences
were statistically significant in both genotypes (p < 0.001).
A higher proportion of patients who had eaten in a
restaurant was affected with GI than GII (p = 0.048,
OR = 4.717, 95% CI = 1.013-21.960).
91 norovirus co-infection samples were discovered
(excluding co-infections of norovirus GI and GII): 21
with rotavirus, 18 with astrovirus, 15 with sapovirus, 10
with Salmonella, 7 with EPEC, 5 with Vibrio
parahemolyticus, 5 with adenovirus, 3 with C. jejuni,2 with C. coli,
1 with Shigella, 1 with EAggEC and 3 triple co-infections.
Acute gastroenteritis is one of the most common
diseases reported in humans. Norovirus is not only the
leading cause of non-bacterial gastroenteritis outbreaks,
but it is also currently recognized as a major cause of
sporadic gastroenteritis in both children and adults .
In China, acute nonbacterial gastroenteritis is also
considered to be a severe public health problem. However,
most studies have mainly focused on norovirus
infections of children, while little research has been
conducted in adult populations to clarify the importance of
norovirus . In addition, materials and analyses with
regards to norovirus have mostly been obtained from
outbreak resources .
This study was the first in Shanghai to be concerned
with sporadic norovirus infections of the whole
population. It was based on a diarrhea disease surveillance
system in Shanghai, which began in 2012. Compared with
other studies[9,15], this study distributed sentinels across
the city and used systematic sampling, which are better
able to better represent and be extrapolated to the citys
population by avoiding the influence of clusters and
season-specific cases; the incidence rate and disease
burdens could be calculated in future studies. The positive
rate of norovirus was 22.91% among 3941 diarrhea
patients, which was quite close to the result of a previous
study in Beijing (26.4% among acute non-bacterial
gastroenteritis patients)  and another in Shenzhen
(21.4% in acute gastroenteritis patients) . In this
study, the norovirus infection rate was the highest
among all pathogenswhen co-infections were excluded.
Previous studies have reported that norovirus mainly
peaked in winter or cold seasons [21,22]. In this study,
the result verified this conclusion, as more strains were
detected from October to April (when the weather was
comparatively cold in Shanghai). Interestingly, an
autumn peak was as distinct as the winter one, which was
in concert with another study in Beijing  (despite the
fact that autumn in Beijing is colder than Shanghai).
This could perhaps be explained by the immunity barrier
to the current epidemic strain set up by the population
during the epidemic season in autumn. The relationship
of norovirus infections and temperature should be
further explored in the future studies. For different age
groups, the seasons when people were vulnerable to
norovirus seemed different in a univariate2 test, but not
enough samples could be included in a logistic
regression model. More studies could be made if enough data
Other than previous studies, which concluded that
young children and elderly people were more vulnerable
than other age groups [10,24], our study discovered that
the highest detection rate was found in the youth group
(19-44y) (25.97%), and the lowest in the children group
(13.30%), with the elderly group in the middle (23.50%),
whereas in a logistic model, the age distribution of
NoV(+) patients could not be proved to be different
from NoV() patients. Age distribution differences were
found to be significant in NoV(+) vs RV(+) and NoV(+) vs
bacteria(+) comparisons, which are stated below.
Males were found to more often be affected by
norovirus when compared with other enteric pathogens.
Although 0 ~ 44y males accounted for a higher proportion
in the NoV(+) group and >45y a lower proportion in an
age stratification analysis, the distribution seemed to be
a general characteristic of all diarrhea patients.
It was observed that local citizens and officials/clerks
had a higher proportion of norovirus infections, while
immigrants and farmers/migrant laborers a lower
proportion. There originally existed associations between
the residency and occupation results, and yet it still
seemed that norovirus was a more urban virus.
A history of consuming suspicious food within 5 days
before onset was more commonly recorded among
norovirus affected patients than non-norovirus ones.
Nevertheless, the fact that a large part of non-norovirus
diarrhea patients might have had physiological diarrhea
or non-communicable enteric diseases might influence
the outcome. It was also found that rotavirus-affected
patients had a higher proportion of suspicious food
history than norovirus patients, while bacteria had a lower
proportion. Unfortunately, though specific food category
information was gathered, the valid sample size was not
large enough to be included in a logistic regression
model. Further research regarding specific food risk
factors could be made in future studies.
Some studies recognized diarrhea, vomiting and fever
as the most common symptoms of norovirus-affected
patients [13,24-26]. Although in this study it was proved
that norovirus was distinguished by diarrhea
(automatically included), nausea, and vomiting among diarrhea
patients, fever was less commonly seen in NoV(+) patients
when compared with NoV() ones. Other studies also
claimed a lower occurrence of fever in norovirus
patients than in rotavirus ones [21,22,27], but their rate
was still much higher than what was reported in this
study (only 8.86% norovirus-affected patients
experienced fever). This was probably because febrile patients
tend to visit fever clinics in Chinese hospital settings.
Abdominal pain was also identified as a rare symptom of
norovirus, which was similar to the result of a previous
study . The clinical feature results produced in a
logistic model were analogous to those in a discriminant
Comparisons between NoV(+) vs RV(+) and NoV(+) vs
bacteria(+) were also made in this study to help enhance
the cognition of the disease and provide evidence for a
rough diagnosis. The results were broadly in line with the
NoV(+) vs NoV() comparison, but some new conclusions
were also drawn: rotavirus occurred in an even colder
climate, and bacteria mainly appeared in hot seasons. Age
distribution differences were significant here: children were
more vulnerable to rotavirus and bacteria than norovirus.
Although the difference in the proportion of patients
showing abdominal distention in norovirus and bacterial
infections was not significant (p = 0.053), observations
should be continued when more data is obtained.
Norovirus GII is predominantly responsible for acute
diarrhea worldwide, as described in most studies [10,24],
and our findings (10.41% GI, 85.16% GII, 4.43% mix of
both genotypes) were consistent with them. Our
research also did further studies on the comparison of
features between two genotypes: GI prevailed in spring
while GII in autumn. This could be caused by variant
alternation with seasonal changes. It was found in a
univariate analysis that a higher proportion of GI-affected
patients had the symptoms of nausea, diarrhea lasing for
less than three days and hyperactive bowel sounds,
whereas the results were not supported by the
multivariate model. The influence of consuming seafood within
five days before onset was also not backed up by the
multivariate model. On the other hand, the multivariate
model supported the univariate conclusions that the
occupations of officials/clerks were a risk factor for
infection with GI variants other than GII, though the
power of the logistic model might be slightly compromised
because of the small sample size of GI cases. Having eaten
in a restaurant could not be regarded as a risk factor here
as the confidence interval was too wide. In order for results
to be revealed by either univariate or multivariate models,
there needs to be more data for tests in the future.
The limitations of this study should be considered.
First, data were gathered through 23 hospitals and 17
laboratories. Though testing methods and materials were
unified, there was still a chance of bias caused by the
different levels and conditions of laboratories (as suggested
above). Admission rate bias should also be taken into
account as patients visiting hospitals of different levels or
in different regions were quite different. Furthermore,
variations in the sentinel numbers would certainly affect
the observation of seasoning, though it could be
alleviated by making a comparison with non-norovirus
patients. Second, only one child sentinel was enrolled and
the data regarding children were quite limited. The
testing power of age distribution might therefore be
undermined. Next year we will enlarge the range of
surveillance in children and include more data. Third, RNA
sequencing of the positive samples was not done in this
study. Since different features could possibly be found
between GI and GII genotypes, this issue is deserving of
further research with regard to particular strains and
variants. Fourth, the recall bias of epidemiological
information was difficult to avoid. The information on
exposure history was primitive in this study. For example,
water contamination was an important cause of
norovirus outbreaks [27-31], and in another study, drinking
spring water was reported as a risk factor . However,
in this study, only 7 out of 3941 diarrhea patients
reported drinking contaminated water and none of them
were affected with norovirus. Meanwhile, very few data
from general laboratory examination results were
recorded. Perhaps if more meaningful variables of this sort
of information were studied in the model, the power of
the test would be greater. Fifth, because of the small
sample size and short surveillance time, we did not
perform further research among sole-infections and
coinfections and other stratification analyses.
This was the first study on norovirus among all age
groups in Shanghai. In this study, several meaningful
conclusions were acquired: Norovirus was the most
frequent enteric pathogen in Shanghai during the
past two years; the epidemic season of norovirus was
October ~ April in Shanghai; the norovirus infection
proportion in children (<18y) was found to be lower
than rotavirus and bacteria; Males had a higher
proportion of norovirus infections than females; higher
proportions of local citizens and officials/clerks were infected
with norovirus than other pathogens; Norovirus could be
characterized by nausea and vomiting among diarrhea
patients, but fever and abdominal pain were rare
symptoms; the GI genotype prevailed in spring while GII in
autumn; It was easier for officials/clerks to be affected
with GI than GII. These results might serve to promote
diagnosis in a clinical setting, especially for medical staff
to detect outbreaks and trace sources early. For public
health workers, the results could help determine focus
timing and populations of norovirus infections.
The study was based on a diarrhea surveillance system
combining case finding in hospitals and laboratory
testing in CDCs into one platform via a dedicated online
system. The results of the norovirus survey proved that
the surveillance system was running well. Other credible
and constructive results on general, epidemiological and
clinical features were generated. In the future, more
improvements on epidemiological data, medical recording
and RNA sequencing should be made based on the
system. Nevertheless, the system still has reference value
for other regions.
Additional file 1: Table S1. Epidemiology and clinical features by
examining NoV(+) and NoV() patients.
Additional file 2: Table S2. Epidemiology and clinical features by
examining NoV(+) and RV(+) patients.
Additional file 3: Table S3. Epidemiology and clinical features by
examining NoV(+) and bacteria(+) patients.
rRT-PCR: Real-time Reverse Transcription -Polymerase Chain Reaction;
CDC: Center for Disease Control and Prevention; OR: Odds Ratio; CI: Confidence
Interval; WHO: World Health Organization; PPS: Probability Proportionate to Size;
C-B: Cary-Blair; DEPC: Diethyl pyrocarbonate; C. jejuni: Campylobacter
jejuni; C. coli: Campylobacter coli; EPEC: Enteropathogenic escherichia
coli; ETEC: Enterotoxigenic escherichia coli; EHEC: Enterohemorrhagic
escherichia coli; EAggEC: Enteroaggregative escherichia coli; EIEC: Enteroinvasive
escherichia coli; NoV+: NoV(+): norovirus positive; NoV-: NoV(), Norovirus
negative; RV+: RV(+), Rotavirus positive.
YX performed the statistical analysis and drafted the manuscript. HP, JH, and
HW placed the surveillance system into effect. JL designed the study of the
surveillance system. WX participated in the management of the system. XZ
carried out the quality control of the laboratory tests. ZY and FW conceived
of the study. All authors read and approved of the final manuscript.
This study was supported by the grant Key Discipline: Epidemiology
(No. 12GWZX0101) and the Shanghai Public Health Professional Overseas
Training Grant (No. GWHW2012105), from the Shanghai Municipal Commission
of Health & Family Planning. The authors of this study thank all of the public
health workers in the CDCs and health-care workers in the hospitals involved in
the surveillance system for keeping the system running and for their acquisition
of data. We thank Hong Ren and Yiyi Zhu for their kind and useful advice during
the drafting of the manuscript. We are also grateful to Yi He for his intellectual
contributions to the studys design.
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