Open Access

Case–control study of diarrheal disease etiology in individuals over 5 years in southwest China

  • Shun-Xian Zhang1, 2,
  • Chun-Li Yang1, 2,
  • Wen-Peng Gu3,
  • Lin Ai1, 2,
  • Emmanuel Serrano4, 5,
  • Pin Yang1, 2,
  • Xia Zhou6,
  • Shi-Zhu Li1, 2,
  • Shan Lv1, 2,
  • Zhi-Sheng Dang1, 2,
  • Jun-Hu Chen1, 2,
  • Wei Hu1, 2,
  • Li-Guang Tian1, 2,
  • Jia-Xu Chen1, 2Email author and
  • Xiao-Nong Zhou1, 2Email author
Contributed equally
Gut Pathogens20168:58

https://doi.org/10.1186/s13099-016-0141-1

Received: 19 July 2016

Accepted: 5 November 2016

Published: 16 November 2016

Abstract

Background

Acute diarrhea is one of the major public health problems worldwide. Most of studies on acute diarrhea have been made on infants aged below 5 years and few efforts have been made to identify the etiological agents of acute diarrhea in people over five, especially in China.

Methods

271 diarrhea cases and 149 healthy controls over 5 years were recruited from four participating hospitals between June 2014 and July 2015. Each stool specimen was collected to detect a series of enteric pathogens, involving five viruses (Rotavirus group A, RVA; Norovirus, NoV; Sapovirus, SaV; Astrovirus, As; and Adenovirus, Ad), seven bacteria (diarrheagenic Escherichia coli, DEC; non-typhoidal Salmonella, NTS; Shigella spp.; Vibrio cholera; Vibrio parahaemolyticus; Aeromonas spp.; and Plesiomonas spp.) and three protozoa (Cryptosporidium spp., Giardia lamblia, G. lamblia, and Blastocystis hominis, B. hominis). Standard microbiological and molecular methods were applied to detect these pathogens. Data was analyzed using Chi square, Fisher-exact tests and logistic regressions.

Results

The prevalence of at least one enteric pathogen was detected in 29.2% (79/271) acute diarrhea cases and in 12.1% (18/149) in healthy controls (p < 0.0001). Enteric viral infections (14.4%) were the most common in patients suffering from acute diarrhea, followed by bacteria (13.7%) and intestinal protozoa (4.8%). DEC (12.5%) was the most common causative agent in diarrhea cases, followed by NoV GII (10.0%), RVA (7.4%) and B. hominis (4.8%). The prevalence of co-infection was statistically higher (p = 0.0059) in the case group (7.7%) than in the healthy control (1.3%). RVA–NoV GII (3.0%) was the most common co-infection in symptomatic cases.

Conclusions

DEC was the most predominant pathogen in diarrhea cases, but it was largely overlooked because the lack of laboratory capacities. Because of the high prevalence of co-infections, it is recommended the urgent development of alternative laboratory methods to assess polymicrobial infections. Such methodological improvements will result in a better prevention and treatment strategies to control diarrhea illness in China.

Keywords

Acute diarrhea Bacteria Virus Enteric protozoa Co-infection

Background

Diarrheal illness is still a serious public health problem that particularly affects individuals in middle and low income countries [1]. Diarrhea is still a major reason of attendance at health services and one of the general causes for hospital admission [2]. In addition, 1,400,000 million deaths are caused by diarrhea across all age groups, of which 700,000 deaths are over 5 years [1, 2].

The main enteric pathogens include a wide range of bacteria (e.g. diarrheagenic Escherichia coli, DEC; non-typhoidal Salmonella, NTS; Shigella spp.; Vibrio cholera; Vibrio parahaemolyticus; Aeromonas spp.; Plesiomonas spp.; Campylobacter spp.), virus (e.g. rotavirus group A, RVA; norovirus, NoV; Sapovirus, SaV; astrovirus, As; adenovirus, Ad; enterovirus.) and enteric parasites (e.g. Cryptosporidium spp.; Giardia lamblia, G. lamblia; Entamoeba histolytica and Blastocystis hominis, B. hominis) [38].

Most researches of enteric pathogens on individuals with and without diarrhea have been largely based on a single or few pathogen species [911]. However, co-infection is a common prevalence in diarrhea cases in such communities with poor food hygiene, low sanitation and contaminated water (35.0, 20.1, 13.0%, respectively) [6, 12, 13]. Co-infection, however, are also common in healthy patients (8.0, 5.3, 0.8%, respectively) [6, 12, 13]. Co-infection is of particular human health importance because pathogen species can interact within the host. Interactions within the host can have either positive or negative effects on each of the co-infecting enteric pathogen species. Under positive enteric pathogen interactions, diarrheal disease transmission and progression are enhanced [6, 12, 14, 15].

Infectious diarrhea is still one of the important public health problems in China. The reported infectious diarrhea is up to 70,000,000, and the reported incidence of infectious diarrhea is 55.9/10,000,000 annually in China listed by China Information System for Diseases Control and Prevention. Diarrheal illness incidence is located in top three of 39 notifiable infectious diseases [11, 16]. However, in many medical institutions, the lack of clinical microbiology laboratories and detection capabilities hamper the detection of etiological agents of gastroenteritis. As result, etiology of gastroenteritis in China is achieved in less than 5.0% of patients [11]. In addition, most of the diarrhea studies have been limited to children under 5 years and either bacterial or viral species [11, 17, 18]. Hence, the aim of the study was twofold: one was to investigate the etiology of diarrhea cases in people over 5 years and to assess patterns of co-infection among virus, bacteria and protozoa in patients from southwest China. This study will contribute to the effective control of acute diarrhea in the country.

Methods

Subjects of this study

Acute gastroenteritis patients were defined as those who had diarrhea over three times within 24 h with abnormal stool specimens (e.g. mucus stool, watery stool, loose stool or bloody stool) in accordance with the WHO standard [19]. Non-diarrheal subjects were defined as those who had no history of diarrhea symptom before 14 days and were recruited at the same time as diarrheal subjects.

Specimen and data collection

The stool specimens were collected from acute diarrhea cases and healthy controls over 5 years in outpatient from four sentinel hospitals as follows: The First people’s Hospital of Yunnan Province, Kunming Children’s Hospital, The Pushan Community Health Service Center in Kunming, The First People’s Hospital of Yunnan Province, and The First Affiliated Hospital of Kunming Medical University. A sterile sampling cup was applied to collect stool sample, with the criterion that each stool must be greater than 3 g or 3 mL, then each stool specimen was delivered to the laboratory of Yunnan Provincial Center for Disease Control and Prevention in Cary-Blair (C-B) culture medium (Oxoid Ltd, Basingstoke, UK) within 12 h. The clinical (e.g. fever, abdominal pain, nausea, vomiting, dehydration and tenesmus) and basic epidemiological data (e.g. sex, age, residence and season) was collected with structured questionnaire by doctors or nurses. The present study was conducted from July 2014 to June 2015.

Laboratory test for enteric pathogens

Each stool sample was divided into three aliquots (Additional file 1). The first one was used for isolating, culturing and identifying bacterial (DEC, NTS, Shigella spp., Vibrio cholera, Vibrio parahaemolyticus, Aeromonas spp. and Plesiomonas spp.), the second one detect viral pathogens (RVA; NoV; astrovirus As, and Adenovirus, Ad), and last to assess intestinal protozoa infection (Cryptosporidium spp., G. lamblia and B. hominis).

Bacterial detection

MacConkey agar (MAC, Oxoid Ltd, Basingstoke, UK) was used for culturing DEC, which was divided into five subtypes by their virulence genetic as following: enteroaggregative E. coli (EAEC), enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), enteroinvasive E. coli (EIEC) and enterohaemorrhagic E. coli (EHEC). The DEC subtypes were examined with quantitative PCR based on the previous literatures (Table 1) [20, 21]. Each stool sample was inoculated into the selenite brilliant green sulfa enrichment broth (Oxoid Ltd, Basingstoke, UK) for enrichment and then inoculated it onto Salmonella–Shigella agar (Oxoid Ltd, Basingstoke, UK) to detect NTS. In addition, each stool specimen was inoculated directly onto Salmonella–Shigella agar (Oxoid Ltd, Basingstoke, UK) to find Shigella spp. Moreover, each sample was inoculated onto alkaline peptone water (Oxoid Ltd, Basingstoke, UK) for enrichment, and then inoculated onto thiosulfate-citrate-bile salts-sucrose agar (Oxoid Ltd, Basingstoke, UK) to detect Vibrio cholera, Vibrio parahaemolyticus, Aeromonas spp. and Plesiomonas spp. For suspicious NTS, Shigella spp., Vibrio cholera, Vibrio parahaemolyticus, Aeromonas spp., and Plesiomonas spp. colonies. The systematic biochemical identification of was performed using the VITEK® 2 Compact instrument (bioMerieux, Marcyl’Etoile, France). Detailed detection procedures are found in references [11, 17].
Table 1

The primers and reactions condition applied to detect enteric pathogens in this study

Enteric pathogens

Target gene

Primer (5′–3′)

Amplicon sizes (bp)

Remarks

Source

EPEC

eae

CCACGGTTTATCAAACTGATAACG

105

Each stool specimen was inoculated to MAC media to culture DEC at 37 °C for 18 h, And then ten putative DEC colonies were selected to mix with 150 μL water to extract DNA at 100 °C for 10 min, and then the 20 μL volume of qPCR system is composed of 10 μL master mix (Takara Bio Inc, Shiga, Japan), 1 μL forward primer (10 μmol), 1 μL reverse primer (10 μmol), 1 μL DNA template and 7 μL H2O. The cycling conditions for each subtype DEC was 95 °C for 5 min, 40 cycles of 95 °C for 5 s, 60 °C for 30 s. The fluorescence recorded was at the annealing stage

[20, 21]

EHEC

stx1

ACTTCTCGACTGCAAAGACGTATG

132

ACAAATTATCCCCTGAGCCACTATC

stx2

CCACATCGGTGTCTGTTATTAACC

93

GGTCAAAACGCGCCTGATAG

ETEC

elt

TTCCCACCGGATCACCAA

62

CAACCTTGTGGTGCATGATGA

estA

CCTTTCGCTCAGGATGCTAAAC

128

CAGTAATTGCTACTATTCATGCTTTCAG

estB

CTTTCCCCTCTTTTAGTCAGTCAACT

137

GCAGTAAAATGTGTTGTTCATATTTTCTG

EAEC

aggR

CAGCGATACATTAAGACGCCTAAAG

116

CGTCAGCATCAGCTACAATTATTCC

EIEC

ipaH

ACCATGCTCGCAGAGAAACT

175

TCAGTACAGCATGCCATGGT

RVA

VP6

GACGGVGCRACTACATGGT

382

RVA, NoV GI, NoV GII, SaV and As were RNA viruses, complementary DNA (cDNA) was synthesized using a random primer (Takara Bio Inc, Shiga, Japan) at 55 °C for 1.5 h, followed by 100 °C for 10 min, and holding at 4 °C. The reaction condition of RVA was 94 °C for 5 min, followed by 40 cycles at 94 °C for 1 min, 42 °C for 1 min, 72 °C for 1 min, and with final extension at 72 °C for 10 min. Multiplex RT-PCR was used to detect the presence of NoV GI, NoV GII, and SaV, the thermal profile consisted of 94 °C for 5 min, 40 cycles of 94 °C for 70 s, 49 °C for 70 s, and 72 °C for 1 min, followed by 72 °C for 10 min. The thermal profile of As was 94 °C for 5 min, 40 cycles of 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 1 min, followed by 72 °C for 10 min

[22]

GTCCAATTCATNCCTGGTGG

NoV GI

NoV GII

SaV

Polymerase

TGACGATTTCATCATCACCATA

331/319

[23]

TGACGATTTCATCATCCCCGTA

GATTACTCCAGGTGGGACTCCAC

GATTACTCCAGGTGGGACTCAAC

GATTACTCCAGGTGGGATTCAAC

GATTACTCCAGGTGGGATTCCAC

As

Capsid

CAACTCAGGAAACAGGGTGT

449

[24]

TCAGATGCATTGTCATTGGT

Ad

Hexon

TTCCCCATGGCICAYAACAC

482

The thermal profile was 94 °C for 5 min, 40 cycles of 94 °C for 30 s, 55 °C for 30 s, and 72 °C for 1 min, followed by 72 °C for 10 min

[25]

CCCTGGTAKCCRATRTTGTA

Blastocistis hominis

SSU-rRNA

CGAATGGCTCATTATATCAGTT

260

The thermal profile was 94 °C for 5 min, 40 cycles of 94 °C for 30 s, 53 °C for 30 s, and 72 °C for 1 min, followed by 72 °C for 10 min

[26]

TCTTCGTTACCCGTTACTGC

Cryptosporidium spp.

18S-rRNA

TTCTAGAGCTAATACATGCG

 

The primary cycle consisted of 94 °C for 5 min, 35 cycles of 94 °C for 50 s, 55 °C for 1 min and 72 °C for 90 s, followed by 72 °C for 10 min, the annealing step for a second reaction was 58 °C

[27]

CCCATTTCCTTCGAAACAGGA

 

GGAAGGGTTGTATTTATTAGATAAAG

840

CTCATAAGGTGCTGAAGGAGTA

Giardia lamblia

Tim

AAATIATGCCTGCTCGTCG

 

The thermal profile of first round was 94 °C for 1 min, 53 °C for 1 min, and 72 °C for 1 min, followed by 72 °C for 10 min. A second reaction was carried out similarly

[28]

CAAACCTTITCCGCAAACC

 

CCCTTCATCGGIGGTAACTT

530

GTGGCCACCACICCCGTGCC

DEC is composed of EAEC, EPEC, EIEC, ETEC and EHEC in this study, the judging standard of subtypes of DEC according to qPCR was: EPEC: eae+; EAEC: aggR+; EIEC: ipaH+; EHEC: eae+, and (stx1+; and/or stx2+); ETEC: hlt+, and/or estA, and/or estB+

Virus detection

Nucleic Acid was extracted from each stool specimen (15% wt/vol or vol/vol suspension) with QIAamp Viral RNA Kit (Qiagen, Hilden, Germany). The reverse transcription-polymerase chain reaction (RT-PCR) was applied to detected RVA [22], NoV (GI, GII) [23] and As [24]. For RT, the viral RNA was reverse transcribed with PrimeScript™ RT reagent Kit (Takara Bio Inc, Shiga, Japan). Ad was found using PCR [25] (Table 1).

Enteric protozoan detection

The genomic DNA of Cryptosporidium spp., G. lamblia and B. hominis was extracted from each stool sample with QIAamp DNA stool mini kit (Qiagen, Hilden, Germany) according to the manufacturers’ protocol. The conventional PCR was applied to detect B. hominis [26], the nested PCR was used to detect Cryptosporidium spp. [27] and G. lamblia [28] (Table 1).

Data analysis

Data analysis was performed by IBM SPSS software (version 19.0 for Windows, Armonk, NY). Odds ratio (OR) and 95% CIs of categorical variables were calculated using two tailed Chi square or Fisher’s exact tests. Quantitative variable was described as mean, median, standard deviation or interquartile range (IQR), among which the median or mean of quantitative variable was compared by rank-sum test, analysis of variance or t test. Logistic regression was performed to find the relationship between diarrhea illness and various enteric pathogens. Single etiology was selected according to bivariate analysis with p < 0.20. Significant difference was taken as the level of p < 0.05 with two-tailed test.

Results

Basic information and clinical symptoms

From July 2014 to June 2015, 420 subjects were recruited for this study, which including 271 diarrhea cases and 149 healthy controls over 5 years. The male-to-female ratio was 0.964 in diarrhea cases and 0.961 in healthy controls (χ2 < 0.001, p = 0.987), respectively. The median age was 40.0 years in acute diarrhea cases and 41.4 years in non-diarrheal group(t = 0.817, p = 0.414). The diarrhea cases from urban areas accounted for 67.9%, and the non-diarrhea patients accounted for 66.4% (χ2 = 1.240, p = 0.538). The subjects in the 5–15 years age group was 64.5% in diarrhea cases and 63.1% in healthy controls (χ2 = 0.767, p = 0.681). The most frequent clinical symptom was nausea (n = 91, 33.6%) in diarrhea cases, and other common symptoms included abdominal pain (n = 73, 26.9%), vomiting (n = 58, 21.4%) and fever (n = 22, 8.1%). Mucus stool (n = 173, 63.8%) was the most common stool type in diarrhea cases, followed by watery stool (n = 70, 25.8%) and other types of stool (n = 28, 10.3%) (Table 2). The frequency of diarrhea was 5.8 times in acute diarrhea cases within 24 h (Additional file 2).
Table 2

Basic information and clinical characteristics of 271 acute diarrhea cases and 149 controls over 5 years

Characteristic

Diarrhea

Control

n (%)

n (%)

n

271

149

Age

 5–15 years

21 (7.7)

9 (6.0)

 15–50 years

175 (64.6)

94 (63.1)

 ≥50 years

75 (27.7)

46 (30.9)

Sex

 Male

133 (49.1)

73 (49.0)

 Female

138 (50.9)

76 (51.0)

Residence

 Urban

184 (67.9)

99 (66.4)

 Rural–urban fringe zone

68 (25.1)

35 (23.5)

 Rural

19 (7.0)

15 (10.1)

Seasons

 Spring (Feb–Apr)

87 (32.1)

32 (21.5)

 Summer (May–Jul)

65 (24.0)

42 (28.2)

 Autumn (Aug–Oct)

59 (25.5)

45 (30.2)

 Winter (Nov–Jan)

50 (18.5)

30 (37.5)

Symptom

 Fever (>37.3 °C)

23 (8.5)

 Abdominal pain

73 (26.9)

 Nausea

91 (33.6)

 Vomiting

58 (21.4)

 Dehydration

3 (1.1)

 Tenesmus

5 (1.8)

Diarrhea

 

 Watery stool

70 (25.8)

 Mucus stool

173 (63.8)

 Other stool

28 (10.3)

SD represent for standard deviation. Kunming city (25º 02′ 20″ N, 102º 43′05″ E, 1891 m.a.s.l.) has a humid subtropical climate of moderate seasonality characterized by a mild (mean temperature = 11.4 °C, min = 8, max = 15) and dry (mean precipitation = 33.4 mm, min = 12, max = 89) autumn (Aug–Oct) and winter (Nov–Jan). Spring (Feb–Apr) and summer (May–Jul) are also mild (mean temperature = 23 °C, min = 19, max = 29) but wet (mean precipitation = 159.6 mm, min = 92, max = 206) seasons. The “–” symbol indicates the information can not be collected

The prevalence of enteropathogen in subjects with diarrhea or not

At least one enteropathogen was isolated from 79 (29.2%) of 271 acute diarrhea cases and 18 (12.1%) of 149 healthy controls (χ2 = 15.774, p < 0.0001). The overall prevalence of bacterial pathogen and viral pathogen in diarrhea cases were higher than in healthy controls (χ2 = 11.327, p = 0.001; χ2 = 10.795, p = 0.001 respectively. Table 3). At least one intestinal protozoa was found in 4.8% (n = 13) of cases and 6.0% (n = 9) of controls (χ2 = 0.299, p = 0.584) (Table 3). In univariate analysis, Details of the enteric pathogens isolates are presented in Table 3, and according to that EAEC, NoV and RVA were more prevalent (χ2 = 7.061, p = 0.008; χ2 = 9.160, p = 0.002; χ2 = 7.061, p = 0.008 respectively) in diarrhea patients (7.4, 10.0, 7.4%, respectively) than in healthy controls (1.3, 2.0, 1.3%, respectively, Table 3). No statistical difference was observed between acute diarrhea patients and healthy subjects for EPEC, ETEC, NTS, Plesiomonas spp., SaV, As, B. hominis and Cryptosporidium spp. In addition, other enteric parasites were not detected in subjects with and without diarrhea (Table 3). However, the multivariate analysis showed that only RVA was an enteric pathogen associated with diarrhea. But EAEC and NoV GII did not relate with diarrheal illness among individuals over 5 years (Table 3).
Table 3

Enteric pathogens in the stool samples with diarrhea cases (n = 271) and healthy controls (n = 149) in Kunming, China

Enteropathogen

Diarrhea cases

n = 271

n (%)

Healthy controls

n = 149

n (%)

Univariate analysis

Multivariate analyses

p value

OR (95% CI)

p value

OR (95% CI)

At least one enteropathogen

79 (29.2)

18 (12.1)

p < 0.0001

3.00 (1.71–5.23)

At least one enteric bacterial pathogens

37 (13.7)

5 (3.4)

p = 0.001

4.55 (1.75–11.85)

 DEC

34 (12.5)

5 (3.4)

p = 0.002

4.13 (1.58–10.80)

  EAEC

20 (7.4)

2 (1.3)

p = 0.008

5.86 (1.35–25.41)

p = 0.198

5.95 (1.33–26.63)

  EPEC

15 (5.5)

3 (2.0)

p = 0.088

2.85 (0.81–10.01)

p = 0.107

2.86 (0.80–10.27)

  ETEC

1 (0.4)

0 (0.0)

  EIEC

0 (0.0)

0 (0.0)

  EHEC

0 (0.0)

0 (0.0)

 NTS

2 (0.7)

0 (0.0)

p = 0.541

 Plesiomonas spp.

1 (0.4)

0 (0.0)

 Vibrio parahaemolyticus

0 (0.0)

0 (0.0)

 Vibrio cholera

0 (0.0)

0 (0.0)

 Aeromonas spp.

0 (0.0)

0 (0.0)

 Shigella spp.

0 (0.0)

0 (0.0)

At least one enteric virus pathogens

39 (14.4)

6 (4.0)

p = 0.001

4.00 (1.66–9.70)

 NoV GII

27 (10.0)

3 (2.0)

p = 0.002

5.38 (1.60–18.06)

p = 0.0794

3.86 (0.85–17.48)

 RVA

20 (7.4)

2 (1.3)

p = 0.008

5.86 (1.35–25.41)

p = 0.0166

4.50 (1.31–15.43)

 NoV GI

1 (0.4)

0 (0.0)

 SaV

1 (0.4)

0 (0.0)

 As

0 (0.0)

1 (0.7)

p = 0.355

 Ad

0 (0.0)

0 (0.0)

  

At least one enteric parasite pathogens

13 (4.8)

9 (6.0)

p = 0.584

0.78 (0.33–1.88)

  

 B. hominis

13 (4.8)

9 (6.0)

p = 0.584

0.78 (0.33–1.88)

p = 0.412

0.68 (0.27–1.71)

 Cryptosporidium spp.

1 (0.4)

0 (0.0)

 Giardia lamblia

0 (0.0)

0 (0.0)

Including the co-infection of enteric pathogens in diarrhea cases and healthy subjects. The “–” symbol indicates the data can not be calculated

In diarrhea cases, DEC (12.5%, n = 34) was the most common pathogen, followed by NoV GII (10.0%, n = 27), RVA (7.0%, n = 20) and B. hominis (4.8%, n = 13).

Temporal distribution of enteric pathogen in diarrhea cases

The prevalence of EAEC, EPEC, RVA and B. hominis showed strong seasonal variations (Table 4). The detection rate of EAEC in summer was higher than in winter (p = 0.0045), and the prevalence of EPEC in summer was higher than in winter (p = 0.0156). RVA was mainly prevalent in autumn and winter (p = 0.0015), and the prevalence peak of B. hominis was summer (p < 0.0001). NoV GII was not statistically different in four seasons (χ2 = 3.359, p = 0.341).
Table 4

The seasonal characteristics of mainly enteric pathogen isolated from diarrhea cases

Enteropathogen

Spring

(Feb–Apr)

n = 87

n (%)

Summer

(May–Jul)

n = 65

n (%)

Autumn

(Aug–Oct)

n = 69

n (%)

Winter

(Nov–Jan)

n = 50

n (%)

χ2

p value

EAEC

1 (1.2)

9 (13.8)

8 (11.6)

2 (4.0)

p = 0.0045

EPEC

7 (8.0)

7 (10.8)

1 (1.4)

0 (0.0)

p = 0.0156

RVA

4 (4.6)

0 (0.0)

8 (11.6)

8 (16.0)

p = 0.0015

NoV

5 (5.7)

7 (10.8)

10 (14.5)

5 (10.0)

3.359

p = 0.341

B. hominis

0 (0.0)

7 (10.8)

6 (8.7)

0 (0.0)

p < 0.0001

Including the co-infection of any enteric pathogens in diarrhea cases. The “–” symbol indicates that data be calculated with Fisher-exact tests

Prevalence of enteric pathogens in diarrhea cases in different age group

Acute diarrhea cases were divided into different age groups, in which 21 (7.7%), 175 (64.6%) and 75 (27.7%) belong to age groups of 5–15, 15–50 and ≥50 years (Table 5). EPEC infection was the highest in the age group of 5–15 years (p = 0.031) (Table 5), but the prevalence of EAEC, RVA, NoV GII and B. hominis were not statistical difference among these three age groups (Table 5), respectively.
Table 5

Prevalence of enteric pathogens in diarrhea cases in different age groups

Enteropathogen

Total

n = 271

n (%)

5–15 years

n = 21

n (%)

15–50 years

n = 175

n (%)

≥50 years

n = 75

n (%)

χ2

p value

At least one enteropathogens

79 (29.2)

9 (42.9)

52 (29.7)

18 (24.0)

2.90

p = 0.234

At least one bacterium

37 (13.7)

5 (23.8)

27 (15.4)

5 (6.7)

5.41

p = 0.0668

At least one virus

39 (14.4)

4 (19.0)

23 (13.1)

12 (16.0)

0.748

p = 0.688

At least one parasite

13 (4.8)

1 (4.8)

10 (5.7)

2 (2.7)

p = 0.654

EAEC

20 (7.4)

1 (4.8)

16 (9.1)

3 (4.0)

2.56

p = 0.323

EPEC

15 (5.5)

4 (19.0)

9 (5.0)

2 (2.7)

p = 0.031

NoV

27 (10.0)

4 (19.0)

15 (8.6)

8 (10.7)

2.35

p = 0.309

RVA

20 (7.4)

2 (9.5)

13 (7.4)

5 (6.7)

0.198

p = 0.906

B. hominis

13 (4.8)

1 (4.8)

10 (5.7)

2 (2.7)

p = 0.654

Including the co-infection of any enteric pathogens in diarrhea cases. The “–” symbol indicates that data be calculated with Fisher-exact tests

Co-infection of enteric pathogen in diarrhea cases and healthy cases

In this study, the prevalence of co-infection with more than one enteric pathogens was higher than in healthy controls (Table 6, p = 0.0059, OR = 6.17, 95% CI 1.43–26.71). In various co-infection cases, the co-infection with two enteric pathogens was more commonly detected in diarrhea patients than non-diarrhea subjects (Table 6, p = 0.0079, OR = 5.86, 95% CI 1.35–25.41). However, the prevalence of co-infection with more than three enteric pathogens in patents was as much as in healthy controls.
Table 6

The co-infection of enteric pathogens detected in diarrhea cases and healthy controls

Co-infections of enteric pathogens

Diarrhea cases

n = 271

n (%)

Healthy controls

n = 149

n (%)

p value

OR (95% CI)

Any two any enteric pathogens

20 (7.4)

2 (1.3)

p = 0.0079

5.86 (1.35–25.41)

Virus–virus

9 (3.3)

0 (0.0)

p = 0.0298

 RVA–NoV GII

8 (3.0)

0 (0.0)

p = 0.0549

Bacteria–virus

5 (1.8)

0 (0.0)

p = 0.166

 DEC–NoV GII

4 (1.5)

0 (0.0)

p = 0.302

 DEC–RVA

3 (1.1)

0 (0.0)

p = 0.556

Bacteria–protozoan

3 (1.1)

2 (1.3)

p = 0.999

0.83 (0.14–5.00)

 DEC–B. hominis

3 (1.1)

2 (1.3)

p = 0.999

0.83 (0.14–5.00)

Any three enteric pathogens

1 (0.4)

0 (0.0)

p = 0.999

 DEC–RVA–Cryptosporidium spp.

1 (0.4)

0 (0.0)

p = 0.999

Total

21 (7.7)

2 (1.3)

p = 0.0059

6.17 (1.43–26.71)

Only co-infections with two pathogens found in at least 1% of diarrhea cases have been shown. The “–” symbol indicates the data can not be calculated

20 diarrhea cases of co-infections with two pathogens was identified, whereby two pathogens were identified, the prominent prevalence was virus–virus (45.0%, 9/20), followed by bacteria–virus (25.0%, 5/20) and bacteria–protozoan (15.0%, 3/20), and the other comprised co-infection was less common in diarrhea cases. The highest prevalence of co-infection in diarrhea cases was RVA–NoV GII (3.0%, n = 8), followed by DEC–NoV GII (1.5%, n = 4), DEC–RVA (1.1%, n = 3) and DEC–B. hominis (1.1%, n = 3). The prevalence of other co-infection between two pathogens was less than 1.0% in acute diarrhea cases (Table 6).

Discussion

Since most studies had focused on diarrheal illness in children under 5 years [6, 11], little is known about the prevalence of acute diarrhea caused by enteric pathogens among person over 5 years. This study was the first of its kind conducted to determine the enteropathogens of acute diarrheal disease in Yunnan Province, China, and a series of pathogens involving bacteria, viruses and parasites were examined with a combination of conventional and molecular diagnostic techniques.

The detection rate of at least one enteric pathogen was significantly higher in diarrhea cases than in healthy controls, which showed a wide range of pathogens involving bacteria, and similar results have also been obtained from other countries [29, 30]. Although bacteria and parasites were the prominent enteropathogen in acute diarrheal cases aged more than 5 years in some developing countries [31], to our surprise, viral pathogens (RVA and NoV) were the most common pathogen in present study.

DEC were detected with a PCR method in stool sample from the patients and non-diarrheal controls, and the result showed that DEC wasn’t the causative agent of diarrhea in individuals over 5 years, and similar conclusions were shown in another study [32]. However, the authors of the other study argued that DEC was one of important enteric pathogen causing acute diarrhea [33]. The detection rate of DEC in present study was lower than that presented in other study [32], but it was higher than that presented in other region of China [11]. The prevalence of DEC varies greatly in different regions due to the detection method [11], behavior habits, geography and environmental hygiene among different areas [34]. Although the molecular biology techniques (e.g. PCR and Real-time PCR) are useful for detecting DEC, PCR was not used widely in medical facilities because of constraints in many developing countries, including the poor laboratory conditions, limited funds and low detection capacities of staff [16]. Hence, DEC was not a pathogen that was routinely detected in clinical laboratories especially in low and middle income countries [35, 36]. The DEC was detected in many studies with the traditional serum agglutination method which has low sensitivity and specificity. Therefore, the prevalence of DEC was underestimated and the pathogenic spectrum of acute diarrheal illness was not accurately described [4]. It was accurately described to detect DEC by PCR with high sensitivity and specificity due to the following reasons [31]: Firstly, the clinical symptom of diarrhea caused by different DEC subtypes and other enteropathogens cannot be distinguished easily. Secondly, DEC is widely prevalent in food and environment, and the modern tourism and trade had accelerated the spread of DEC. The modern detection method (e.g. PCR) can improve the sensitivity and specificity for detecting DEC in stool samples in order to accurately assess the burden of DEC in cases [4, 31]. In addition, the modern method has advantages in saving diagnosis time and reducing workload of finding DEC in diarrhea cases. Especially, it is more accurate to identify the various DEC subtypes, and it can be completed more quickly and more accurately.

EAEC is also the leading cause of diarrhea in children, adult and HIV-positive patients worldwide [37, 38]. In addition, EAEC was one of major causes of diarrhea outbreak in some developed countries (e.g. Europe, the UK and Japan) [31, 38]. EAEC was not the important bacterial pathogen associated diarrhea in individuals over 5 years in present study, and similar conclusion was obtained from other study [32]. However another study showed that EAEC was associated with diarrheal disease [33]. Further studies found that the concentration with 1010 CFU of serotype 042 EAEC strain can lead to diarrhea, but other serotype of EAEC strain cannot cause diarrhea in children and adults [37, 38]. It can be deducted that the genotype is likely to be an important factor in determining pathogenicity. The detection rate of EAEC in this study was as high as 7.4%, which was similar to the other study [33]. However the prevalence of EAEC was still lower than in many developing countries [37]. In the present study, EPEC was also not associated with diarrhea disease, similar to other study [31]. Further mechanism research might be conducted to explore the pathogenicity and infectivity at a genetic level.

Adults suffering diarrhea rarely visit a medical institution, unless they have acute serious or persistent diarrhea. The study suggests that although many enteric pathogens were detected from diarrhea patients over 5 years old, only RVA was significantly related with diarrheal illness in individuals over 5 years old. This study provides further evidence that RVA is a cause of acute adult diarrhea in China, but other study show that RVA was not an etiological agent with diarrhea [32]. The frequency of RVA infection (7.4%) was close to other study (9.6%) [39], but was higher than in the study (2.6%) conducted in adolescents or adults (10–89 years) in Italy [40].

NoV GII is one of major pathogens which can lead sporadic and outbreak acute diarrhea cases across all age groups worldwide [41]. The present study showed that NoV GII was the second most common enteropathogen in diarrhea cases. The high prevalence of NoV GII in individuals might be attributed to frequent social activities, and NoV GII is one of the most important food borne pathogen and exists widely in foods (such as shellfish, vegetables and water, et al.). These foods contaminated with NoV GII were primary reasons to lead sporadic and outbreak acute diarrhea [4245]. The detection rate of NoV GII in our study was lower than that of in other study [46, 47]. The reason might be that seafood (e.g. shellfish) was not easily obtained and was not a conventional food in inland of China, including Kunming city.

Blastocystis hominis was found to be the most common protozoan in gastrointestinal tract of human and animals. It was widespread in natural world [48] and was highly prevalent in immunodeficiency patients [49]. Blastocystis hominis was not a pathogenic agent in present study, but other studies showed that B. hominis was a diarrhea-associated pathogen [50, 51]. Blastocystis hominis had high prevalence in healthy controls in present study implied that B. hominis was carried in health individual, which was a common phenomenon [50]. Whether B. hominis was one of pathogenic pathogen is need to explore the pathogenicity of different subtypes and mechanism. Cryptosporidium spp. and G. lamblia are leading cause of acute and chronic diarrhea in the tropics regions and some developing counties [52], but Cryptosporidium spp. had low prevalence and no one G. lamblia was detected in cases and healthy controls in present study, which indicating that these two kinds of intestinal protozoa were not serious disease burden and intimidate to individuals over 5 years old. This low prevalence of two protozoa might be due to epidemic characteristics of enteric parasites. Our research field was selected in urban with perfective municipal facilities of sewage treatment system, chlorine disinfection water, as well as, the population with high living level and health habits, so that the detection rate of enteric protozoa was very low, and the same results was showed in other studies in China [5, 17].

The co-infection was not neglected in diarrhea cases (7.7%) in this study, although other studies found that co-infection was high prevalent in sick individuals (13.0, 35.0, 25.0%, respectively) [12, 13, 53]. The co-infection leads to that individuals with greater levels of morbidity and mortality, making persons more vulnerable to species, for instance, the co-infection of RVA and other enteric pathogen can aggravate diarrheal symptom [14, 54]. In addition, the co-infection adds the difficulty to accurately determine etiological role of the enteric pathogen. Although co-infection by multiple groups of pathogens is the norm rather than the exception in nature, most research on the effect of pathogens on their hosts has been largely based on a single or few pathogen species [15]. Understanding the causes and consequences of co-infection among enteric pathogens remains one of the major challenges. Nevertheless, there is an increasing interest to move from the ‘diarrheal disease-one enteric pathogen’ perspective to a more holistic view of hosts as ecosystems of diarrhea illness [6], partially motivated by the health impact of co-occurring infections. In fact, in such complex ‘host–enteric pathogen ecosystems’ a variety of both direct and indirect interactions between enteric pathogens, their hosts and the circumstances must be taken into account [55].

Limitations of this study

It was indentified several limitations in this study. Firstly, the study was conducted in an urban region that probably shows a poor representation of the potential enteric pathogen. Secondly, the diarrhea cases were selected from outpatients and hospitalized cases. But the patients who did not to seek medical advice were not recruited. Thirdly, helminthes and some intestinal bacteria were not detected in this study. Fourthly, the percentage of diarrheal patients who have taken antibiotics before the admission was not known, which may influence the detection rate of bacterial pathogens. In addition, enteric protozoa were not detected with microscopy, and the concentration of DNA in 1 μL can be different and therefore, the outcome of PCR might not be comparable [56]. Therefore, further research involved diarrhea case from urban, rural, outpatient and hospitalized might be done to evaluate the burden of diarrhea disease and assess the association between diarrhea and specific enteric pathogen. Match case–control study will be a good choice, and quantitate the DNA by nanodrop or something else and then loaded equal amount of DNA (e.g. 1 ng) for every PCR reaction will be have high reliability for entire project.

Conclusions

Although it appears clear that RVA has impact on diarrhea illness, it was ignored in individuals over 5 years old. The prevalence of DEC was high in diarrhea cases, but it would be largely neglected due to lack of access to good quality diagnostic tests, which suggests that enhance laboratory capacities are urgently need in order to implement diarrhea surveillance programs. The co-infection was high prevalent in diarrhea cases, which will respond to better medical and public health interventions of diarrhea disease. In view of the diarrhea cases detected in urban region of Kunming city, Yunnan Province, which have effluent sewerage system, good sanitary condition and clean drinking water, it is concluded that food pollution might be the leading cause of acute gastroenteritis.

Notes

Abbreviations

Ad: 

adenovirus

As: 

astrovirus

AWP: 

alkaline peptone water

B. hominis

Blastocystis hominis

CI: 

confidence interval

CFU: 

colony-forming unit-megakaryocyte

DEC: 

diarrheagenic E. coli

EAEC: 

enteroaggregative E. coli

EHEC: 

enterohemorrhagic E. coli

EIEC: 

enteroinvasive E. coli

EPEC: 

enteropathogenic E. coli

ETEC: 

enterotoxigenic E. Coli

G. lamblia

Giardia lamblia

MAC: 

macConkey agar

NoV: 

norovirus

NTS: 

non-typhoidal salmonella

OR: 

odd ratios

qPCR: 

quantitative PCR

RT-PCR: 

reverse transcription polymerase chain reaction

RVA: 

rotavirus A group

SaV: 

sapovirus

SD: 

standard deviation

SS: 

Salmonella–Shigella

TCBS: 

thiosulfate-citrate-bile salts-sucrose

WHO: 

World Health Organization

XLD: 

xylose, lysine and deoxycholate agar

Declarations

Authors’ contributions

SX-Z and ES performed the statistical analysis and drafted the manuscript. LG-T, JX-C, WH and XN-Z conceived and designed the study, CL-Y, LA, WP-G, XZ, SZ-L, SL, ZS-D and JH-C conducted the dates collected and pathogens detected, PY edited the English. All authors read and approved the final manuscript.

Acknowledgements

None.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

Data of the study can be available upon request from the corresponding author (XN-Z).

Ethics approval and consent to participate

The study was approved by the ethical review committee of the National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention. Informed verbal or written consent was obtained from the subject or their parents/guardians before collecting the stool samples.

Funding

Development of PCR to detect virus, G. lamblia was supported by the National Science and Technology Major Project (Grant number: 2008ZX10004-011); Development of PCR to find Cryptosporidium spp. was supported by National Science and Technology Major Project (2012ZX10004-220). The B. hominis identified was supported from National Natural Science Foundation of China (Grant number: 81473022). The field epidemiological investigation was supported by Chinese Special Program for Scientific Research of Public Health (No. 201502021). The bacterial pathogens identified was supported by The Fourth Round Three Year Action Plan Public Health of Shanghai city (GWIV-29). The data analysis was supported from the fund of the postdoctoral programme of the Fundação para a Ciência ea Tecnologia the Fundação para a Ciência ea Tecnologia, Portugal (SFRH/BPD/96637/2013).

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention
(2)
Key Laboratory for Parasitology and Vector Biology, MOH of China, WHO Collaborating Center for Tropical Diseases, National Center for International Research on Tropical Diseases
(3)
Yunnan Provincial Center for Disease Control and Prevention
(4)
Center for Environmental and Marine Studies (CESAM), Departamento de Biología, Universidade de Aveiro
(5)
Servei d´Ecopatologia de Fauna Salvatge (SEFaS), Departament de Medicina i Cirurgia Animals, Universitat Autònoma de Barcelona (UAB)
(6)
Department of parasitology, College of Medicine, Soochow University

References

  1. Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, Abraham J, Adair T, Aggarwal R, Ahn SY, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the global burden of disease study 2010. Lancet. 2012;380(9859):2095–128. doi:https://doi.org/10.1016/S0140-6736(12)61728-0.View ArticlePubMedGoogle Scholar
  2. Walker CL, Rudan I, Liu L, Nair H, Theodoratou E, Bhutta ZA, O’Brien KL, Campbell H, Black RE. Global burden of childhood pneumonia and diarrhoea. Lancet. 2013;381(9875):1405–16. doi:https://doi.org/10.1016/S0140-6736(13)60222-6.View ArticlePubMedGoogle Scholar
  3. Platts-Mills JA, Babji S, Bodhidatta L, Gratz J, Haque R, Havt A, McCormick BJ, McGrath M, Olortegui MP, Samie A, et al. Pathogen-specific burdens of community diarrhoea in developing countries: a multisite birth cohort study (MAL-ED). Lancet Glob Health. 2015;3(9):e564–75. doi:https://doi.org/10.1016/S2214-109X(15)00151-5.View ArticlePubMedGoogle Scholar
  4. Liu J, Kabir F, Manneh J, Lertsethtakarn P, Begum S, Gratz J, Becker SM, Operario DJ, Taniuchi M, Janaki L, et al. Development and assessment of molecular diagnostic tests for 15 enteropathogens causing childhood diarrhoea: a multicentre study. Lancet Infect Dis. 2014;14(8):716–24. doi:https://doi.org/10.1016/S1473-3099(14)70808-4.View ArticlePubMedGoogle Scholar
  5. Hao R, Li P, Wang Y, Qiu S, Wang L, Li Z, Xie J, Wu Z, Lin R, Liu N, et al. Diversity of pathogens responsible for acute diarrheal disease in China. Clin Infect Dis. 2013;57(12):1788–90. doi:https://doi.org/10.1093/cid/cit572.View ArticlePubMedGoogle Scholar
  6. Zhang SX, Zhou YM, Xu W, Tian LG, Chen JX, Chen SH, Dang ZS, Gu WP, Yin JW, Serrano E, et al. Impact of co-infections with enteric pathogens on children suffering from acute diarrhea in southwest China. Infect Dis Poverty. 2016;5(1):64. doi:https://doi.org/10.1186/s40249-016-0157-2.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Nic Fhogartaigh C, Dance DAB. Bacterial gastroenteritis. Medicine. 2013;41(12):693–9.View ArticleGoogle Scholar
  8. Fischer WC, Sack D, Black RE. Etiology of diarrhea in older children, adolescents and adults: a systematic review. PLoS Negl Trop Dis. 2010;4(8):e768. doi:https://doi.org/10.1371/journal.pntd.0000768.View ArticleGoogle Scholar
  9. Duan ZJ, Liu N, Yang SH, Zhang J, Sun LW, Tang JY, Jin Y, Du ZQ, Xu J, Wu QB, et al. Hospital-based surveillance of rotavirus diarrhea in the People’s Republic of China, August 2003–July 2007. J Infect Dis. 2009;200(Suppl 1):S167–73. doi:https://doi.org/10.1086/605039.View ArticlePubMedGoogle Scholar
  10. Tang MB, Chen CH, Chen SC, Chou YC, Yu CP. Epidemiological and molecular analysis of human norovirus infections in Taiwan during 2011 and 2012. BMC Infect Dis. 2013;13:338. doi:https://doi.org/10.1186/1471-2334-13-338.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Qu M, Deng Y, Zhang X, Liu G, Huang Y, Lin C, Li J, Yan H, Li X, Jia L, et al. Etiology of acute diarrhea due to enteropathogenic bacteria in Beijing, China. J Infect. 2012;65(3):214–22. doi:https://doi.org/10.1016/j.jinf.2012.04.010.View ArticlePubMedGoogle Scholar
  12. Nimri LF, Elnasser Z, Batchoun R. Polymicrobial infections in children with diarrhoea in a rural area of Jordan. FEMS Immunol Med Microbiol. 2004;42(2):255–9.View ArticlePubMedGoogle Scholar
  13. Vu NT, Le Van P, Le Huy C, Nguyen GK, Weintraub A. Etiology and epidemiology of diarrhea in children in Hanoi, Vietnam. Int J Infect Dis. 2006;10(4):298–308.View ArticleGoogle Scholar
  14. Bhavnani D, Goldstick JE, Cevallos W, Trueba G, Eisenberg JNS. Synergistic effects between rotavirus and coinfecting pathogens on diarrheal disease: evidence from a community-based study in Northwestern Ecuador. Am J Epidemiol. 2012;176(5):387–95. doi:https://doi.org/10.1093/aje/kws220.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Serrano E, Millan J. What is the price of neglecting parasite groups when assessing the cost of co-infection? Epidemiol Infect. 2014;142(7):1533–40. doi:https://doi.org/10.1017/S0950268813002100.View ArticlePubMedGoogle Scholar
  16. Zhang Y, Zhao Y, Ding K, Wang X, Chen X, Liu Y, Chen Y. Analysis of bacterial pathogens causing acute diarrhea on the basis of sentinel surveillance in Shanghai, China, 2006–2011. Jpn J Infect Dis. 2014;67(4):264–8.View ArticlePubMedGoogle Scholar
  17. Yu J, Jing H, Lai S, Xu W, Li M, Wu J, Liu W, Yuan Z, Chen Y, Zhao S, et al. Etiology of diarrhea among children under the age five in China: results from a five-year surveillance. J Infect. 2015;71(1):19–27. doi:https://doi.org/10.1016/j.jinf.2015.03.001.View ArticlePubMedPubMed CentralGoogle Scholar
  18. Liu N, Xu Z, Li D, Zhang Q, Wang H, Duan ZJ. Update on the disease burden and circulating strains of rotavirus in China: a systematic review and meta-analysis. Vaccine. 2014;32(35):4369–75. doi:https://doi.org/10.1016/j.vaccine.2014.06.018.View ArticlePubMedGoogle Scholar
  19. The World Health Organization. http://www.who.int/mediacentre/factsheets/fs330/en/. Accessed Apr 2013.
  20. Deer DM, Lampel KA. Development of a multiplex real-time PCR assay with internal amplification control for the detection of Shigella species and enteroinvasive Escherichia coli. J Food Prot. 2010;73(9):1618–25.PubMedGoogle Scholar
  21. Hidaka A, Hokyo T, Arikawa K, Fujihara S, Ogasawara J, Hase A, Hara-Kudo Y, Nishikawa Y. Multiplex real-time PCR for exhaustive detection of diarrhoeagenic Escherichia coli. J Appl Microbiol. 2009;106(2):410–20. doi:https://doi.org/10.1111/j.1365-2672.2008.04043.x.View ArticlePubMedGoogle Scholar
  22. Iturriza GM, Wong C, Blome S, Desselberger U, Gray J. Molecular characterization of VP6 genes of human rotavirus isolates: correlation of genogroups with subgroups and evidence of independent segregation. J Virol. 2002;76(13):6596–601.View ArticleGoogle Scholar
  23. Zintz C, Bok K, Parada E, Barnes-Eley M, Berke T, Staat MA, Azimi P, Jiang X, Matson DO. Prevalence and genetic characterization of caliciviruses among children hospitalized for acute gastroenteritis in the United States. Infect Genet Evol. 2005;5(3):281–90.View ArticlePubMedGoogle Scholar
  24. Yan H, Yagyu F, Okitsu S, Nishio O, Ushijima H. Detection of norovirus (GI, GII), sapovirus and astrovirus in fecal samples using reverse transcription single-round multiplex PCR. J Virol Methods. 2003;114(1):37–44.View ArticlePubMedGoogle Scholar
  25. Khamrin P, Okame M, Thongprachum A, Nantachit N, Nishimura S, Okitsu S, Maneekarn N, Ushijima H. A single-tube multiplex PCR for rapid detection in feces of 10 viruses causing diarrhea. J Virol Methods. 2011;173(2):390–3. doi:https://doi.org/10.1016/j.jviromet.2011.02.012.View ArticlePubMedGoogle Scholar
  26. Menounos PG, Spanakos G, Tegos N, Vassalos CM, Papadopoulou C, Vakalis NC. Direct detection of Blastocystis sp. in human faecal samples and subtype assignment using single strand conformational polymorphism and sequencing. Mol Cell Probes. 2008;22(1):24–9.View ArticlePubMedGoogle Scholar
  27. Liu H, Shen Y, Yin J, Yuan Z, Jiang Y, Xu Y, Pan W, Hu Y, Cao J. Prevalence and genetic characterization of Cryptosporidium, Enterocytozoon, Giardia and Cyclospora in diarrheal outpatients in China. BMC Infect Dis. 2014;14:25. doi:https://doi.org/10.1186/1471-2334-14-25.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Sulaiman IM, Fayer R, Bern C, Gilman RH, Trout JM, Schantz PM, Das P, Lal AA, Xiao L. Triosephosphate isomerase gene characterization and potential zoonotic transmission of Giardia duodenalis. Emerg Infect Dis. 2003;9(11):1444–52.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Albert MJ, Faruque AS, Faruque SM, Sack RB, Mahalanabis D. Case–control study of enteropathogens associated with childhood diarrhea in Dhaka, Bangladesh. J Clin Microbiol. 1999;37(11):3458–64.PubMedPubMed CentralGoogle Scholar
  30. Randremanana R, Randrianirina F, Gousseff M, Dubois N, Razafindratsimandresy R, Hariniana ER, Garin B, Randriamanantena A, Rakotonirina HC, Ramparany L, et al. Case–control study of the etiology of infant diarrheal disease in 14 districts in Madagascar. PLoS ONE. 2012;7(9):e44533. doi:https://doi.org/10.1371/journal.pone.0044533.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Thompson CN, Phan MV, Hoang NV, Minh PV, Vinh NT, Thuy CT, Nga TT, Rabaa MA, Duy PT, Dung TT, et al. A prospective multi-center observational study of children hospitalized with diarrhea in Ho Chi Minh City, Vietnam. Am J Trop Med Hyg. 2015;92(5):1045–52. doi:https://doi.org/10.4269/ajtmh.14-0655.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Al-Gallas N, Bahri O, Bouratbeen A, Ben Haasen A, Ben Aissa R. Etiology of acute diarrhea in children and adults in Tunis, Tunisia, with emphasis on diarrheagenic Escherichia coli: prevalence, phenotyping, and molecular epidemiology. Am J Trop Med Hyg. 2007;77(3):571–82.PubMedGoogle Scholar
  33. Bruijnesteijn VCL, Dullaert-de BM, Ruijs GJ, van der Reijden WA, van der Zanden AG, Weel JF, Schuurs TA. Case–control comparison of bacterial and protozoan microorganisms associated with gastroenteritis: application of molecular detection. Clin Microbiol Infect. 2015;21(6):592-e9–19. doi:https://doi.org/10.1016/j.cmi.2015.02.007.View ArticleGoogle Scholar
  34. Okeke IN. Diarrheagenic Escherichia coli in sub-Saharan Africa: status, uncertainties and necessities. J Infect Dev Ctries. 2009;3(11):817–42.PubMedGoogle Scholar
  35. Gerner-Smidt P, Jensen C, Olsen KE, Scheutz F, Molbak K, Olesen B. Diarrheagenic potential of Escherichia coli in children in a developed country. J Clin Microbiol. 2003;41(12):5836.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Estrada-Garcia T, Cerna JF, Paheco-Gil L, Velazquez RF, Ochoa TJ, Torres J, DuPont HL. Drug-resistant diarrheogenic Escherichia coli, Mexico. Emerg Infect Dis. 2005;11(8):1306–8.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Huang DB, Mohanty A, DuPont HL, Okhuysen PC, Chiang T. A review of an emerging enteric pathogen: enteroaggregative Escherichia coli. J Med Microbiol. 2006;55(Pt 10):1303–11.View ArticlePubMedGoogle Scholar
  38. Hebbelstrup JB, Olsen KE, Struve C, Krogfelt KA, Petersen AM. Epidemiology and clinical manifestations of enteroaggregative Escherichia coli. Clin Microbiol Rev. 2014;27(3):614–30. doi:https://doi.org/10.1128/CMR.00112-13.View ArticleGoogle Scholar
  39. Luchs A, Cilli A, Morillo SG, de Cassia CCR, Do CSTT. Rotavirus in adults, Brazil, 2004–2011: g2P[4] dominance and potential impact on vaccination. Braz J Infect Dis. 2014;18(1):53–9. doi:https://doi.org/10.1016/j.bjid.2013.05.010.View ArticlePubMedGoogle Scholar
  40. Ianiro G, Delogu R, Bonomo P, Fiore L, Ruggeri FM. Molecular analysis of group A rotaviruses detected in adults and adolescents with severe acute gastroenteritis in Italy in 2012. J Med Virol. 2014;86(6):1073–82. doi:https://doi.org/10.1002/jmv.23871.View ArticlePubMedGoogle Scholar
  41. Ahmed SM, Hall AJ, Robinson AE, Verhoef L, Premkumar P, Parashar UD, Koopmans M, Lopman BA. Global prevalence of norovirus in cases of gastroenteritis: a systematic review and meta-analysis. Lancet Infect Dis. 2014;14(8):725–30. doi:https://doi.org/10.1016/S1473-3099(14)70767-4.View ArticlePubMedGoogle Scholar
  42. Campos CJ, Lees DN. Environmental transmission of human noroviruses in shellfish waters. Appl Environ Microbiol. 2014;80(12):3552–61.View ArticlePubMedPubMed CentralGoogle Scholar
  43. Hall AJ, Eisenbart VG, Etingue AL, Gould LH, Lopman BA, Parashar UD. Epidemiology of foodborne norovirus outbreaks, United States, 2001–2008. Emerg Infect Dis. 2012;18(10):1566–73. doi:https://doi.org/10.3201/eid1810.120833.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Crim SM, Iwamoto M, Huang JY, Griffin PM, Gilliss D, Cronquist AB, Cartter M, Tobin-D’Angelo M, Blythe D, Smith K, et al. Incidence and trends of infection with pathogens transmitted commonly through food—foodborne diseases active surveillance network, 10 US sites, 2006–2013. MMWR Morb Mortal Wkly Rep. 2014;63(15):328–32.PubMedGoogle Scholar
  45. Huang J, Xu X, Weng Q, Hong H, Guo Z, He S, Niu J. Serial foodborne norovirus outbreaks associated with multiple genotypes. PLoS ONE. 2013;8(5):e63327. doi:https://doi.org/10.1371/journal.pone.0063327.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Tian G, Jin M, Li H, Li Q, Wang J, Duan ZJ. Clinical characteristics and genetic diversity of noroviruses in adults with acute gastroenteritis in Beijing, China in 2008–2009. J Med Virol. 2014;86(7):1235–42. doi:https://doi.org/10.1002/jmv.23802.View ArticlePubMedGoogle Scholar
  47. Jin M, Chen J, Zhang XH, Zhang M, Li HY, Cheng WX, Liu N, Tan M, Jiang T, Duan ZJ. Genetic diversity of noroviruses in Chinese adults: potential recombination hotspots and GII-4/Den Haag-specific mutations at a putative epitope. Infect Genet Evol. 2011;11(7):1716–26. doi:https://doi.org/10.1016/j.meegid.2011.07.005.View ArticlePubMedGoogle Scholar
  48. Thathaisong U, Worapong J, Mungthin M, Tan-Ariya P, Viputtigul K, Sudatis A, Noonai A, Leelayoova S. Blastocystis isolates from a pig and a horse are closely related to Blastocystis hominis. J Clin Microbiol. 2003;41(3):967–75.View ArticlePubMedPubMed CentralGoogle Scholar
  49. Tian LG, Chen JX, Wang TP, Cheng GJ, Steinmann P, Wang FF, Cai YC, Yin XM, Guo J, Zhou L, et al. Co-infection of HIV and intestinal parasites in rural area of China. Parasites Vectors. 2012;5:36. doi:https://doi.org/10.1186/1756-3305-5-36.View ArticlePubMedPubMed CentralGoogle Scholar
  50. Wang KX, Li CP, Wang J, Cui YB. Epidemiological survey of Blastocystis hominis in Huainan City, Anhui Province, China. World J Gastroenterol. 2002;8(5):928–32.View ArticlePubMedPubMed CentralGoogle Scholar
  51. Clark CG, van der Giezen M, Alfellani MA, Stensvold CR. Recent developments in Blastocystis research. Adv Parasitol. 2013;82:1–32. doi:https://doi.org/10.1016/B978-0-12-407706-5.00001-0.View ArticlePubMedGoogle Scholar
  52. Kotloff KL, Nataro JP, Blackwelder WC, Nasrin D, Farag TH, Panchalingam S, Wu Y, Sow SO, Sur D, Breiman RF, et al. Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case–control study. Lancet. 2013;382(9888):209–22. doi:https://doi.org/10.1016/S0140-6736(13)60844-2.View ArticlePubMedGoogle Scholar
  53. Li LL, Liu N, Humphries EM, Yu JM, Li S, Lindsay BR, Stine OC, Duan ZJ. Aetiology of diarrhoeal disease and evaluation of viral-bacterial coinfection in children under 5 years old in China: a matched case–control study. Clin Microbiol Infect. 2016;22(4):381.e9–16. doi:https://doi.org/10.1016/j.cmi.2015.12.018.View ArticleGoogle Scholar
  54. Valentini D, Vittucci AC, Grandin A, Tozzi AE, Russo C, Onori M, Menichella D, Bartuli A, Villani A. Coinfection in acute gastroenteritis predicts a more severe clinical course in children. Eur J Clin Microbiol Infect Dis. 2013;32(7):909–15. doi:https://doi.org/10.1007/s10096-013-1825-9.View ArticlePubMedGoogle Scholar
  55. Seabloom EW, Borer ET, Gross K, Kendig AE, Lacroix C, Mitchell CE, Mordecai EA, Power AG. The community ecology of pathogens: coinfection, coexistence and community composition. Ecol Lett. 2015;18(4):401–15. doi:https://doi.org/10.1111/ele.12418.View ArticlePubMedGoogle Scholar
  56. Zhang SX, Li L, Yin JW, Jin M, Kong XY, Pang LL, Zhou YK, Tian LG, Chen JX, Zhou XN. Emergence of human caliciviruses among diarrhea cases in southwest China. BMC Infect Dis. 2016;16(1):511. doi:https://doi.org/10.1186/s12879-016-1831-5 View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s) 2016