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  • Review
  • Open Access

Prevalence of Cryptosporidium, microsporidia and Isospora infection in HIV-infected people: a global systematic review and meta-analysis

Parasites & Vectors201811:28

https://doi.org/10.1186/s13071-017-2558-x

  • Received: 1 August 2017
  • Accepted: 27 November 2017
  • Published:

Abstract

Background

Diarrhea caused by opportunistic intestinal protozoa is a common problem in HIV infection. We aimed to establish the prevalence of Cryptosporidium, misrosporidia, and Isospora in HIV-infected people using a systematic review and meta-analysis, which is central to developing public policy and clinical services.

Methods

We searched PubMed, ScienceDirect, Google Scholar, Embase, Chinese Web of Knowledge, Wanfang, and Chongqing VIP databases for studies reporting Cryptosporidium, microsporidia, or Isospora infection in HIV-infected people. We extracted the numbers of people with HIV and protozoa infection, and estimated the pooled prevalence of parasite infection by a random effects model.

Results

Our research identified 131 studies that reported Cryptosporidium, microsporidia, and Isospora infection in HIV-infected people. We estimated the pooled prevalence to be 14.0% (3283/43,218; 95% CI: 13.0–15.0%) for Cryptosporidium, 11.8% (1090/18,006; 95% CI: 10.1–13.4%) for microsporidia, and 2.5% (788/105,922; 95% CI: 2.1–2.9%) for Isospora. A low prevalence of microsporidia and Isospora infection was found in high-income countries, and a high prevalence of Cryptosporidium and Isospora infection was found in sub-Saharan Africa. We also detected a high prevalence of Cryptosporidium, microsporidia, and Isospora infection in patients with diarrhea. Sensitivity analysis showed that three studies significantly affect the prevalence of Isospora, which was adjusted to 5.0% (469/8570; 95% CI: 4.1–5.9%) by excluding these studies.

Conclusions

Our findings suggest that HIV-infected people have a high prevalence of Cryptosporidium, microsporidia, and Isospora infection in low-income countries and patients with diarrhea, especially in sub-Saharan Africa, reinforcing the importance of routine surveillance for opportunistic intestinal protozoa in HIV-infected people.

Keywords

  • HIV
  • Cryptosporidium
  • Microsporidia
  • Isospora
  • Meta-analysis

Background

Despite the advance of antiretroviral therapy (ART), diarrhea is still a common problem of HIV infection and contributes to the reduced life quality and survival of HIV patients [1, 2]. It is estimated that diarrhea occurs in roughly 90% HIV/AIDS patients in developing countries, and 30–60% in developed countries [3]. Opportunistic pathogens that cause diarrhea in HIV-infected people include protozoa, fungi, viruses, and bacteria [4]. Several protozoan species belonging to Cryptosporidium, microsporidia and Isospora, are among the most common causative pathogens responsible for significant morbidity and mortality in HIV patients [5].

With a worldwide distribution of Cryptosporidium, C. parvum and C. hominis are the most common species detected in humans, though other species, including C. meleagridis, C. felis and C. canis, have also been reported [6]. Despite the use of ART in many countries of the world, the infection rates of Cryptosporidium in HIV patients are still high, accounting for up to a third of diarrhea cases in HIV patients [7].

Microsporidia are obligate intracellular eukaryotic pathogens, which are phylogenetically related to fungi, and have been considered as opportunistic infections in both developed and developing countries, especially in HIV patients with a CD4 cell count below 100 cells/μl [8]. Of the 15 species of microsporidia that infect humans, Enterocytozoon bieneusi and Encephalitozoon intestinalis can cause gastrointestinal diseases, with E. bieneusi being the more commonly identified species in HIV-infected people [9].

Isospora belli is the only species of the genus Isospora, and is frequently found in HIV-infected people of tropical and subtropical regions, accounting for up to 20% of diarrhea cases in AIDS patients [7]. The species can cause acute self-limiting diarrhea in immunocompetent individuals, but in severely immunocompromised patients, this parasite can cause severe chronic diarrhea which may result in a wasting syndrome, or even the death of AIDS patients [10].

The opportunistic parasites Cryptosporidium spp., microsporidians and Isospora spp. develop in enterocytes, and are excreted via feces and transmitted through the fecal-oral route via ingestion of contaminated water or food, or direct contact with infected animals or humans [11]. HIV-infected people are more likely to develop abrupt, severe, and explosive diarrhea when infected with opportunistic protozoa than immunocompetent individuals. Millions of people are affected by the morbidity caused by these parasites, as there was an estimated 36.7 million people living with HIV in 2015 worldwide [12]. Since there is no reliable or well-defined treatment for the protozoan infections in immunocompromised patients [1], understanding their epidemiology is central in formulating effective control strategies against cryptosporidiosis, microsporidiosis, and isosporiasis in these populations. We undertook a systematic review and meta-analysis to evaluate the worldwide prevalence of Cryptosporidium, microsporidia and Isospora infection in people with HIV.

Methods

Search strategy

We searched PubMed, ScienceDirect, Google Scholar, Embase, Chinese Web of Knowledge, Wanfang, and Chongqing VIP databases for studies reporting Cryptosporidium, microsporidia, or Isospora infection in HIV-infected people from inception to 31 December 2016. The databases were searched using the term “Cryptosporidium”, “cryptosporidiosis”, “microsporidia”, “microsporidiosis”, “Isospora” or “isosporiasis” cross-referenced with “HIV”, “immunodeficiency”, “acquired immune deficiency syndrome”, or “AIDS”, without language restriction. We did our analyses according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [13] (see PRISMA checklist in Additional file 1: Table S1).

Selection criteria

The included studies were required to investigate HIV-infected people and needed to have data that allowed us to calculate the prevalence of Cryptosporidium, microsporidia, and Isospora infection. We excluded studies if they were reviews, animal studies, or repeated studies; if there were no raw data; if the sample size was less than 20; or if the diagnostic methods of parasite infection were unclear.

Two independent reviewers (LZ and SL) carefully examined all titles and abstracts identified in the search, and assessed the full text considered potentially relevant. Any disagreements were resolved by discussion with other two authors (Z-DW and H-HL).

Data analysis

Two reviewers (Z-DW and SL) extracted the information about the first author, publication year, country of the study, numbers of HIV-infected people and Cryptosporidium, microsporidia, or Isospora co-infected people, diagnostic methods, study design, and demographic characteristics from each eligible study, and reached a consensus after discussing any controversial finding.

We assessed the quality of the included publications on the basis of criteria derived from the Grading of Recommendations Assessment, Development and Evaluation method [14]. We used a scoring approach to grade quality. Studies were given one point each if they had probability sampling, larger sample sizes of more than 200, and repeated detection. Up to four points could be assigned to each study. We regarded publications with a total score of three or four points to be of high quality, whereas two points represented moderate quality and scores of one or zero represented low quality.

We did a meta-analysis by a random-effects model or fixed-effects model to calculate the pooled prevalence of Cryptosporidium, microsporidia, or Isospora infection using Stata version 12.

The heterogeneity between studies was evaluated using Cochran’s Q and the I2-statistic, which presents the percentage of variation between studies. Due to high heterogeneity (I2 > 50%, P < 0.1), random effects models were used for summary statistics. A potential source of heterogeneity was investigated by subgroup analysis and meta-regression analysis. We examined factors both individually and in multiple-variable models to determine the possible factors that caused heterogeneity in our study. The factors included geographical region by comparison of sub-Sahara Africa with other regions, income level by comparison of low-income countries with others, and patients with diarrhea by comparison of patients with diarrhea with others. We also evaluated the effect of selected studies on the pooled prevalence by excluding single studies sequentially. A study was considered to have no influence if the pooled estimate without it was within the 95% confidence limits of the overall prevalence [15].

Results

Our research identified 2785 records. After initial screening and removal of duplicates, 193 papers were reviewed in full. Of these, 51 articles did not include sufficient data that were required or conform to the criteria, 13 were unavailable for full text, five had duplicate samples, and two included the sample size of less than 20. After an updated search, nine papers were included and we had 131 articles for quality assessment and meta-analysis (Fig. 1).
Fig. 1
Fig. 1

Flowchart of the study selection process

According to our criteria, 51 publications were of high quality with a score of three or four, 48 had a score of two indicating moderate quality, and the remaining 32 were of low quality with a score of zero or one (Tables 1, 2 and 3).
Table 1

Included studies of Cryptosporidium infection in people with HIV listed in order of year published

 

Country

Income level

Patients with diarrhea

No. of patients

Prevalence (%)

Quality score

Western and central Europe and North America

René et al. (1989) [37]

France

High

Mixed

132

21.2

2

Connolly et al. (1990) [53]

UK

High

Yes

33

15.2

1

Brandonisio et al. (1993) [54]

Italy

High

Yes

51

33.3

1

Sorvillo et al. (1994) [41]

USA

High

Mixed

16,953

3.8

2

Colford et al. (1996) [34]

USA

High

Mixed

3564

5.4

3

Mathewson et al. (1998) [42]

USA

High

Yes

83

10.8

2

Matos et al. (1998) [35]

Portugal

High

Yes

465

7.7

3

Brandonisio et al. (1999) [38]

Italy

High

Mixed

154

11.0

3

Cama et al. (2006) [55]

USA

High

Mixed

21

33.3

1

Lagrange-Xelot et al. (2008) [27]

France

High

Mixed

6827

1.3

1

Sub-Saharan Africa

Henry et al. (1986) [32]

DR Congo

Low

Yes

46

8.7

0

Colebunders et al. (1988) [56]

DR Congo

Low

Yes

42

31.0

0

Therizol-Ferly et al. (1989) [57]

Ivory Coast

Middle

Yes

148

6.8

1

Hunter et al. (1992) [58]

Zambia

Middle

Mixed

90

2.2

2

Assoumou et al. (1993) [59]

Ivory Coast

Middle

Mixed

217

8.8

1

Dieng et al. (1994) [60]

Senegal

Low

Yes

72

13.9

1

Chintu et al. (1995) [61]

Zambia

Middle

Yes

44

13.6

2

Mwachari et al. (1998) [62]

Kenya

Middle

Yes

75

17.3

2

Fisseha et al. (1999) [63]

Ethiopia

Low

Mixed

190

20.0

2

Gumbo et al. (1999) [31]

Zimbabwe

Low

Yes

82

8.5

2

Cegielski et al. (1999) [64]

Tanzania

Low

Yes

86

7.0

2

Lebbad et al. (2001) [65]

Guinea-Bissau

Low

Yes

37

21.6

2

Nwokediuko et al. (2002) [66]

Nigeria

Middle

Yes

161

0.0

1

Adjei et al. (2003) [67]

Ghana

Middle

Yes

21

28.6

2

Tumwine et al. (2005) [28]

Uganda

Low

Yes

91

73.6

2

Tadesse et al. (2005) [68]

Ethiopia

Low

Yes

70

28.6

1

Sarfati et al. (2006) [69]

Cameroon

Middle

Mixed

154

9.7

3

Adesiji et al. (2007) [29]

Nigeria

Middle

Yes

100

79.0

3

Mariam et al. (2008) [70]

Ethiopia

Low

Mixed

109

7.3

2

Blanco et al. (2009) [71]

Equatorial Guinea

Middle

na

171

18.1

3

Cooke et al. (2009) [72]

South Africa

Middle

Mixed

26

7.7

0

Babatunde et al. (2010) [73]

Nigeria

Middle

Mixed

90

32.2

1

Alemu et al. (2011) [74]

Ethiopia

Low

Mixed

188

43.6

1

Bartelt et al. (2011) [30]

South Africa

Middle

na

193

75.6

1

Roka et al. (2012) [75]

Equatorial Guinea

Middle

Mixed

260

9.2

4

Wumba et al. (2012) [76]

DR Congo

Low

Mixed

242

5.4

4

Nwuba et al. (2012) [33]

Nigeria

Middle

Mixed

202

30.7

3

Girma et al. (2014) [77]

Ethiopia

Low

Mixed

268

34.3

3

Samie et al. (2014) [78]

South Africa

Middle

Mixed

151

26.5

2

Vouking et al. (2014) [79]

Cameroon

Middle

Mixed

207

7.2

3

Bissong et al. (2015) [80]

Cameroon

Middle

Mixed

200

7.0

3

Kiros et al. (2015) [81]

Ethiopia

Low

Mixed

399

5.8

3

Nsagha et al. (2016) [39]

Cameroon

Middle

Mixed

300

44.0

4

Shimelis et al. (2016) [3]

Ethiopia

Low

Mixed

491

13.2

3

Ojuromi et al. (2016) [82]

Nigeria

Middle

Mixed

90

4.4

3

Asia and the Pacific

Kamel et al. (1994) [83]

Malaysia

Middle

Mixed

100

23.0

0

Moolasart et al. (1995) [84]

Thailand

Middle

Yes

250

8.8

2

Anand et al. (1996) [85]

India

Middle

Mixed

200

35.0

1

Punpoowong et al. (1998) [86]

Thailand

Middle

Yes

22

9.1

0

Wanachiwanawin et al. (1999) [87]

Thailand

Middle

Yes

91

25.3

2

Prasad et al. (2000) [88]

India

Middle

Mixed

26

11.5

2

Wiwanitkit et al. (2001) [89]

Thailand

Middle

Mixed

60

3.3

1

Chokephaibulkit et al. (2001) [90]

Thailand

Middle

Yes

82

6.1

2

Waywa et al. (2001) [91]

Thailand

Middle

Yes

288

19.1

3

Kumar et al. (2002) [92]

India

Middle

Mixed

100

14.0

2

Mohandas et al. (2002) [93]

India

Middle

Mixed

120

10.8

3

Lim et al. (2005) [94]

Malaysia

Middle

Mixed

66

3.0

1

Guk et al. (2005) [95]

South Korea

High

Mixed

67

10.4

1

Chhin et al. (2006) [96]

Cambodia

Middle

Yes

80

45.0

3

Dwivedi (2007) [48]

India

Middle

Mixed

75

33.3

2

Ramakrishnan et al. (2007) [97]

India

Middle

Yes

80

28.8

2

Qu et al. (2007) [19]

China

Middle

Yes

141

3.5

0

Stark et al. (2007) [98]

Australia

High

Yes

618

2.3

4

Saldanha et al. (2008) [99]

India

Middle

na

307

17.3

1

Jayalakshmi et al. (2008) [43]

India

Middle

Yes

89

12.4

2

Viriyavejakul et al. (2009) [100]

Thailand

Middle

Mixed

64

20.3

2

Saksirisampant et al. (2009) [101]

Thailand

Middle

Mixed

90

34.4

1

Kulkarni et al. (2009) [44]

India

Middle

Yes

137

11.7

1

Guo et al. (2011) [20]

China

Middle

Yes

149

16.1

2

Tian et al. (2012) [102]

China

Middle

na

302

8.3

4

Tian et al. (2012) [22]

China

Middle

Mixed

46

13.0

3

Li et al. (2012) [21]

China

Middle

Yes

67

6.0

2

Wang et al. (2012) [23]

China

Middle

Yes

253

12.6

3

Sherchan et al. (2012) [103]

Nepal

Low

Mixed

146

2.7

3

Wang et al. (2013) [9]

China

Middle

Mixed

673

1.5

4

Mehta et al. (2013) [104]

India

Middle

Mixed

100

2.0

3

Vyas et al. (2013) [105]

India

Middle

Yes

75

14.7

2

Gupta et al. (2013) [45]

India

Middle

Mixed

100

4.0

2

Baragundi Mahesh et al. (2013) [106]

India

Middle

Mixed

75

18.7

2

Paboriboune et al. (2014) [107]

Laos

Middle

Mixed

137

6.6

3

Jain et al. (2014) [108]

India

Middle

Mixed

250

20.8

2

Pang et al. (2015) [16]

China

Middle

na

450

17.3

3

Angal et al. (2015) [109]

Malaysia

Middle

Mixed

131

3.8

3

Xie et al. (2015) [17]

China

Middle

Mixed

152

13.2

0

Khalil et al. (2015) [110]

India

Middle

Mixed

200

7.5

3

Asma et al. (2015) [111]

Malaysia

Middle

Mixed

346

12.4

4

Kaniyarakkal et al. (2016) [112]

India

Middle

Mixed

200

2.5

2

Mitra et al. (2016) [113]

India

Middle

Mixed

194

29.4

2

Shah et al. (2016) [114]

India

Middle

Mixed

45

13.3

2

Wang et al. (2016) [18]

China

Middle

Mixed

285

0.7

4

Latin America and the Caribbean

Chacin-Bonilla et al. (1992) [115]

Venezuela

High

Mixed

29

41.4

1

Escobedo et al. (1999) [116]

Cuba

Middle

Mixed

67

11.9

2

Florez et al. (2003) [117]

Colombia

Middle

Mixed

115

10.4

3

Ribeiro et al. (2004) [118]

Brazil

Middle

Mixed

75

9.3

2

Chacin et al. (2006) [119]

Venezuela

High

Yes

103

25.2

2

Goncalves et al. (2009) [120]

Brazil

Middle

Mixed

100

9.0

2

Cardoso et al. (2011) [121]

Brazil

Middle

Mixed

500

0.2

3

Velasco et al. (2011) [122]

Colombia

Middle

Mixed

131

29.0

2

Guimarães et al. (2012) [123]

Brazil

Middle

Mixed

93

2.2

1

Assis et al. (2013) [124]

Brazil

Middle

Mixed

59

10.2

2

Middle East and North Africa

Zali et al. (2004) [125]

Iran

Middle

Mixed

206

1.5

2

Yosefi et al. (2012) [126]

Iran

Middle

Mixed

60

8.3

2

Agholi et al. (2013) [127]

Iran

Middle

Mixed

356

9.6

3

Salehi Sangani et al. (2016) [128]

Iran

Middle

Mixed

80

1.3

2

Eastern Europe and central Asia

Brannan et al. (1996) [129]

Romania

Middle

Mixed

73

78.1

3

Kucervoa et al. (2011) [130]

Russia

Middle

na

46

41.3

2

Abbreviations: Yes, patients with diarrhea; Mixed, including patients with or without diarrhea; na, not applicable (parameter not provided)

Table 2

Included studies of microsporidia infection in people with HIV listed in order of year published

 

Country

Income level

Patients with diarrhea

No. of patients

Prevalence (%)

Quality score

Western and central Europe and North America

Weber et al. (1992) [131]

USA

High

Mixed

134

4.5

2

Kotler et al. (1994) [132]

USA

High

Mixed

194

28.9

3

Anwar-Bruni et al. (1996) [36]

USA

High

Mixed

371

5.9

4

Coyle et al. (1996) [133]

USA

High

Mixed

111

27.9

3

Mathewson et al. (1998) [42]

USA

High

Yes

83

6.0

2

Brandonisio et al. (1999) [38]

Italy

High

Mixed

154

4.5

3

Ferreira et al. (2001) [134]

Portugal

High

Yes

215

42..8

4

Lagrange-Xelot et al. (2008) [27]

France

High

Mixed

6827

0.8

1

Sub-Saharan Africa

van Gool et al. (1995) [135]

Zimbabwe

Low

Yes

129

10.1

2

Maiga et al. (1997) [24]

Mali

Low

Mixed

77

32.5

1

Mwachari et al. (1998) [62]

Kenya

Middle

Yes

36

2.8

2

Cegielski et al. (1999) [64]

Tanzania

Low

Yes

86

3.5

2

Gumbo et al. (1999) [31]

Zimbabwe

Low

Yes

55

50.9

2

Lebbad et al. (2001) [65]

Guinea-Bissau

Low

Yes

37

8.1

2

Endeshaw et al. (2005) [136]

Ethiopia

Low

Yes

80

22.5

1

Tumwine et al. (2005) [28]

Uganda

Low

Yes

91

76.9

2

Endeshaw et al. (2006) [137]

Ethiopia

Low

Yes

214

18.2

3

Sarfati et al. (2006) [69]

Cameroon

Middle

Mixed

154

5.2

3

Breton et al. (2007) [138]

Gabon

Middle

na

822

3.0

4

Breton et al. (2007) [138]

Cameroon

Middle

na

758

2.9

4

Akinbo et al. (2012) [139]

Nigeria

Middle

Mixed

463

16.6

3

Wumba et al. (2012) [76]

DR Congo

Low

Mixed

242

8.3

4

Bissong et al. (2015) [80]

Cameroon

Middle

Mixed

200

2.0

3

Nsagha et al. (2016) [39]

Cameroon

Middle

Mixed

300

21.3

4

Ojuromi et al. (2016) [82]

Nigeria

Middle

Mixed

90

5.6

3

Asia and the Pacific

Punpoowong et al. (1998) [86]

Thailand

Middle

Yes

22

27.3

0

Wanachiwanawin et al. (1998) [140]

Thailand

Middle

Yes

66

33.3

3

Wanachiwanawin et al. (1999) [87]

Thailand

Middle

Yes

91

28.6

2

Chokephaibulkit et al. (2001) [90]

Thailand

Middle

Yes

82

19.5

2

Wiwanitkit et al. (2001) [89]

Thailand

Middle

Mixed

60

1.7

1

Waywa et al. (2001) [91]

Thailand

Middle

Yes

288

9.7

3

Kumar et al. (2002) [92]

India

Middle

Mixed

150

0.7

2

Wanachiwanawin et al. (2002) [141]

Thailand

Middle

Yes

95

25.3

2

Mohandas et al. (2002) [93]

India

Middle

Mixed

120

2.5

3

Dwivedi et al. (2007) [48]

India

Middle

Mixed

75

6..7

2

Saksirisampant et al. (2009) [101]

Thailand

Middle

Mixed

90

5.6

1

Viriyavejakul et al. (2009) [100]

Thailand

Middle

Mixed

64

81.3

2

Kulkarni et al. (2009) [44]

India

Middle

Yes

137

1.5

1

Wang et al. (2013) [9]

China

Middle

Mixed

683

5.7

4

Xie et al. (2015) [17]

China

Middle

Mixed

152

5.3

0

Khalil et al. (2015) [110]

India

Middle

Mixed

200

2.5

3

Khanduja et al. (2016) [8]

India

Middle

Mixed

222

1.8

4

Mitra et al. (2016) [113]

India

Middle

Mixed

194

2.1

2

Latin America and the Caribbean

Florez et al. (2003) [117]

Colombia

Middle

Mixed

115

3.5

3

Sulaiman et al. (2003) [142]

Peru

Middle

Mixed

2672

3.9

4

Chacin-Bonilla et al. (2006) [119]

Venezuela

High

Mixed

103

13.6

1

Middle East and North Africa

Agholi et al. (2013) [127]

Iran

Middle

Mixed

356

2.2

3

Eastern Europe and central Asia

Kucerova et al. (2011) [130]

Russia

Middle

na

46

13.0

2

Abbreviations: Yes, patients with diarrhea; Mixed, including patients with or without diarrhea; na, not applicable (parameter not provided)

Table 3

Included studies of Isospora infection in people with HIV listed in order of year published

 

Country

Income level

Patients with diarrhea

No of patients

Prevalence (%)

Quality score

Western and central Europe and North America

René et al. (1989) [37]

France

High

Mixed

132

0.8

2

Sorvillo et al. (1995) [25]

USA

High

Mixed

16,351

0.8

2

Mathewson et al. (1998) [42]

USA

High

Yes

83

3.6

2

Brandonisio et al. (1999) [38]

Italy

High

Mixed

154

0.6

3

Guiguet et al. (2007) [143]

France

High

Mixed

74,174

0.2

2

Lagrange-Xelot et al. (2008) [27]

France

High

Mixed

6827

0.4

1

Sub-Saharan Africa

Henry et al. (1986) [32]

DR Congo

Low

Yes

46

19.6

0

Colebunders et al. (1988) [56]

DR Congo

Low

Yes

42

11.9

0

Therizol-Ferly et al. (1989) [57]

Ivory Coast

Middle

Yes

148

16.2

1

Hunter et al. (1992) [58]

Zambia

Middle

Mixed

90

7.8

2

Dieng et al. (1994) [60]

Senegal

Low

Yes

72

15.3

1

Fisseha et al. (1999) [63]

Ethiopia

Low

Mixed

190

1.6

2

Lebbad et al. (2001) [65]

Guinea-Bissau

Low

Yes

37

10.8

2

Keshinro et al. (2003) [26]

Nigeria

Middle

Yes

40

7.5

1

Sarfati et al. (2006) [69]

Cameroon

Middle

Mixed

154

1.9

3

Mariam et al. (2008) [70]

Ethiopia

Low

Mixed

109

1.8

2

Babatunde et al. (2010) [73]

Nigeria

Middle

Mixed

90

11.1

1

Alemu et al. (2011) [74]

Ethiopia

Low

Mixed

188

15.4

1

Wumba et al. (2012) [144]

DR Congo

Low

Mixed

242

2.9

4

Abaver et al. (2012) [145]

Nigeria

Middle

Mixed

480

1.7

3

Nwuba et al. (2012) [33]

Nigeria

Middle

Mixed

202

24.3

3

Vouking et al. (2014) [79]

Cameroon

Middle

Mixed

207

5.8

3

Girma et al. (2014) [77]

Ethiopia

Low

Mixed

268

1.5

3

Bissong et al. (2015) [80]

Cameroon

Middle

Mixed

200

6.5

3

Kiros et al. (2015) [81]

Ethiopia

Low

Mixed

399

1.3

3

Nsagha et al. (2016) [39]

Cameroon

Middle

Mixed

300

4.3

4

Shimelis et al. (2016) [3]

Ethiopia

Low

Mixed

491

2.2

3

Asia and the Pacific

Punpoowong et al. (1998) [86]

Thailand

Middle

Yes

22

4.5

0

Wanachiwanawin et al. (1999) [87]

Thailand

Middle

Yes

91

7.7

2

Mukhopadhya et al. (1999) [146]

India

Middle

Mixed

111

12.6

1

Prasad et al. (2000) [88]

India

Middle

Yes

26

26.9

2

Waywa et al. (2001) [91]

Thailand

Middle

Yes

288

4.5

3

Wiwanitkit et al. (2001) [89]

Thailand

Middle

Mixed

60

5.0

1

Mohandas et al. (2002) [93]

India

Middle

Mixed

120

2.5

3

Kumar et al. (2002) [92]

India

Middle

Mixed

150

9.3

2

Guk et al. (2005) [95]

South Korea

High

Mixed

67

7.5

1

Dwivedi et al. (2007) [48]

India

Middle

Yes

75

2.7

2

Jayalakshmi et al. (2008) [43]

India

Middle

Yes

89

3.4

2

Saksirisampant et al. (2009) [101]

Thailand

Middle

Mixed

90

1.1

1

Kulkarni et al. (2009) [44]

India

Middle

Yes

137

8.0

1

Sherchan et al. (2012) [103]

Nepal

Low

Mixed

146

2.1

3

Baragundi Mahesh et al. (2013) [106]

India

Middle

Mixed

75

9.3

2

Vyas et al. (2013) [105]

India

Middle

Yes

75

12.0

2

Mehta et al. (2013) [104]

India

Middle

Mixed

100

18.0

3

Gupta et al. (2013) [45]

India

Middle

Mixed

100

25.0

2

Jain et al. (2014) [108]

India

Middle

Mixed

250

0.8

2

Paboriboune et al. (2014) [107]

Laos

Middle

Mixed

137

4.4

3

Khalil et al. (2015) [110]

India

Middle

Mixed

200

7.5

3

Kaniyarakkal et al. (2016) [112]

India

Middle

Mixed

200

4.5

2

Mitra et al. (2016) [113]

India

Middle

Mixed

194

14.4

2

Shah et al. (2016) [114]

India

Middle

Mixed

45

20.0

2

Latin America and the Caribbean

Escobedo et al. (1999) [116]

Cuba

Middle

Mixed

67

1.5

2

Moran et al. (2005) [147]

Mexico

Middle

Mixed

203

0.5

3

Cardoso et al. (2011) [121]

Brazil

Middle

Mixed

500

1.2

3

Guimarães et al. (2012) [123]

Brazil

Middle

Mixed

93

1.1

1

Assis et al. (2013) [124]

Brazil

Middle

Mixed

59

6.8

2

Middle East and North Africa

Agholi et al. (2013) [127]

Iran

Middle

Mixed

356

0.6

3

Salehi Sangani et al. (2016) [128]

Iran

Middle

Mixed

80

2.5

2

Abbreviations: Mixed, including patients with or without diarrhea; Yes, patients with diarrhea

One hundred and six studies assessed Cryptosporidium infection in HIV-infected people (Fig. 1, Table 1), including a total of 43,218 HIV-infected patients. These studies were done in 36 countries (Fig. 2), including five countries of western and central Europe and North America, 15 of sub-Saharan Africa, four of Latin America and the Caribbean, two of eastern Europe and central Asia, nine of Asia and the Pacific, and one of Middle East and North Africa. Of these identified studies, 16 were done in low-income countries, 76 were in middle-income countries, and 14 were in high-income countries (Fig. 2). Ninety-eight papers were written in English, and eight in Chinese [1623].
Fig. 2
Fig. 2

Map of Cryptosporidium infection in HIV-infected people worldwide. Pooled percentage prevalence and 95% CI are shown for each country

The prevalence of Cryptosporidium infection ranged between 0 and 78.1% (Fig. 3). Meta-analysis by random-effect model showed that the estimated pooled prevalence of Cryptosporidium infection in people with HIV infection was 14.0% (3283/43,218; 95% CI: 13.0–15.0%) overall, 21.1% (1105/5315; 95% CI: 16.1–21.1%) in sub-Saharan Africa, 7.3% (1042/28,283; 95% CI: 5.4–9.2%) in western and central Europe and North America, 12.6% (896/7529; 95% CI: 10.5–14.7%) in Asia and the Pacific, 13.0% (121/1272; 95% CI: 7.3–18.7%) in Latin America and the Caribbean, 4.7% (43/702; 95% CI: 0.5–8.8%) in the Middle East and North Africa, and 60.1% (76/119; 95% CI: 24.1–96.1%) in eastern Europe and central Asia. Only four studies were done in Middle East and North Africa, and two in eastern Europe and central Asia, where the prevalence of Cryptosporidium infection in HIV-infected people was very poorly recorded.
Fig. 3
Fig. 3

Random-effect meta-analysis of Cryptosporidium infection in HIV-infected people

With a substantial heterogeneity (I2 = 97.6%, P < 0.0001; Table 4), meta-regression analyses showed that geographical distribution (P = 0.039) and patients with diarrhea (P = 0.009) might be sources of heterogeneity, whereas we detected no significant differences in income levels (P = 0.328). Subgroup analysis showed the pooled prevalence of Cryptosporidium infection in HIV-infected people was significantly lower in western and central Europe and North America than in sub-Saharan Africa (OR 0.73, 95% CI: 0.54–0.99, P = 0.044), and higher in patients with diarrhea (OR 1.21, 95% CI: 1.00–1.46, P = 0.047).
Table 4

Pooled prevalence of Cryptosporidium infection in HIV-infected patients

 

No. of studies

No. of HIV-infected patients

No. of patients with Cryptosporidium co-infection

Prevalence of Cryptosporidium co-infection (95% CI) (%)

Heterogeneity

Univariate meta-regression

P-value

I2 (%)

Coefficient (95% CI) (%)

P-value

Region

      

0.20 (0.01–0.38)

0.039

 Western and central Europe and North America

10

28,283

1042

7.3 (5.4–9.2)

< 0.0001

97.0

  

 Sub-Saharan Africa

35

5313

1105

21.1 (16.1–26.1)

< 0.0001

98.5

  

 Asia and the Pacific

45

7529

896

12.6 (10.5–14.7)

< 0.0001

94.1

  

 Latin America and the Caribbean

10

1272

121

13.0 (7.3–18.7)

< 0.0001

94.0

  

 Middle East and North Africa

4

702

43

4.7 (0.5–8.8)

< 0.0001

88.1

  

 Eastern Europe and central Asia

2

119

76

60.1 (24.1–96.1)

< 0.0001

94.4

  

Income level

    

< 0.0001

 

0.12 (-0.12–0.37)

0.328

 Low income

16

2559

460

19.7 (13.3–26.1)

< 0.0001

96.6

  

 Middle income

76

11,559

1722

14.8 (13.3–16.4)

< 0.0001

97.5

  

 High income

14

29,100

1101

7.7 (6.0–9.5)

< 0.0001

96.2

  

Patients with diarrhea

    

< 0.0001

 

0.19 (0.05–0.33)

0.009

 Yes

34

4232

625

18.2 (14.6–21.7)

< 0.0001

97.3

  

 Mixed

66

37,517

2306

11.8 (10.6–13.0)

< 0.0001

96.7

  

 na

6

1469

352

29.4 (12.4–46.4)

< 0.0001

98.7

  

Total

106

43,218

3283

14.0 (13.0–15.0)

< 0.0001

97.6

  

Abbreviations: Yes, patients with diarrhea; Mixed, including patients with or without diarrhea; na, not applicable (parameter not provided)

Forty-seven studies reported prevalence of microsporidia (Fig. 1, Table 2), including a total of 18,006 HIV-infected people tested for microsporidia infection. The included studies were conducted in 23 countries (Fig. 4), including 11 countries of sub-Saharan Africa, four of western and central Europe and North America, three of Asia and the Pacific, three of Latin America and the Caribbean, one each of Middle East and North Africa and eastern Europe and central Asia. Of the identified studies, 9 were done in low-income countries, 30 were in middle-income countries, and 9 were in high-income countries (Fig. 4). Forty-five papers were written in English, one each in Chinese and French [17, 24].
Fig. 4
Fig. 4

Map of microsporidia infection in HIV-infected people worldwide. Pooled percentage prevalence and 95% CI are shown for each country

The prevalence of microsporidia infection ranged between 0.7–81.3% (Additional file 2: Figure S1). Meta-analysis by random-effect model indicated that the estimated pooled prevalence of microsporidia infection in people with HIV infection was 11.8% (1090/18,006; 95% CI: 10.1–13.4%) overall, 15.4% (425/3834; 95% CI: 11.1–19.7%) in sub-Saharan Africa, 14.4% (277/8089; 95% CI: 7.8–21.1%) in western and central Europe and North America, 11.7% (251/2791; 95% CI: 8.2–15.1%) in Asia and the Pacific, 5.6% (123/2890; 95% CI: 1.9–9.3%) in Latin America and the Caribbean, 2.2% (8/356; 95% CI: 0.7–3.8%) in the Middle East and North Africa, and 13.0% (6/46; 95% CI: 3.3–22.8%) in eastern Europe and central Asia. Only three studies were done in Latin America and the Caribbean, one each in Middle East and North Africa, and in eastern Europe and central Asia. The prevalence of microsporidia infection in these regions should be interpreted with caution.

Due to the substantial heterogeneity (I2 = 96.7%, P < 0.0001; Table 5), meta-regression analyses indicated that the income level (P = 0.024) and patients with diarrhea (P = 0.004) might be sources of heterogeneity, whereas we detected no significant differences in geographical distribution (P = 0.323). Subgroup analysis showed the pooled prevalence of microsporidia infection in HIV-infected people was significantly higher in low-income countries than in middle-income countries (OR 1.58, 95% CI: 1.08–2.31, P = 0.018), and higher in patients with diarrhea than the control (OR 1.54, 95% CI: 1.14–2.07, P = 0.005).
Table 5

Pooled prevalence of microsporidia infection in HIV-infected patients

 

No. of studies

No. of HIV-infected patients

No. of patients with microsporidia co-infection

Prevalence of microsporidia co-infection (95% CI) (%)

Heterogeneity

Univariate meta-regression

P-value

I2 (%)

Coefficient (95% CI) (%)

P-value

Region

      

0.16 (0.16–0.47)

0.323

 Western and central Europe and North America

8

8089

277

14.4 (7.8–21.1)

< 0.0001

97.6

  

 Sub-Saharan Africa

17

3834

425

15.4 (11.1–19.7)

< 0.0001

96.9

  

 Asia and the Pacific

18

2791

251

11.7 (8.2–15.1)

< 0.0001

95.8

  

 Latin America and the Caribbean

3

2890

123

5.6 (1.9–9.3)

0.017

75.6

  

 Middle East and North Africa

1

356

8

2.2 (0.7–3.8)

  

 Eastern Europe and central Asia

1

46

6

13.0 (3.3–22.8)

  

Income level

      

0.42 (0.06–0.79)

0.024

 Low income

9

1011

219

25.2 (13.0–37.4)

< 0.0001

97.3

  

 Middle income

30

8803

580

8.4 (6.5–10.3)

<0.0001

94.5

  

 High income

9

8192

291

14.4 (8.1–20.6)

< 0.0001

97.4

  

Patients with diarrhea

      

0.44 (0.15–0.73)

0.004

 Yes

17

1807

396

22.2 (14.5–29.9)

< 0.0001

96.9

  

 Mixed

28

14,573

641

8.3 (6.5–10.1)

< 0.0001

96.3

  

 na

3

1626

53

3.2 (1.7–4.6)

0.128

51.3

  

Total

48

18,006

1090

11.8 (10.1–13.4)

< 0.0001

96.7

  

Abbreviations: Yes, patients with diarrhea; Mixed, including patients with or without diarrhea; na, not applicable (parameter not provided)

Fifty-eight studies tested 105,922 HIV-infected patients for Isospora infection (Fig. 1, Table 3). The selected studies were done in 20 countries (Fig. 5), including three countries of western and central Europe and North America, eight of sub-Saharan Africa, five of Asia and the Pacific, three of Latin America and the Caribbean, and one of Middle East and North Africa. No studies were found from eastern Europe and central Asia. Of the identified studies, 12 were done in low-income countries, 39 were in middle-income countries, and seven were in high-income countries (Fig. 5). All the included papers were written in English.
Fig. 5
Fig. 5

Map of Isospora infection in HIV-infected people worldwide. Pooled percentage prevalence and 95% CI are shown for each country

The prevalence of Isospora infection ranged between 0.2–26.9% (Additional file 3: Figure S2). Meta-analysis by random-effect model showed that the estimated pooled prevalence of Isospora infection in people with HIV infection was 2.5% (788/105,922; 95% CI: 2.1–2.9%) overall, 6.1% (232/3995; 95% CI: 4.5–7.7%) in sub-Saharan Africa, 0.5% (324/97,721; 95% CI: 0.2–0.8%) in western and central Europe and North America, 7.1% (215/2848; 95% CI: 5.2–9.0%) in Asia and the Pacific, 1.0% (13/922; 95% CI: 0.3–1.7%) in Latin America and the Caribbean, 0.8% (4/436; 95% CI: 0–2.0%) in the Middle East and North Africa. However, few data were available from Latin America, Middle East and North Africa. Only two studies were conducted in Middle East and North Africa, five were done in Latin America and the Caribbean, showing a poor record of Isospora infection in these regions.

With a substantial heterogeneity (I2 = 89.8%, P < 0.0001; Table 6), meta-regression analyses showed that patients with diarrhea might be sources of heterogeneity (P = 0.005), whereas we detected no significant differences in region distribution (P = 0.143) and income levels (P = 0.806). Subgroup analysis showed that the pooled prevalence of Isospora infection in HIV-infected people was significantly lower in central Europe and North America than in sub-Saharan Africa (OR 0.40, 95% CI: 0.27–0.59) and in Asia and the Pacific (OR 0.37, 95% CI: 0.26–0.54). Additionally, it was significantly higher in low-income countries (OR 1.94, 95% CI: 1.24–3.04, P = 0.005) and middle-income countries (OR 2.08, 95% CI: 1.41–3.07, P < 0.0001) than in high-income countries. We also found that patients with diarrhea had a higher prevalence of Isospora infection (OR 1.53, 95% CI: 1.14–2.06, P = 0.005).
Table 6

Pooled prevalence of Isospora infection in HIV-infected patients

 

No. of studies

No. of HIV-infected patients

No. of patients with Isospora co-infection

Prevalence of Isospora co-infection (95% CI) (%)

Heterogeneity

Univariate meta-regression

P-value

I2 (%)

Coefficient (95% CI) (%)

P-value

Region

      

0.21 (-0.07–0.49)

0.143

 Western and central Europe and North America

6

97,721

324

0.5 (0.2–0.8)

< 0.0001

92.8

  

 Sub-Saharan Africa

21

3995

232

6.1 (4.5–7.7)

< 0.0001

87.0

  

 Asia and the Pacific

24

2848

215

7.1 (5.2–9.0)

< 0.0001

83.4

  

 Latin America and the Caribbean

5

922

13

1.0 (0.3–1.7)

0.349

10.1

  

 Middle East and North Africa

2

436

4

0.8 (0.0–2.0)

0.279

14.7

  

Income level

      

-0.04 (-0.38–0.30)

0.806

 Low income

12

2230

93

3.8 (2.2–5.5)

< 0.0001

91.9

  

 Middle income

39

5904

366

5.8 (4.7–7.0)

< 0.0001

86.9

  

 High income

7

97,788

329

0.5 (0.2–0.9)

< 0.0001

80.0

  

Patients with diarrhea

    

< 0.0001

 

-0.43 (-0.72– -0.13)

0.005

 Yes

15

1271

112

8.3 (5.7–10.9)

< 0.0001

66.1

  

 Mixed

43

104,651

676

2.0 (1.6–2.4)

< 0.0001

90.4

  

Total

58

105,922

788

2.5 (2.1–2.9)

< 0.0001

89.8

  

Abbreviations: Yes, patients with diarrhea; Mixed, including patients with or without diarrhea

We determined the effect of selected studies on the pooled prevalence by excluding single studies sequentially, and found no significant effect of study quality on prevalence of Cryptosporidium and microsporidia infection in HIV-infected people (all P > 0.05), but there was significant effect of study quality on the prevalence of Isospora infection (P = 0.033 and 0.043).

When we excluded the studies by Sorvillo et al. [25], Guiguet et al. [26], and Lagrange-Xelot et al. [27], the pooled prevalence of Isospora infection in HIV-infected people was increased from 2.5% (95% CI: 2.1–2.9%) to 3.0% (95% CI: 2.5–3.5%), 3.3% (95% CI: 2.8–3.8%), and 3.0% (95% CI: 2.5–3.4%), respectively. These findings indicated that the pooled prevalence of Isospora infection in HIV-infected people was substantially influenced by the three studies, and adjusted to 5.0% (469/8570; 95% CI: 4.1–5.9%) by excluding these studies (Additional file 4: Figure S3).

Discussion

Our aim was to estimate the worldwide prevalence of opportunistic intestinal protozoa in people with HIV, showing that Cryptosporidium and microsporidia are the main intestinal protozoa in HIV-infected people, followed by Isospora; their prevalences are usually high in sub-Saharan Africa and in patients with diarrhea, and low in high-income countries. Because of the large proportion of low-income countries and the large number of people with HIV [12], sub-Saharan Africa has a very high burden of Cryptosporidium, microsporidia and Isospora infection, reinforcing the importance of routine testing for opportunistic intestinal protozoa in all HIV-infected people. To our knowledge, this is the first systematic review and meta-analysis of the global prevalence of Cryptosporidium, microsporidia and Isospora infection in HIV-infected people.

Our findings corroborate evidence for a high prevalence of Cryptosporidium, microsporidia and Isospora infection in Africa and a low prevalence in Europe. In HIV-infected people, a high prevalence has been reported in Uganda (73.6%) [28], Nigeria (79.0%) [29], and South Africa (75.6%) [30] for Cryptosporidium infection; in Zimbabwe (50.9%) [31] and Uganda (76.9%) [28] for microsporidia infection; and in DR Congo (19.6%) [32] and Nigeria (24.3%) [33] for Isospora infection. In contrast, a low prevalence has been shown in France (1.3%) [27], USA (5.4%) [34] and Portugal (7.7%) [35] for Cryptosporidium infection; in France (0.8%) [27] and USA (5.9%) [36] for microsporidia infection; and in France (0.8%) [37] and Italy (0.6%) [38] for Isospora infection.

The incidence of opportunistic intestinal protozoa infection varies, relying on sanitation facilities, drinking contaminated water, animal exposure, CD4 T cell count, ART, diagnostic methods [39, 40]. Thus, the prevalence of infection may vary substantially, even within a country or among different populations of the same region. For example, in the USA, the prevalence of Cryptosporidium infection is 3.8% in Los Angeles [41], 5.4% in San Francisco [34] and 10.8% in Houston [42]. Large differences of Isospora infection have also been reported in India, with a prevalence of 3.4% in Coimbatore [43], 8.0% in Pune [44] and 25.0% in New Delhi [45]. There are significant differences between different countries for Cryptosporidium (0–78.1%), microsporidia (0.7–81.3%) and Isospora (0.2–26.9%) infection in HIV-infected people. However, limited country-level surveys of Cryptosporidium, microsporidia and Isospora infection have been undertaken, making it difficult to compare the infections between regions or populations.

The majority of the studies had additional data on opportunistic intestinal protozoa. Due to the variability of data quality and reporting consistency, we only extracted and analyzed the data on diarrhea, and demonstrated it was related to Cryptosporidium (OR: 1.21, 95% CI: 1.01–1.46, P = 0.047), microsporidia (OR 1.53, 95% CI: 1.13–2.07, P = 0.007) and Isospora (OR 1.53, 95% CI: 1.14–2.06, P = 0.005) infection in HIV-infected people in comparison with their controls. Moreover, there were some case-control studies that investigated opportunistic intestinal protozoa infection in people with HIV with and without diarrhea. We analyzed the association of diarrhea with Cryptosporidium, microsporidia and Isospora infection in HIV-infected people. The estimated pooled random effects ORs of Cryptosporidium, microsporidia and Isospora infection in HIV people with diarrhea compared with their controls were 4.09 (95% CI: 2.32–7.20), 4.72 (95% CI: 3.47–6.42), and 4.93 (95% CI: 3.33–7.29), respectively (Additional files 5, 6 and 7: Figures S4, S5 and S6). These findings show that diarrhea is associated with opportunistic intestinal protozoa infection in HIV people. However, other factors seem to increase the likelihood of infection with opportunistic intestinal protozoa, including CD4 T-lymphocyte counts of less than 100 cells/μl [46], ingestion of contaminated drinking water or food [47], exposure to infected pets or animals [48] and unsafe homosexual activity [49].

There are a few limitations of the present meta-analysis, which may affect the results. First, many relevant studies were identified through our literature search, but not all data were available; there is a possibility that some qualified data were missed. Secondly, the majority of the studies were of moderate or low quality, as most of the data resulted from the conventional microscopic diagnostic techniques; these have a sensitivity which is inferior to polymerase chain reaction, ELISA and direct fluorescent-antibody tests. Additionally, most studies examined a single stool specimen, potentially leading to a false negative result. This means that the reported prevalence was possibly underestimated. Thirdly, the included studies were concentrated in Asia (n = 50), sub-Saharan Africa (n = 45), and western and central Europe and North America (n = 17), Latin America and the Caribbean (n = 12), with few studies from Middle East and North Africa (n = 5), and eastern Europe and central Asia (n = 2), and the study quality was variable, emphasizing the need for more robust surveillance of Cryptosporidium, microsporidia and Isospora infection in HIV-infected people in these regions. Fourthly, different species and genotypes of Cryptosporidium and microsporidia may cause different clinical manifestations in HIV-infected people [40, 50]. However, we did not analyze their distribution characteristics as the microscopic diagnostic techniques in most of the selected studies could not identify the species within the genus Cryptosporidium and microsporidians.

To explain the specific causes of heterogeneity, we did univariate meta-regression analyses on various sources including geographical distribution, income level, and patients with diarrhea, and found different main causes of heterogeneity for the three opportunistic protozoa. These may come from geographical distribution (P = 0.039) and patients with diarrhea (P = 0.009) for Crytosporidium infection, from income level (P = 0.024) and patients with diarrhea (P = 0.004) for microsporidia infection, and from patients with diarrhea (P = 0.005) for Isospora infection. Other potential causes of heterogeneity may include publication year, sample size, and detection methods. Unfortunately, we did not analyze them, as there were not enough data available.

Moreover, we did dummy variable analysis on geographical distribution, income level, and patients with diarrhea. The countries in sub-Saharan Africa had a higher prevalence of Cryptosporidium and Isospora infection in HIV-infected patients than those in western and central Europe and North America, and the low-income countries had a higher prevalence of microsporidia and Isospora infection than the middle or high-income countries. These findings support an association between parasite infection and the income level of countries, which could be due to the fact that people in high-income countries have access to safe water and sanitation facilities, which are responsible for the reduced odds of parasite infection.

Conclusions

The results of our global meta-analysis show a heavy burden of Cryptosporidium, microsporidia and Isospora infection in HIV-infected people, especially in low-income countries and sub-Saharan Africa. Thus, routine screening of opportunistic intestinal protozoa should be done, particularly for those who have CD4 T-lymphocyte count less than 100 cells/μl, and early treatment should be administered. This should include a combination of antibiotics of azithromycin, paramomycin and nitazoxanide for Cryptosporidium infection, albendazole for microsporidia infection, and trimethoprim-sulfamethoxazole for Isospora infection [51, 52]. However, antibiotics alone may not necessarily reduce the symptoms associated with opportunistic intestinal protozoa infection [7, 51]. More importantly, it is obligatory to reconstruct the immune system by ART. Additional preventive measures should also emphasize the environmental and personal hygiene, along with the quality of drinking water [47].

Abbreviations

AIDS: 

Acquired immune deficiency syndrome

ART: 

Antiretroviral therapy

CI: 

Confidence interval

HIV: 

Human immunodeficiency virus

OR: 

Odds ratio

PRISMA: 

Preferred reporting items for systematic reviews and meta-analyses

Declarations

Acknowledgements

Not applicable.

Funding

This work was supported, in part, by the National Key Research and Development Program of China (Grant No. 2017YFD0501300), the National Natural Science Foundation of China (Grant No. 31672542), the Fundamental Research Funds of Chinese Academy of Agricultural Sciences (Grant Nos. Y2016JC05 and 1610312017004) and the Agricultural Science and Technology Innovation Program (ASTIP) (Grant No. CAAS-ASTIP-2014-LVRI-03).

Availability of data and materials

All data generated or analyzed in this study are included in this article and its additional files.

Authors’ contributions

QL and X-QZ conceived and designed the study, and critically revised the manuscript. Z-DW and QL conducted the study. H-HL, SL, LZ and Y-KZ collected and analyzed the data. Z-DW and QL wrote the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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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)
State Key Laboratory of Veterinary Etiological Biology, Key Laboratory of Veterinary Parasitology of Gansu Province, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou, Gansu Province, 730046, People’s Republic of China
(2)
Military Veterinary Institute, Key Laboratory of Jilin Province for Zoonosis Prevention and Control, Academy of Military Medical Sciences, Changchun, Jilin Province, 130122, People’s Republic of China
(3)
College of Animal Science and Technology, Jilin Agricultural University, Changchun, Jilin Province, 130188, People’s Republic of China

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