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. 2018 Jan 9;11:28. doi: 10.1186/s13071-017-2558-x

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

Ze-Dong Wang 1, Quan Liu 2,3,✉, Huan-Huan Liu 3, Shuang Li 3, Li Zhang 3, Yong-Kun Zhao 2, Xing-Quan Zhu 1,✉
PMCID: PMC5759777  PMID: 29316950

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.

Electronic supplementary material

The online version of this article (10.1186/s13071-017-2558-x) contains supplementary material, which is available to authorized users.

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

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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
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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
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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
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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 [16–23].

Fig. 2.

Fig. 2

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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

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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
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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

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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
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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

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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
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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].

Additional files

Additional file 1: Table S1. (69.5KB, doc)

Checklist of items to include when reporting a meta-analysis. (DOC 69 kb)

Additional file 2: Figure S1. (268.1KB, pdf)

Random-effect meta-analysis of microsporidia infection in HIV-infected people. (PDF 267 kb)

Additional file 3: Figure S2. (345.8KB, pdf)

Random-effect meta-analysis of Isospora infection in HIV-infected people. (PDF 345 kb)

Additional file 4: Figure S3. (343.4KB, pdf)

Random-effect meta-analysis of Isospora infection in HIV-infected people when the three studies affecting the prevalence of Isospora were excluded. (PDF 344 kb)

Additional file 5: Figure S4. (227.2KB, pdf)

Random-effect meta-analysis of the association of diarrhea with Cryptosporidium infection in HIV-infected people. (PDF 227 kb)

Additional file 6: Figure S5. (170.1KB, pdf)

Fixed-effect meta-analysis of the association of diarrhea with microsporidia infection in HIV-infected people. (PDF 170 kb)

Additional file 7: Figure S6. (217.6KB, pdf)

Fixed-effect meta-analysis of the association of diarrhea with Isospora infection in HIV-infected people. (PDF 217 kb)

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.

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

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

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Footnotes

Electronic supplementary material

The online version of this article (10.1186/s13071-017-2558-x) contains supplementary material, which is available to authorized users.

Contributor Information

Ze-Dong Wang, Email: 851077608@qq.com.

Quan Liu, Email: liuquan1973@hotmail.com.

Huan-Huan Liu, Email: lhh1211291518@163.com.

Shuang Li, Email: 18704493241@163.com.

Li Zhang, Email: 913710993@qq.com.

Yong-Kun Zhao, Email: zhaoyongkun1976@126.com.

Xing-Quan Zhu, Email: xingquanzhu1@hotmail.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file 1: Table S1. (69.5KB, doc)

Checklist of items to include when reporting a meta-analysis. (DOC 69 kb)

Additional file 2: Figure S1. (268.1KB, pdf)

Random-effect meta-analysis of microsporidia infection in HIV-infected people. (PDF 267 kb)

Additional file 3: Figure S2. (345.8KB, pdf)

Random-effect meta-analysis of Isospora infection in HIV-infected people. (PDF 345 kb)

Additional file 4: Figure S3. (343.4KB, pdf)

Random-effect meta-analysis of Isospora infection in HIV-infected people when the three studies affecting the prevalence of Isospora were excluded. (PDF 344 kb)

Additional file 5: Figure S4. (227.2KB, pdf)

Random-effect meta-analysis of the association of diarrhea with Cryptosporidium infection in HIV-infected people. (PDF 227 kb)

Additional file 6: Figure S5. (170.1KB, pdf)

Fixed-effect meta-analysis of the association of diarrhea with microsporidia infection in HIV-infected people. (PDF 170 kb)

Additional file 7: Figure S6. (217.6KB, pdf)

Fixed-effect meta-analysis of the association of diarrhea with Isospora infection in HIV-infected people. (PDF 217 kb)

Data Availability Statement

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

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