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. 2021 Jan 12;115(1):7–20. doi: 10.1080/20477724.2020.1851922

Prevalence of strongyloidiasis in the general population of the world: a systematic review and meta-analysis

Aida Vafae Eslahi b, Milad Badri c,✉,*, Kareem Hatam Nahavandi d, Elham Houshmand e, Sahar Dalvand f, Seyed Mohammad Riahi g, Morteza Ghanbari Johkool c, Negar Asadi b,h, Seyed Abedin Hoseini Ahangari i, Ali Taghipour a, Mohammad Zibaei j,k, Shahram Khademvatan b,h,✉
PMCID: PMC7850468  PMID: 33433291

ABSTRACT

Strongyloides stercoralis is a neglected soil-transmitted helminth affects approximately 100-370 million people globally. The life cycle is unusual as only larvae can be found in stool specimens. Thecurrent review and meta-analysis represented the distribution of strongyloidiasis in general population of the world based on published papers. Five English databases (Science Direct, Scopus, PubMed, Web of Science, and Google Scholar(were explored for literature published before October 2019.Altogether 235 studies (862243 participants) was eligible. Regarding diagnostic method, the overall prevalence for studies performed microscopic, culture, immunological and molecular method was 1.47% (95% CI = 1.56%), 10.08% (95% CI = 8.99% - 11.16%), 23.88% (95% CI =  20.82% - 26.94%) and 9.3% (95% CI  =  7.2% - 11.3%), respectively. Based on microscopic methods, the highest prevalence was related to the Western Pacific region [9.47% (95% CI =  8.55% - 10.39%)]. According to the culture method, Western Pacific region [21.36% (95% CI  =  16.32% - 26.39%)] had the highest estimated pooled prevalence. In immunological studies, Eastern Mediterranean Region [40.72% (95% CI  =  36.74% - 44.70%)] had the highest seroprevalence.Also in molecular surveys, the highest prevalence was related to the African region [19.72% (95% CI  =  16.71% - 22.73%)]. The current study indicated that strongyloidiasis is still considered a health problem in many parts of the world. Thus a comprehensive control program and improvement of public health sectors are required.

KEYWORDS: Prevalence, strongyloides stercoralis, Worldwide, Soil transmitted helminths (STHs), General population, Neglected tropical disease (NTD)

Introduction

Soil-transmitted helminths (STHs) are a major health problem in tropical and subtropical regions. According to the World Health Organization (WHO) reports, almost 1.5 billion people are exposed to these parasites [1]. The most important STHs are Ascaris lumbricoides, hookworms, and Trichuris trichiura [2]. Strongyloides stercoralis is a STH which affects approximately 100–370 million people around the world and is considered as a cause of the neglected tropical disease (NTD) [3,4]. Strongyloidiasis symptoms are often mild to severe diarrhea in immunocompetent persons and it is accompanied by eosinophilia in 60% of the cases [5]. In heavy infections due to the high burden of parasites, it leads to hyperinfection syndrome with different signs such as serpiginous urticarial rash, Loeffler’s syndrome, and gastrointestinal complications (2% of the cases especially in immunocompromised patients), as well as corticosteroid consumers, diabetes mellitus, alcoholism, and chronic renal failure [6–8]. During hyperinfection, some intestinal commensal bacteria increase the severity of the syndrome up to 60% [9]. Disseminated strongyloidiasis often happens after hyperinfection syndrome in immunodeficient persons, such as Human T lymphotropic virus type 1 (HTLV-1) positive patients. In malignant cases, it becomes ectopic in various parts of the body such as lymph nodes, central nervous system, pancreas, kidneys, ovaries, and skeletal muscles. In ectopic infection, the mortality rate is 100% without treatment [10–13]. The life cycle of S. stercoralis is unusual as rhabditiform larvae can be found in stool specimens. In direct development, first-stage larvae (rhabditiform) develop to the infective stage larvae (filariform) in soil. In the free-living cycle, after mating, females produce eggs from which first-stage larvae (rhabditiform) hatch and change to the infective stage larvae (filariform) after two molts [14,15]. The diagnostic tests consist of fecal-based or alternative methods such as immunological and molecular techniques. Most of the cases of strongyloidiasis are asymptomatic and under-diagnosed and the microscopic diagnostic methods have low sensitivity (in the case of chronic infection with low numbers of larvae). Some of them, such as Baermann or Agar plate culture (APC), are time-consuming. Immunological methods are helpful especially for seroepidemiological research or diagnosis of specific individual records [16]. The first line of treatment in S. stercoralis is ivermectin, which is more effective than other drugs [17]. Regarding the distribution of this parasitic infection and according to the reports worldwide, the present review and meta-analysis aim to determine the prevalence of this infection in the general population across the world.

Materials and methods

Search strategy

Five databases in English (Science Direct, Scopus, PubMed, Web of Science, and Google Scholar) were explored for articles with regard to the prevalence of S. stercoralis in the global general population without time limitation before October 2019. The search terms were ‘Prevalence,’ ‘Strongyloides stercoralis,’ Strongyloidiasis,’ ‘Human,’ ‘General population,’ ‘Soil-transmitted helminths,’ ‘Intestinal parasites,’ and ‘Worldwide’ alone or in combination using OR and AND operators.

Exclusion and inclusion criteria

A comprehensive systematic search was conducted and two independent reviewers evaluated the papers and separate eligible articles according to their titles and abstracts. Those studies that met the following inclusion criteria were selected: (a) studies estimated the prevalence of strongyloidiasis in the general population of the world, and (b) peer-reviewed original observational articles with cross-sectional, cohort, prospective, and retrospective design. The exclusion criteria include: (a) review or systematic reviews, case series, case report, letter to editor, fact sheet, opinion, preprint, and (b) studies without full-text accessibility. In order to prevent missing data, all references of full-text-published literature were checked precisely. We used discussion and consensus to resolve any disagreements. For each included paper, two authors extracted the following specified variables in an excel spreadsheet: year of publication, study area (country and related continent), WHO regions (Western Pacific region, Eastern Mediterranean region, South-East Asia region, African region, Region of the Americas and the European region), latitude and longitude, Human Development Index (HDI), Gini index, study design (cross-sectional), sample type (feces or serum), patients group (hospital patients, refugees, and immigrants), patient position (rural or urban), educational level, number of examined individuals, diagnostic technique (microscopic, culture, immunological, molecular), and number of infected individuals. The PRISMA protocol (Preferred reporting items for systematic reviews and meta-analysis) was used to report the data.

The level of HDI for each country was obtained from the United Nations Development Program (UNDP) [18]. The Gini index was taken from the World Bank Data with the purpose of measuring of the distribution of income in a population [19].

Statistical approach and meta-analyses

The prevalence and the 95% confidence intervals (CI) of strongyloidiasis were estimated for all of the eligible studies using random effects model for each method. Also, data adjusted by Freeman-Tukey double arcsine transformation and Clopper-Pearson method was used to estimate their 95% CIs [20]. The meta-analysis provided a forest plot representing the pooled prevalence and related 95% CIs of each study along with summary measures. Cochran’s Q and I2 statistics (I2 values of 25%, 50%, and 75% were regarded as low, moderate and high heterogeneity, accordingly) were used to evaluate the heterogeneity. Meta-regression was used to examine the association between publication year of studies, sample size, HDI, Gini, latitude and longitude of studies with the prevalence of each method. Sensitivity analysis was applied to assess the impact of each study on the overall prevalence for each method. Additionally, the funnel plot based on Egger’s regression asymmetry test was used to investigate small study effects and publication bias. All analyses were performed using Stata software version 14. Also, the significance level was considered 0.05 for all analyses.

Results

In total 35,652 records were identified in our systematic search, 1238 studies were assessed for eligibility and finally, 235 of them (862,243 individuals) were included in the meta-analysis (Figure 1). We showed the searched literature, as well as the characteristics of all included studies, regarding the global prevalence of S. stercoralis in Table 1. The weighted prevalence rate for microscopic, culture, immunological, and molecular was 1.47% (95% CI = 1.38%–1.56%), 10.08 (95% CI = 8.99%–11.16%), 23.88% (95% CI = 20.82%–26.94%) and 9.3% (95% CI = 7.2%–11.3%), respectively (Figures 2 and 3). In total, 60 of 195 countries had documented human strongyloidiasis. The largest number of studies was done in Thailand (25 studies). Bar graph was designed to show the distribution of countries for all eligible studies in this systematic review and meta-analysis (Supplementary Fig. 1).

Figure 1.

Figure 1.

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Flow diagram of the study design process

Table 1.

Main characteristics of the eligible studied reporting the prevalence of strongyloidiasis

No. First author Public year Country WHO regions Continent Total sample Positive
1 F. Lorincz 1930 Hungary European region Europe 1567 9
2 I.Hakki 1931 Turkey European region Europe 800 20
3 K. Deneche 1954 Iraq Eastern Mediterranean Asia 800 59
4 G.R. Winsberg 1975 United states Region of the americas North America 358 6
5 W. Jelitowy 1976 Poland European region Europe 9300 35
6 F. Arfaa 1977 Iran Eastern Mediterranean Asia 1240 5
7 N.D. Kuliev 1979 Azerbaijan European region Europe 3484 143
8 E.M. Proctor 1985 Canada Region of the americas North America 694 4
9 W. Alakija 1986 Nigeria African region Africa 1166 7
10 H. Carstensen 1987 Guinea-Bissau African region Africa 270 15
11 I. Ilard 1987 Somali African region Africa 237 23
12 R.W. Douce 1987 Thailand South – east Asian region Asia 206 18
13 T. Arakaki 1988 Japan South – east Asian region Asia 1017 46
14 R.M. Genta 1988 Italy European region Europe 4203 118
15 C.V. Holland 1989 Nigeria African region Africa 766 23
16 Y. Sato 1990 Japan South – east Asian region Asia 2906 577
17 T.W. Gyorkos 1990 Canada Region of the americas North America 232 150
18 Pitisuttithum 1990 Thailand South – east Asian region Asia 189 18
19 Egger 1990 Thailand South – east Asian region Asia 343 87
20 Koga 1991 Thailand South – east Asian region Asia 137 31
21 Boyajian 1992 Thailand South – east Asian region Asia 958 9
22 J.F. Lindo 1994 Jamaica Region of the americas South America 244 59
23 J.F. Lindo 1994 Jamaica Region of the americas South America 244 9
24 A. Hall 1994 Bangladesh South – east Asian region Asia 880 102
25 J. Kobayashi 1995 Brazil Region of the americas South America 222 23
26 M.J. Bangs 1996 Indonesia South – east Asian region Asia 478 4
27 T. Joyce 1996 Kenya African region Africa 70 3
28 M. Rezaeian 1996 Iran Eastern Mediterranean Asia 2368 244
29 G. Dreyer 1996 Brazil Region of the americas South America 972 311
30 C.E. Borda 1996 Argentina Region of the americas South America 207 4
31 T. Wodimagegnehu 1997 Ethiopia African region Africa 1787 3
32 G. Kang 1998 India South – east Asian region Asia 78 12
33 E.R. Machado 1998 Brazil Region of the americas South America 300 23
34 S. Jongwutiwes 1999 Thailand South – east Asian region Asia 1085 241
35 F.A. Núñez 1999 Cuba Region of the americas South America 401 1
36 A.K. Mohammed 1999 Iraq Eastern Mediterranean Asia 1681 25
37 C.C. Appleton 1999 South Africa African region Africa 1561 71
38 Toma 1999 Indonesia South – east Asian region Asia 654 7
39 Widjana 2000 Indonesia South – east Asian region Asia 2394 39
40 Anantaphruti 2000 Thailand South – east Asian region Asia 945 14
41 A. Farahnak 2001 Iran Eastern Mediterranean Asia 984 68
42 A.K. Shrestha 2001 Nepal South – east Asian region Asia 341 1
43 Y.A. Raja’a 2001 Yemen African region Africa 897 2
44 P.R. Sanchez 2001 Spain European region Europe 16,607 152
45 A. Al-Hindi 2002 Palestine Eastern Mediterranean Asia 650 4
46 J. Waikagul 2002 Thailand South – east Asian region Asia 2171 9
47 O.A. Adeyeba 2002 Nigeria African region Africa 248 1
48 S.de Silva 2002 Australia Western Pacific Region Australia 95 22
49 S. Nuchprayoon 2002 Thailand South – east Asian region Asia 6231 186
50 W. Saksirisampant 2002 Thailand South – east Asian region Asia 2213 26
51 Sithithaworn 2003 Thailand South – east Asian region Asia 332 41
52 Sithithaworn 2003 Thailand South – east Asian region Asia 332 40
53 W. Saksirisampant 2003 Thailand South – east Asian region Asia 106 1
54 N. Tang 2003 China Western Pacific region Asia 2558 1
55 P. Jongsuksuntigul 2003 Thailand South – east Asian region Asia 1233 290
56 N.J. Taranto 2003 Argentina Region of the americas South America 95 48
57 S.A. Miller 2003 Venezuela Region of the americas South America 45 1
58 P.R. Sanchez 2003 Spain European region Europe 250 31
59 F.B. Morrone 2004 Brazil Region of the americas South America 96 3
60 B.R. Saab 2004 Lebanon Eastern Mediterranean Asia 2634 2
61 J.C. Anosike 2004 Nigeria African region Africa 231 4
62 K. Koga-Kita 2004 Cambodia South – east Asian region Asia 3574 521
63 P.K. Garg 2005 United states Region of the americas North America 534 7
64 T.S. Chandrashekhar 2005 Nepal South – east Asian region Asia 2091 2
65 T.R. Ghimire 2005 Nepal South – east Asian region Asia 400 10
66 R. Yaicharoen 2005 Thailand South – east Asian region Asia 2230 2
67 N. Wongjindanon 2005 Thailand South – east Asian region Asia 4014 20
68 L. Yelifaria 2005 Ghana African region Africa 20,250 2146
69 K.E. Mote 2005 Uganda African region Africa 94 23
70 T. Chhakda 2006 Cambodia Western Pacific region Asia 188 38
71 P. Sithithaworn 2006 Laos Western Pacific region Asia 434 47
72 S.R.Caruana 2006 Australia Western Pacific Region Australia 204 10
73 J.C. Anosike 2006 Nigeria African region Africa 700 52
74 S.R. Caruana 2006 Australia Western Pacific Region Australia 230 97
75 S. Peruzzi 2006 Italy European region Europe 1117 3
76 M. Pirisi 2006 Italy European region Europe 100 28
77 S. L. Choubisa 2006 India South – east Asian region Asia 870 19
78 P.P. Yori 2006 Peru Region of the americas South America 792 69
79 P.P. Yori 2006 Peru Region of the americas South America 492 44
80 A.J. Rodr´guez-Morales 2006 Venezuela Region of the americas South America 1038 25
81 P.K. Patel 2006 Oman Eastern Mediterranean Asia 436 2
82 M.H. Wakid 2006 SaudiArabia Eastern Mediterranean Asia 1009 19
83 B.F. Alzain 2006 Palestine Eastern Mediterranean Asia 1600 90
84 D.L. Posey 2007 United states Region of the americas North America 562 237
85 M.R. Nilforoushan 2007 Iran Eastern Mediterranean Asia 1500 50
86 E.B. Kia 2007 Iran Eastern Mediterranean Asia 900 59
87 F.H. Abu-Elamreen 2007 Palestine Eastern Mediterranean Asia 150 1
88 D.L. Posey 2007 Sudan Eastern Mediterranean Africa 462 213
89 D. L. Posey 2007 Somali Eastern Mediterranean Africa 100 23
90 E.R. Machado 2007 Brazil Region of the americas South America 92 17
91 K.H. Jacobsen 2007 Equador Region of the americas South America 293 2
92 T. Hirata 2007 Japan South – east Asian region Asia 2406 112
93 G.T.A. Jombo 2007 Nigeria African region Africa 150 1
94 O.M. Agbolade 2007 Nigeria African region Africa 1059 7
95 P. Steinmann 2007 China Western Pacific region Asia 180 22
96 P. Steinmann 2007 China Western Pacific region Asia 180 40
97 A. Tungtrongchitr 2007 Thailand South – east Asian region Asia 479 10
98 S. Kitvatanachai 2008 Thailand South – east Asian region Asia 214 13
99 T.E. Erlanger 2008 Laos Western Pacific region Asia 5107 71
100 C.A. Ibidapo 2008 Nigeria African region Africa 300 54
101 S. Knopp 2008 Tanzania African region Africa 336 7
102 B.F. AL-Zain 2008 Palestine Eastern Mediterranean Asia 256 5
103 S. Rasti 2008 Iran Eastern Mediterranean Asia 297 1
104 G.R. Mowlavi 2008 Iran Eastern Mediterranean Asia 1494 9
105 B.F. Al-Zain 2009 Palestine Eastern Mediterranean Asia 256 5
106 S. Leelayoova 2009 Thailand South – east Asian region Asia 317 8
107 V. Nasiri 2009 Iran Eastern Mediterranean Asia 13,915 5
108 L. Akhlaghi 2009 Iran Eastern Mediterranean Asia 1000 1
109 M.H. Wakid 2009 SaudiArabia Eastern Mediterranean Asia 504 5
110 M.A. Babiker 2009 Sudan Eastern Mediterranean Africa 1500 2
111 S. Sayasone 2009 Laos Western Pacific region Asia 232 24
112 Z. Dabrowiecki 2009 Poland European region Europe 426 29
113 J.J. Verweij 2009 Ghana African region Africa 212 45
114 J.J. Verweij 2009 Ghana African region Africa 212 22
115 R. Houmsou 2009 Nigeria African region Africa 1000 17
116 O.A. Morenikeji 2009 Nigeria African region Africa 123 7
117 S. Foday 2009 Liberia African region Africa 646 2
118 B. Shakya 2009 Nepal South – east Asian region Asia 2221 6
119 F. Cheikhrouhou 2009 Tunisia Eastern Mediterranean Africa 30,573 92
120 N. Dash 2010 United Arab Emirates Eastern Mediterranean Asia 10,514 3
121 S.P. Sherchand 2010 Nepal South – east Asian region Asia 187 3
122 K. Ashrafi 2010 Iran Eastern Mediterranean Asia 150 63
123 S. Bdir 2010 Palestine Eastern Mediterranean Asia 123,290 112
124 A.J. Krolewiecki 2010 United states Region of the americas South America 228 59
125 A.J. Krolewiecki 2010 Argentina Region of the americas North America 228 67
126 B. Bon 2010 France European region Europe 195 57
127 D. Glinz 2010 Cote d’Ivoire African region Africa 251 82
128 C. Sarfati 2010 Cameroon African region Africa 420 4
129 F. Koksal 2010 Turkey European region Europe 27,664 2
130 A.A. Umar 2010 Nigeria African region Africa 280 104
131 J.C. Sousa-Figueiredo 2011 Uganda African region Africa 352 41
132 G.K. Singh 2011 Nepal South – east Asian region Asia 5524 40
133 Z. Dakić 2011 Serbia European region Europe 2440 1
134 M. Żukiewicz 2011 Poland European region Europe 120 7
135 L.S. Peterson 2011 Kenya African region Africa 211 6
136 E.DJ. Inês 2011 Brazil Region of the americas South America 634 40
137 H.Z. Rayan 2011 Egypt Eastern Mediterranean Africa 115 81
138 B.F. Al-zain 2011 Palestine Eastern Mediterranean Asia 1600 217
139 H. Moghaddassani 2011 Iran Eastern Mediterranean Asia 782 32
140 Z. Daki 2011 Serbia European region Europe 2440 1
141 E.DJ.Inês 2011 Brazil Region of the americas South America 634 29
142 J.R. Dib 2012 Argentina Region of the americas South America 149 4
143 J.D. Machicado 2012 Peru Region of the americas South America 73 39
144 A. Daryani 2012 Iran Eastern Mediterranean Asia 1100 13
145 H. Sadeghi 2012 Iran Eastern Mediterranean Asia 133 1
146 Y. Sultana 2012 Bangladesh South – east Asian region Asia 1004 222
147 C.E. Moore 2012 Cambodia Western Pacific region Asia 16,372 429
148 Y. Sultana 2012 Bangladesh South – east Asian region Asia 147 34
149 Y. Sultana 2012 Bangladesh South – east Asian region Asia 147 90
150 A.Vitta 2012 Thailand South – east Asian region Asia 124 3
151 S.J. Kaewpitoon 2012 Thailand South – east Asian region Asia 333 16
152 R. Canete 2012 Cuba Region of the americas South America 104 1
153 J.V. Conlan 2012 Laos Western Pacific region Asia 1358 121
154 V. Khieu 2013 Cambodia Western Pacific region Asia 458 183
155 A.F. Ahmad 2013 Malaysia Western Pacific region Asia 54 17
156 A.F. Ahmad 2013 Malaysia Western Pacific region Asia 54 3
157 C. Silvestri 2013 Italy European region Europe 5323 7
158 W. Anamnart 2013 Thailand South – east Asian region Asia 600 198
159 M. Asmar 2013 Iran Eastern Mediterranean Asia 700 7
160 H.A. Taha 2013 SaudiArabia Eastern Mediterranean Asia 2732 16
161 S. Boonjaraspinyo 2013 Thailand South – east Asian region Asia 253 15
162 W. Anamnart 2013 Thailand South – east Asian region Asia 600 200
163 S. Tandukar 2013 Nepal South – east Asian region Asia 1392 3
164 R. Shrestha 2013 Nepal South – east Asian region Asia 495 9
165 Y. Sultana 2013 Bangladesh South – east Asian region Asia 160 56
166 Schär 2013 Cambodia Western Pacific region Asia 218 131
167 N.M.S. Azira 2013 Malaysia Western Pacific region Asia 15,155 12
168 S. Davis 2013 United states Region of the americas North America 102 5
169 M.M. Naves 2013 Brazil Region of the americas South America 200 10
170 P. Naidu 2013 Canada Region of the americas North America 350 16
171 E.S. Russell 2014 United states Region of the americas North America 378 7
172 A.F. Malheiros 2014 Brazil Region of the americas South America 542 24
173 K. Ikegami 2014 Bolivia Region of the americas South America 274 41
174 E. Badparva 2014 Iran Eastern Mediterranean Asia 2839 2
175 M.TC. Fernández 2014 Spain European region Europe 1384 320
176 A.P. Santos 2014 Cuba Region of the americas South America 300 2
177 V. Khieu 2014 Cambodia Western Pacific region Asia 2861 875
178 Schär 2014 Cambodia Western Pacific region Asia 218 81
179 V. Khieu 2014 Cambodia Western Pacific region Asia 3560 1700
180 A.A. Hama 2014 Iraq Eastern Mediterranean Asia 1028 2
181 M.J.O. Rivero 2014 Colombia Region of the americas South America 262 2
182 M.J.O. Rivero 2014 Colombia Region of the americas South America 262 2
183 A.E. Abah 2015 Nigeria African region Africa 3826 273
184 H. Sadeghi 2015 Iran Eastern Mediterranean Asia 5739 1
185 M. Tork 2015 Iran Eastern Mediterranean Asia 880 5
186 M. Sharifdini 2015 Iran Eastern Mediterranean Asia 466 261
187 A.B. Rapoport 2015 United states Region of the americas North America 189 11
188 A. Asundi 2015 Canada Region of the americas North America 570 176
189 J.R. Dib 2015 Argentina Region of the americas South America 90 12
190 A. Aksoy Gökmen 2015 Turkey European region Europe 281 1
191 K. Korzeniewski 2015 Afghanistan Eastern Mediterranean Asia 1369 3
192 V. Krcmery 2015 Slovakia European region Europe 7640 92
193 S.L. Becker 2015 Cote d’Ivoire African region Africa 256 76
194 Y. Vonghachack 2015 Laos Western Pacific region Asia 729 299
195 S.J. Kaewpitoon 2015 Thailand South – east Asian region Asia 209 3
196 H.S. Supram 2015 Nepal South – east Asian region Asia 9470 7
197 K.Yadav 2016 Nepal South – east Asian region Asia 161 6
198 A. Kumar 2016 India South – east Asian region Asia 1638 2
199 S. Mohan 2016 India South – east Asian region Asia 372 14
200 J.W. Priest 2016 Cambodia Western Pacific region Asia 2150 935
201 S. Laymanivong 2016 Laos Western Pacific region Asia 327 134
202 R. Ngui 2016 Malaysia Western Pacific region Asia 236 5
203 T.Nguyen 2016 Vietnam Western Pacific region Asia 42,920 3174
204 K. Takaoka 2016 United Kingdom European region Europe 3306 31
205 D. Buonfrate 2016 Italy European region Europe 1351 153
206 A.S.R. Alsubaie 2016 Yemen African region Africa 258 2
207 R. Ngui 2016 Malaysia Western Pacific region Asia 236 26
208 H.El-din. I.El-Nemr 2016 SaudiArabia Eastern Mediterranean Asia 160 1
209 M.F. Karami 2017 Iran Eastern Mediterranean Asia 12,155 7
210 K.S. Randhir 2017 Nepal South – east Asian region Asia 2423 2
211 M. Tork 2017 Iran Eastern Mediterranean Asia 1120 6
212 R. Ghasemikhah 2017 Iran Eastern Mediterranean Asia 1800 12
213 G. Štrkolcová 2017 Slovakia European region Europe 81 20
214 M.R. de Alegra 2017 Angola African region Africa 230 33
215 I. Praharaj 2017 India South – east Asian region Asia 257,588 2306
216 C.W. Liao 2017 Cambodia Western Pacific region Asia 308 1
217 A.Forrer 2018 Cambodia Western Pacific region Asia 2576 1251
218 S. Nagpal 2018 India South – east Asian region Asia 318 16
219 E. Daca 2018 Angola African region Africa 351 75
220 Y. Paran 2018 Israel European region Europe 106 1
221 B. Monge-Maillo 2018 Spain European region Europe 752 76
222 P.V.da Silva 2018 Brazil Region of the americas South America 196 13
223 J.B. Nunes 2018 Brazil Region of the americas South America 258 139
224 R.A. Errea 2018 Peru Region of the americas South America 124 13
225 A.S. Pagheh 2018 Iran Eastern Mediterranean Asia 4788 18
226 M. Sharifdini 2018 Iran Eastern Mediterranean Asia 155 21
227 H. Kristanti 2018 Indonesia South – east Asian region Asia 80 60
228 H. Kristanti 2018 Indonesia South – east Asian region Asia 80 45
229 A. Gashout 2019 Libya Eastern Mediterranean Africa 18,000 2
230 S. Zhou 2019 China Western Pacific region Asia 98 7
231 N. Sahimin 2019 Malaysia Western Pacific region Asia 388 3
232 H.M. Al-Mekhlafi 2019 Malaysia Western Pacific region Asia 1142 180
233 H.M. Al-Mekhlafi 2019 Malaysia Western Pacific region Asia 1142 157
234 T. Menjetta 2019 Ethiopia African region Africa 13,679 41
235 N. Sahimin 2019 Malaysia Western Pacific region Asia 483 236
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Figure 2.

Figure 2.

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The pooled prevalence of S. stercoralis based on culture method

Figure 3.

Figure 3.

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The pooled prevalence of S. stercoralis based on immunological method

Parasitology methods (microscopic and culture methods)

In the current survey, 164 records from 53 countries included data with microscopic methods (751,421 individuals). The calculated total prevalence was 1.47% (95% CI = 1.38%–1.56%). Egypt had the highest prevalence with 34.78% (95% CI = 26.14%–44.22%) followed by Peru with 32.87% (95% CI = 22.32%–44.86%), whereas the lowest was in Libya with 0.01% (95% CI = 0.001%–0.04%). According to the continent, the highest level of infection was in South America with 7.42% (95% CI = 5.28%–9.56%) and Africa with 1.60% (95% CI = 1.31%–1.89%) was the continent with the lowest prevalence. Among WHO regions, the Western Pacific region had the highest infection rate with 9.47% (95% CI = 8.55%–10.39%) while the Eastern Mediterranean region had the lowest prevalence with 0.4% (95% CI = 0.3%–0.5%). Our results showed that the majority of infected people were immigrants, with a prevalence of 23.12% (95% CI = 20.92%–25.43%) but a small number was hospital patients with 0.01% (95% CI = 0.004%–0.03%). In accordance with the patient position, group one (rural) with 4.66% (95% CI = 3.94%–5.39%) was the most infected group unlike group two (urban) with the lowest infection rate of 0.19% (95% CI = 0.1%–0.2%).

The publication bias using Egger’s regression test was statistically significant (p<0.0001) (Supplementary Fig. 2). Meta-regression results showed no statistically significant relationship between prevalence of the parasitology method and sample size (P =0.175), year of publication (P =0.310), HDI (P =0.456), Gini (P =0.439), latitude (P = 0.121), and longitude (P = 0.390) (Supplementary Fig. 3&4).

The culture method was used in 41 surveys from 20 countries (54,858 individuals) and the overall prevalence was 10.08% (95% CI = 08.99%–11.16%). Laos had the highest prevalence with 40.97% (95% CI = 35.59%–46.52%) and Serbia [0.041% (95% CI = 0.001%–0.22%)] was the least prevalent country. The culture method showed the highest frequency in Asia [13.92% (95% CI = 10.94%–16.91%)] and the lowest in Europe [0.7% (95% CI = 0.2%–1.0%)]. Based on WHO Region, the Western Pacific region with the pooled prevalence of 21.36% (95% CI = 16.32%–26.39%) had the highest prevalence while the lowest was in the European region 0.7% (95% CI = 0.2%–1.63%). Farm workers [12.40% (95% CI = 8.58%–17.37%)] were amongst the most infected patients and travelers had the least infection rate with 0.041% (95% CI = 0.001%–0.2%). The results of Egger’s test indicated that there was statistically significant publication bias (p<0.0001) (Supplementary Fig. 5). There was a significant correlation between frequency of the parasitology methods and HDI (P = 0.004), Gini (P = 0.008), latitude (P = 0.023) and longitude (P = 0.013) (Figures 4 and 5; Supplementary Fig. 6 and 7). No significant relation was detected between prevalence of the culture method and sample size (P = 0.812), year of publication (P = 0.362), HDI (P = 0.456), Gini (P = 0.439), latitude (P = 0.121) and longitude (P = 0.390). Bar graphs of the distribution of year of publication and the included countries for the parasitology method were presented in Supplementary Figures 8 and 9.

Figure 4.

Figure 4.

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Meta-regression plot for the culture method based on HDI

Figure 5.

Figure 5.

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Meta-regression plot for the culture method based on Gini

Immunological methods

Thirty-four seroprevalence studies from 22 countries were carried out on (60,310 individuals). The total prevalence was 23.88% (95% CI = 20.82%–26.94%) with the immunological method. Based on the immunological method, the highest and the lowest pooled prevalence was related to Argentina and Turkey with 50.52% (95% CI = 40.07%–60.94%) and 0.35% (95% CI = 0.009%–1.96%), accordingly. Among the continents, Africa showed the highest pooled seroprevalence with 40.72% (95% CI = 36.74%–44.70%) but the lowest was in Europe with 9.06% (95% CI = 6.02%–12.09%). The Eastern Mediterranean Region with 40.72% (95% CI = 36.74%–44.70%) had the most seroprevalence among WHO Regions while the European Region had the lowest pooled prevalence of 9.06% (95% CI = 6.02%–12.09%). Also, our results showed that refugees were the most infected patients with 30.96% (95% CI = 14.62%–47.30%) versus the lowest pooled prevalence of 0.3% (95% CI = 0.009%–1.96%) in farmers. Furthermore, group three (patient position), showed the highest pooled prevalence of 24.18% (95% CI = 18.94%–30.05%) and group two had been the least infected group with 20.66% (95% CI = 14.86%–26.45%). In addition, the publication bias was very significant (P<0.0001) (Supplementary Fig. 10). Based on results of the meta-regression test, there was a statistical significant relationship between frequency of the immunological methods and sample size (P =0.324), year of publication (P =0.419), HDI (P =0.103), Gini (P =0.663), latitude (P = 0.502) and longitude (P = 0.428). Bar graphs of the distribution of year of publication and the included countries for the immunological method are shown in Supplementary Figures 11 and 12.

Molecular methods

We found that 16 reports from nine countries used the molecular method (among 7985 participants). The total molecular prevalence of strongyloidiasis was 9.3% (95% CI = 7.2%–11.3%). Angola with 21.36% (95% CI = 17.19%–26.03%) and Ghana with 21.22% (95% CI = 15. 92%–27.35%) had the maximum molecular-pooled prevalence, but the minimum was detected in Palestine with 0.6% (95% CI = 0.01%–3.65%). Based on continent, Africa was the most prevalent [19.75% (95% CI = 17.20%–22.30%)] and Asia was the least prevalent with 6.35% (95% CI = 4.41%–8.28%). Among WHO Regions, the highest total prevalence was in the African region with 19.72% (95% CI = 16.71%–22.73%) while the Eastern Mediterranean Region had the lowest prevalence of 5.89% (95% CI = 3.96%–8.08%). Our results showed that schoolchildren with 13.74% (95% CI = 11.80%–15.88%) were the most infected patients but the least prevalent group was related to the children admitted to the pediatric hospital [0.6% (95% CI = 0.01%–3.65%)]. As shown in Supplementary Figure 13, publication bias was statistically significant based on asymmetry Egger regression test (P <0.0001). Based on the results of meta-regression test, there was a significant relationship between prevalence of the molecular method and HDI (p=0.020). However, it didn’t show a significant relation between prevalence of the molecular method and sample size (P =0.172), year of publication (P =0.661), Gini (P =0.592), latitude (P =0.522) and longitude (P =0.143). Regarding the prevalence of human strongyloidiasis in different geographical regions of the world, four GIS maps were designed based on the microscopic, culture, immunological, and molecular studies (Figures 6–9). Bar graphs of the distribution of year of publication and included countries for the molecular method are shown in Supplementary Figures 14 and 15. Sensitivity analysis for culture, immunological and molecular methods showed that none of the studies alone had the significant impact on the pooled prevalence of each methods (Supplementary Fig. 16, 17 &18).

Figure 6.

Figure 6.

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Prevalence of Strongyloidiasis in different geographical regions of the world based on microscopic method

Figure 7.

Figure 7.

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Prevalence of Strongyloidiasis in different geographical regions of the world based on Culture method

Figure 8.

Figure 8.

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Prevalence of Strongyloidiasis in different geographical regions of the world based on Immunological method

Figure 9.

Figure 9.

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Prevalence of Strongyloidiasis in different geographical regions of the world based on Molecular method

The number of molecular studies was assessed according to the year of publication and countries (Supplementary Fig. 14 and 15). Sensitivity estimate analysis for all mentioned methods (microscopic, culture, immunological, and molecular) showed that the studies had no impact on the pooled prevalence individually (Supplementary Fig. 16, 17, and 18).

Discussion

Strongyloidiasis is one of the most widespread chronic infections caused by the neglected soil-transmitted helminth, S. stercoralis with a homogonic (host-dependent) and heterogonic (free-living) life cycle [20]. Previous reports have shown that the infection is not exclusively limited to tropical and subtropical regions, as there are some cases from non-tropical urban areas [21]. According to these surveys, S. stercoralis is a predominant specie in humans but it can also infect other mammals including dogs or cats and even primates [22,23]. Our systematic review and meta-analysis represented the overall frequency of strongyloidiasis in the general population across the world with the purpose of establishing prophylactic approaches to eradicating these parasites in the future. Published epidemiological records from five English databases (Science Direct, Scopus, PubMed, Web of Science, and Google Scholar) were explored according to the related keywords without time limitation before October 2019. We estimated the pooled prevalence and its correlation with various types of criteria according to the different diagnostic techniques such as parasitology (microscopy and culture), immunology, and molecular methods [16]. Two hundred and thirty-five entries on the subject of human strongyloidiasis were found to be eligible for inclusion in the review. Sixty out of 195 countries had reported human strongyloidiasis and the majority of studies were related to Thailand (25 records). The worldwide prevalence of human strongyloidiasis was 1.47% (95% CI = 1.38%–1.56%) by microscopy, 10.08 (95% CI = 8.99%–11.16%) by culture, 23.88% (95% CI = 20.82%–26.94%) by serology and 9.3% (95% CI = 7.2%–11.3%) by molecular techniques. In our study, many of the studies used microscopy procedure as a diagnostic method (166 studies). Based on microscopic techniques, Egypt (34.78%) and Peru (32.87%) had the highest pooled prevalence among countries. The studies were limited in both Egypt and Peru, as there was just one eligible record for each country that can be used as evidence for the high rate of pooled prevalence. Immigrants were the largest group of infected people (23.12%) in our microscopy results.

It can be inferred from a former survey that strongyloidiasis has a high prevalence rate in Latin America, sub-Saharan Africa, and South–East Asia. Also, it showed that the main risk groups are refugees and immigrants as they had infection rates of more than 75% [24]. According to our results of microscopy investigations, rural populations (4.66%) were the most infected group. This can indicate that the infection rate and clinical symptoms of strongyloides can be high in socio-economically and environmentally poor regions where people live with low sanitary standards and no access to diagnostic and treatment procedures.

This situation was similar to the results of studies in individuals with a high rate of S. stercoralis infection in rural communities in Cambodia. Another investigation with regard to helminth infection among schoolchildren in Ethiopia showed that the infection was higher in rural than in urban areas, which could indicate the direct impact of bare feet on the prevalence of intestinal helminths in those settings [25,26]. Our findings from surveys with the culture method showed that Laos had the largest number of cases (40.97%). This country is located in the Western Pacific Region of Asia and as one of the least developed countries, it has a high mortality rate due to the lack of appropriate nutrition and high prevalence of intestinal parasites as well as S. stercoralis. Previous evidence has suggested that helminthic infections are endemic in this area where walking barefoot outdoors is a common habit. Additionally, it must be stated that socioeconomic factors such as sanitary level, agricultural conditions, rate of environmental contamination by human feces may also have an impact on the level of strongyloidiasis in this country [27,28].

Asia has a large population with favorable conditions of climate, ecology, and socio-economy for the transmission and persistence of S. stercoralis. However, the reports on its occurrence are still limited in this region. Nowadays, the application of stool cultures including the Koga Agar plate culture, Baermann method, and also vermiculite stool culture seems to be reliable for detection of S. stercoralis in fecal samples [29]. Strongyloidiasis is one of the NTDs that is associated with health and economic losses especially in the countries of the WHO Western Pacific Region [30]. According to our results, this WHO region had the highest infection rate from both microscopy (9.47%) and culture methods (21.36%). Those studies that used an immunological assay confirmed that Argentina (50.52%) had the most infected cases of seroprevalence. Prior reports from Argentina showed that in this region the disease is endemic (prevalence rates of 30%–50%) since socioeconomic and environmental circumstances are compatible for transmission and persistence of the infection [31,32]. Likewise, the WHO Eastern Mediterranean Region (40.72%) had a maximum rate of seroprevalence. Since Somalia and Sudan are located in the Eastern Mediterranean WHO Region of the African continent, the highest seropositive cases were detected in these areas. The European region, with a high level of sanitary conditions and health care, had the least seropositive cases and most of the infected individuals were refugees and immigrants [33]. The total molecular prevalence of strongyloidiasis derived from our results showed that Angola (21.36%) and Ghana (21.22%) were the most prevalent countries in the WHO African region with a total prevalence of 19.72%. The molecular overall prevalence was the highest in the African continent and African WHO region. The molecular pooled prevalence of strongyloidiasis obtained in our study was comparable to those studies performed in Angola (21.4%) and Ethiopia (20.7%), where there are wet and dry seasons with tropical grasslands [34]. Our results showed a direct relation between publication bias and the pooled prevalence in all assessed studies. There are probable differences in sensitivity and specificity of the various diagnostic methods that affected the estimated pooled prevalence described here. A common worldwide diagnostic test for intestinal parasites is a direct wet mount which has low sensitivity, especially as a low burden of infection may increase the misdiagnosis. There is no gold standard method for the diagnosis of strongyloidiasis. However, parasitological and serological techniques are two common and useful tests. There are different types of parasitological procedures in order to detect the larval stage in fecal samples, containing microscopy (Direct smear, formalin-ethyl acetate, and Baermann method) and culture (Harada-Mori culture and Agar Plate Culture). Even though the low burden of parasites and disordered larval elimination can lead to the low sensitivity of mentioned techniques, collecting several fecal samples during different days is necessary. Applying culture methods is useful for the differentiation of filariform larvae from rhabditoid larvae [35]. Kato-Katz and Mini-FLOTAC method are two alternative procedures with reliable accuracy. The immunological methods (enzyme-linked immunosorbent assay (ELISA), western blot, indirect agglutination, and indirect immunofluorescence) detecting larval antigens in serum, stool, and urine samples have different sensitivity and specificity [36–40]. Former investigations showed that the sensitivity of immunological assays are superior to parasitological methods but still there is an issue regarding their specificity, including antibody cross-reactivity with antigens from other helminthic infections and false-positive cases as a result of the persistence antibody [41,42]. The relevant diagnostic molecular methods are consisted of conventional polymerase chain reaction (PCR), nested-PCR, real-time-PCR (qPCR), and Loop-mediated isothermal amplification (LAMP) using ITS-1, ITS-2, COX-1, SSU rRNA, 18S rRNA [36,43–45]. These molecular procedures have higher sensitivity than parasitological or immunological tests; however, accuracy depends on extraction procedures [46,47]. Consideration of an adequate diagnostic method with high sensitivity and specificity is needed to avoid a lack of diagnosis and to perform appropriate management of infection in future surveys.

Conclusion

The current systematic review and meta-analysis shows the global distribution and epidemiological features of human strongyloidiasis. Several investigations imply that gender, age, walking barefoot, using corticosteroids, being an immunocompromised patients, living in high-density populations with a low level of sanitary settings (latrines and sewage system), geographical conditions of the living area, being at a poor socio-economic level and having malnutrition are the main risk factors for strongyloidiasis. We found significant differences in prevalence between rural and urban areas, as has been reported in many studies. This infection is probably more prevalent than that reported in the published literature as the sensitivity and specificity of diagnostic methods vary. Comprehensive research using reliable assays along with advanced screening plans, particularly for at-risk groups and population in endemic areas, are very helpful. The higher frequency in the Western Pacific and Eastern Mediterranean regions highlights the importance of geographical situation which has a direct impact on the infection rate. We recommend health-care administrators to implement effective health surveillance, especially in regions with high infection levels, along with methods to improve public awareness.

Supplementary Material

Supplemental Material
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Funding Statement

This work was supported by the Urmia University [IR.UMSU.REC.1398.384].

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed here.

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