This review explores our understanding of Giardia and Cryptosporidium distribution in Middle East and North African (MENA) water resources. Results emphasize that Cryptosporidium species (sp.) and G. duodenalis (oo)cysts are present in distinct categories of water in 10 MENA countries. Cryptosporidium sp. proportional prevalence in the MENA region was 24.5% (95% CI 16.3–33.8), while G. duodenalis prevalence was 37.7% (95% CI 21.9–55.1). Raw wastewater and surface water were the water categories most significantly impacted. Both parasites were reported in the various types of MENA drinking waters. The most frequent species/genotypes reported were C. hominis, C. parvum, and G. duodenalis assemblage A. Despite the high prevalence of (oo)cysts reported, we should consider the absence of waterborne outbreaks. This indicates significant underestimation and underreporting of both parasites in MENA. Stakeholders should apply water contamination legislation to eradicate Cryptosporidium sp. and G. duodenalis (oo)cysts from water resources/categories.

  • Cryptosporidium and G. duodenalis (oo)cysts are found in all water supplies of MENA.

  • High contamination of the raw wastewater and surface water samples.

  • MENA drinking waters are contaminated with both parasites.

  • The treatment processes are not efficient in eradicating parasites from water.

  • Cryptosporidium sp. and G. duodenalis are underreported and underestimated.

C. hominis

Cryptosporidium hominis

C. parvum

Cryptosporidium parvum

CRT

City reservoir tanks

DALY

Disability-adjusted life years

DhR

Dihydrofolate reductase

DsW

Desalinated water

DW

Drinking water

ef1α

Elongation factor 1α

ELISA

Enzyme-linked immune-sorbent assay

G. duodenalis

Giardia duodenalis

Gdh

Glutamate dehydrogenase

GEMS

Global Enteric Multicenter Study

GCC

Gulf Corporation Countries

gp60

Glycoprotein 60

HBT

Home-based tanks

IMS – IFA

Immunomagnetic separation coupled with immunofluorescent assay

IMS-IFT

Immunomagnetic separation-immunofluorescent technique

LAMP

Lateral flow loop-mediated isothermal amplification

MENA

Middle East and North Africa

MeSH

Medical Subject Headings

mZN

Modified Ziehl–Nielsen

PCR

Polymerase chain reaction

PCR-RFLP

Restriction fragment length polymorphism polymerase chain reaction

RWW

Raw wastewater

SAM-1

S-adenosyl-1-methionine synthetase

SF

Surface water

Sp

Species

SwP

Swimming pools

2nd

Secondary treated wastewater

3rd TWW

Tertiary treated wastewater

Tpi

Triosephosphate isomerase

UAE

United Arab Emirates

UV

Ultraviolet

WBP

Waterborne protozoa

WHO

World Health Organization

In the past century, the human population has more than tripled, and water needs have more than quadrupled, leading to an increased demand for water resources worldwide (Rosado-García et al. 2017). Aside from a lack of water, its quality is questionable: Two billion people use contaminated water sources, resulting in 485,000 deaths from diarrhea each year (World Health Organization 2019). The severity of water contamination, characterized by a rising prevalence of pathogenic microorganisms such as protozoa, is accountable for the fatalities mentioned earlier. Waterborne protozoa (WBP) represent a public health risk with worldwide distribution, and they have been reported in both developed and developing countries with a continuously increasing number of outbreaks (Karanis et al. 2007; Baldursson & Karanis 2011; Efstratiou et al. 2017a; Bourli et al. 2023). The most common WBP are Cryptosporidium sp. and Giardia duodenalis (G. duodenalis), which could infect various hosts, including humans (Karanis et al. 2007; Baldursson & Karanis 2011; Efstratiou et al. 2017a; Ahmed et al. 2018; Bourli et al. 2023).

Cryptosporidium sp. and G. duodenalis are ubiquitous enteric protozoan parasites with a broad host range and multiple transmission routes (Aw et al. 2019). Cryptosporidium sp. and G. duodenalis can be transmitted via various routes, including fecal–oral, zoonotic, waterborne, and foodborne routes (Gerba 2009; Ahmed & Karanis, 2018; Pal et al. 2021). Waterborne transmission is the primary route for cryptosporidiosis and giardiasis via (oo)cysts contaminating surface water, groundwater, and wastewater (da Silva et al. 2021). (Oo)cysts' sizes and resistance to disinfection procedures (chlorination, ultraviolet (UV)) increase their survival and render water treatment processes ineffective (Karanis et al. 1998, 2007; Ben Ayed et al. 2009; Baldursson & Karanis 2011; Efstratiou et al. 2017a; Karanis 2018; Bourli et al. 2023).

Between 2004 and 2023, Cryptosporidium sp. and G. duodenalis were the leading etiological agents of waterborne and foodborne outbreaks (Karanis et al. 2007; Baldursson & Karanis 2011; Efstratiou et al. 2017a; Ben Ayed et al. 2019; Bourli et al. 2023). Cryptosporidium sp. has been identified as the leading cause of 1,227 reported waterborne outbreaks, followed by G. duodenalis (213 waterborne outbreaks) (Nygård et al. 2006; Karanis et al. 2007; Cheun et al. 2013; Rosado-García et al. 2017; Efstratiou et al. 2017a; Bourli et al. 2023), in which recreational water and swimming pools were identified as potential origins for 92% of Cryptosporidium sp. and 25.3% of G. duodenalis outbreaks.

Cryptosporidium sp. is ranked as the second leading cause of moderate-to-severe diarrhea in infants at all seven Global Enteric Multicenter Study (GEMS) sites due to the high oocyst output from infected individuals (Kotloff et al. 2012; Sow et al. 2016) and low infectious dose (<10 oocysts) (Haas & Rose 1994; Environmental Protection Agency 2001). Globally, the average reported prevalence of Cryptosporidium is 4.3% in developed countries and 10.4% in developing countries (Dong et al. 2020). Among children under five, Cryptosporidium sp. is the fifth most prevalent cause of diarrhea, leading to 4.2 million disability-adjusted life years (DALYs) and more than 48.000 deaths globally (Chique et al. 2020). It is strongly associated with colon cancer (Osman et al. 2017). The parasite can also infect different animals' digestive and respiratory tracts, like fish, amphibians, reptiles, birds, and mammals (Holubova et al. 2019), resulting in economic losses associated with livestock production (Castro-Hermida et al. 2010). Forty-seven Cryptosporidium sp. have been identified (Jezkova et al. 2021; Zahedi et al. 2021), and more than 120 genotypes described (Ryan et al. 2021); almost 19 species and four genotypes of them have been observed in humans, with Cryptosporidium hominis (C. hominis) and Cryptosporidium parvum (C. parvum) being the most common infecting species (Innes et al. 2020; Ryan et al. 2021).

G. duodenalis, one of the most common human parasitic infections worldwide, is a significant health burden. It infects 200 million people in Africa, Asia, and Latin America (Hernández et al. 2019). Giardiasis, the disease caused by G. duodenalis, is characterized by debilitating symptoms, including diarrhea, nausea, abdominal cramps, vomiting, and fatigue. These symptoms can be chronic, recurring, and last for several weeks, significantly impacting the quality of life of those affected. The human prevalence of G. duodenalis has been reported in both industrialized countries (1–8%) and developing ones (8–33%) (Cacciò 2015; Ryan et al. 2021). Giardia is a multispecies complex with eight recognized assemblages (A–H). Assemblages A and B are the major human pathogens (Wang et al. 2019).

The Middle East and North Africa (MENA) region is considered a water-scarce area because it hosts only 2% of the world's renewable freshwater supply for nearly 6% of its population. Consequently, about 61% of the MENA population lives under water stress conditions (Mazzoni & Zaccagni 2019). Hence, the current challenge for the MENA region is to manage water demand and supply while addressing climate change. The MENA countries are a mix of low-, middle-, and high-income countries, with a wide range of natural resources and socio-demographic aspects (Mazzoni et al. 2018; Ahmed & Karanis 2020).

With limited access to safe drinking water (DW), cases of cryptosporidiosis and giardiasis are most likely underreported because they are not mandatory notifiable diseases (Plutzer et al. 2018), leaving gaps in understanding their natural circulation in the environment. (Oo)cysts presence is not correlated to the existence of fecal indicators (Bailey et al. 2021). Nevertheless, in the MENA region, (oo)cysts of Cryptosporidium sp. and G. duodenalis were reported in surface water, DW, raw and treated wastewater (TWW), swimming water, and seawater (Nasser et al. 2003; Mahmoudi et al. 2013; Ghasemi et al. 2019; Moussa et al. 2023).

More information is needed regarding the burden of Cryptosporidium sp. and G. duodenalis on the MENA region's water resources. The current review aims to systematically meta-analyze the distribution and prevalence of Cryptosporidium sp. and G. duodenalis in different water resources and water categories of the MENA region, as well as their environmental circulation and distribution.

Search strategy

PubMed, Scopus, Web of Science, and Academia were used in the literature selection process, which began on 23 July 2022, and ended on 14 July 2023, to assess the information on Cryptosporidium sp. and G. duodenalis (oo)cysts prevalence and distribution in the water resources and categories of the MENA countries. The articles were searched regardless of language or publication year. The search strategy was limited to title/abstract/keywords using the following MeSH terms/keywords employing Boolean positional operators (‘AND, OR’): (Giardia) OR (Protozoa) OR (Cryptosporidium) OR (Parasite OR Parasites) AND (Water OR groundwater OR water wells OR wastewater OR drinking water OR recreational water OR irrigation water OR surface water OR water bodies) AND (Algeria OR Bahrain OR Egypt OR Iran OR Iraq OR Israel OR Jordan OR Kuwait OR Lebanon OR Libya OR Morocco OR Oman OR Qatar OR Saudi Arabia OR Syria OR Tunisia OR United Arab Emirates (UAE) OR Palestine OR Yemen) AND (outbreaks OR contamination OR occurrence OR incidence OR prevalence).

Eligibility criteria

Articles in MENA water categories with titles containing the words Cryptosporidium and Giardia were screened and selected for inclusion in the literature review. Three authors (LBA, SA, and SB) independently reviewed abstracts and potentially relevant full texts, resolving conflicts by consensus.

Following the full-text screening, a comprehensive array of information was meticulously extracted: study site, publication year, type of water investigated, the volume of water sampled, sampling procedure, frequency of Cryptosporidium sp. and G. duodenalis in each kind of water (number of contaminated/number of total) as reported by the authors or estimated from data provided in the paper, methods used for both parasites detection, the concentration of (oo)cysts in the tested type of water, and details of molecular genotyping/subtyping when investigated. This thorough data extraction process ensures the depth and accuracy of our review.

Publications were excluded if they lacked an abstract, full text; used languages other than English, Arabic, or French; were related to animals, humans, food, or soil; had the goal of diagnosis and intervention; were performed in countries outside the MENA region; were reviews, short communications, and conference proceedings or had ambiguous data (indistinct data, poor quality citation, include the same results as another paper published by the same author).

Data classification and meta-analysis

Numerous synonyms of water resources were discussed in the selected publications. Therefore, the water resources in MENA countries were classified into six main categories: DW, swimming pool (SwP), surface water (SF), wastewater, seawater, and medical water. The main categories were subsequently subcategorized to facilitate data analysis, as illustrated in Table 1.

Table 1

Details of each water category reported in the retrieved studies

No.CategoryWater subcategories
Drinking water (DW) Tap water, cooler water, bottled (shops, vendors, mineral water), city reservoir tanks (CRT), roof/underground home-based tanks (HBT), wells, spring, and desalinated water (DsW) 
Swimming pool (SwP) Swimming pool 
Surface water (SF) Rivers, canals, ponds, water pumps and works 
Wastewater Raw wastewater (RWW) 
Secondary treated wastewater (2nd TWW) 
Tertiary treated wastewater (3rd TWW) 
Seawater Marine water 
Medical water Dental irrigation water 
No.CategoryWater subcategories
Drinking water (DW) Tap water, cooler water, bottled (shops, vendors, mineral water), city reservoir tanks (CRT), roof/underground home-based tanks (HBT), wells, spring, and desalinated water (DsW) 
Swimming pool (SwP) Swimming pool 
Surface water (SF) Rivers, canals, ponds, water pumps and works 
Wastewater Raw wastewater (RWW) 
Secondary treated wastewater (2nd TWW) 
Tertiary treated wastewater (3rd TWW) 
Seawater Marine water 
Medical water Dental irrigation water 

A meta-analysis approach was used to determine the significance of Cryptosporidium sp. and G. duodenalis contamination in the various water categories within the MENA region. Consequently, we extracted data from studies retained by the eligibility criteria section, ensuring that the water source parameters were reported at least twice for the correlation analysis. Therefore, to prevent data loss, subgrouping was favored due to the use of distinct target parameters (Boughattas 2017). The MedCalc statistical software version 22.016 (MedCalc Software Ltd, Osten, Belgium https://www.medcalc.org/) was subsequently utilized to conduct a proportion meta-analysis to obtain the effect sizes and 95% confidence intervals (95% CI) associated with the variance for the desired set of studies. As measured by Cochran's score Q, the heterogeneity of observations should be observed with p (Q) < 0.0005 when tested against a chi-square distribution to conduct correlation analysis. Publication bias was explored in the current study and assessed by Egger's test (E), with a low p-value indicating publication bias.

Reports data and meta-analysis characteristics

According to the eligibility criteria (section 2.2), a combined search of NCBI (911), Scopus (50), Academia (549), and Web of Science (49) yielded 1,559 studies. Following title verification and duplicate removal, 1,198 studies were retained. Only 38 studies were eligible within the maintained records after the title/abstract screening. After complete text checking, another ten articles were excluded. Hence, according to the defined categories (Supplementary File, Figure S1), 1,170 studies were excluded due to incompatibility with the inclusion criteria.

Finally, twenty-eight studies were eligible for inclusion. Seven different studies were added during the reference list screening process. The current review includes 35 studies for the final meta-analysis (Supplementary File, Figure S1).

The studies included in this review, spanning from 1988 to 2023, provide a comprehensive view of the presence of Cryptosporidium sp. and G. duodenalis in MENA countries. Cryptosporidium sp. and G. duodenalis are represented, respectively, in 10 (52.63%) and 9 (47.36) of 19 MENA countries. Notably, Egypt, Iran, Iraq, Israel, Jordan, Lebanon, Morocco, Palestine, Saudi Arabia, and Tunisia were the countries that included studies in the present review and reported the presence of Cryptosporidium sp. in water resources and categories. Giardia sp. presence was reported in all countries above except Jordan. However, Algeria, Bahrain, Kuwait, Libya, Oman, Qatar, Syria, UAE, and Yemen (47.39%) had no studies to include (Figure 1), indicating a potential research gap in these regions.
Figure 1

Distribution of water studies (number and location) for Cryptosporidium and Giardia in the Middle East and North Africa. Countries with zero included studies are Algeria, Bahrain, Kuwait, Libya, Oman, Qatar, Syria, United Arab Emirates (UAE), and Yemen; N/R, not reported.

Figure 1

Distribution of water studies (number and location) for Cryptosporidium and Giardia in the Middle East and North Africa. Countries with zero included studies are Algeria, Bahrain, Kuwait, Libya, Oman, Qatar, Syria, United Arab Emirates (UAE), and Yemen; N/R, not reported.

Close modal

For Cryptosporidium sp., Egypt emerged as a significant contributor, leading the way with the most included studies in MENA (10/35; 28.5%). This was closely followed by Iran (6/35; 17.1%), Tunisia, and Israel (2/35; 5.7% for each). Other countries such as Iraq, Jordan, Lebanon, Palestine, and Saudi Arabia also made notable contributions (1/35; 2.85% for each) (Table 2).

Table 2

Reports on Cryptosporidium contamination of water bodies in the Middle East and North Africa (MENA) countries

CountrySerial no. of reportsType of water investigatedSampling volume (L)Method of detectionMethod applied for concentration and detectionNo. of contaminated/no. of totalReference
Egypt DW 0.6 to 1.5 Non-molecular N/R Bottled water: 0/84 Abd El-Salam et al. (2008)  
DW 0.1 Non-molecular N/R Public coolers: 3/20 Hussein et al. (2009)  
SF 10 Non-molecular and molecular Filtration, concentration, staining, and MAS – PCR Canal: 19/24 Rayan et al. (2009)  
DW Tap: 2/64 
SwP NM Non-molecular Filtration, centrifugation, and staining 1/30 Abd El-Salam (2012)  
Medical water 0.5 Non-molecular Filtration and staining Dental irrigation water: 11/40 Hassan et al. (2012)  
SF 0.01 Non-molecular Filtration, centrifugation, and staining Total water samples:63/246
  • – River: 15/48

  • – Waterworks: 10/48

  • – Pumps: 9/48

  • – Ponds: 17/48

  • – Canal: 12/48

 
Khalifa et al. (2014)  
DW Total water samples:18/96
  • – Tap: 6/48

  • – CRT: 12/48

 
DW 10 Non-molecular and molecular Filtration, staining, nested PCR, and PCR-RFLP Tap: 29/80 Hamdy et al. (2019)  
SwP Non-molecular Filtration and staining 27/78 Hassanein et al. (2023)  
SF 10 Non-molecular and molecular Filtration, centrifugation, IMS-IFA, and PCR *Cryptosporidium was detected in 20.83% of the inlet (SF) and outlet (tap) samples at the DTWP Moussa et al. (2023)  
DW 
10 DW 25 Non-molecular and molecular IMS – IFA and PCR Tap: 2/50 Abou Elez et al. (2023)  
Iran SF 10 Molecular Nested PCR and PCR-RFLP River: 6/30 Manouchehri et al. (2011)  
SF 10 Non-molecular and molecular Filtration, IFA, nested PCR, and LAMP River: 11/20 Mahmoudi et al. (2013)  
SF 2–50 Non-molecular and molecular Concentration, IMS, and nested PCR River: 24/49 Mahmoudi et al. (2015a)  
SF 50 Non-molecular IMS- IFA *Cryptosporidium was detected in 73.68% of investigated river samples Hadi et al. (2016)  
SwP Molecular Nested PCR 0/13 Ghasemi et al. (2019)  
SF 10 Non-molecular and molecular Filtration, staining, and PCR River: 17/42 Sharafi et al. (2023)  
Iraq DW 0.01–0.02 Non-molecular Direct wet smear, and staining Tap: 21/100 Al-Samarrai et al. (2022)  
Israel Seawater 10 Non-molecular IMS- IFA Marine water: 5/10 Nasser et al. (2003)  
Wastewater RWW: 0.2 Non-molecular and molecular Filtration, concentration, IFA, and nested PCR 21/43 Taran-Benshoshan et al. (2015)  
2nd TWW: 10 27/43 
3rd TWW: 25–50 17/25 
Jordan DW 15 Non-molecular Filtration, staining, and IFA HBT
  • – Underground cisterns: 4/52

  • – Concrete reservoir: 0/31

  • – Metal tanks: 0/149

 
Abo-Shehada et al. (2004)  
Lebanon DW Non-molecular Filtration, sucrose flotation, and IFA Total water samples: 30/55
  • – Wells: 4/11,

  • – Bottled water: (vendors: 17/32 & shop: 4/4)

  • – Tap: (school: 3/5 & municipality: 2/3).

 
Khoury et al. (2016)  
Morocco SF Non-molecular Direct spawning, modified Bailenger method, and Faust flotation Cryptosporidium was detected in 50% of river samples. Ouarrak et al. (2022)  
 DW 40 Molecular Filtration and real-time qPCR Total water samples: 0/144
  • – Tap: 0/66

  • – Wells: 0/19

  • – Spring: 0/19

 
Berrouch et al. (2023)  
Palestine Seawater Non-molecular Direct smear, concentration, and staining Marine water: 21/52 Hilles et al. (2014)  
Saudi Arabia DW 10 Molecular Nested PCR Total water samples: 15/228
  • – Wells: 7/96

  • – Bottled water: 0/60

  • – DsW: 8/72

 
Hawash et al. (2015)  
Tunisia Wastewater Non-molecular and molecular Filtration, modified Bailenger method, IMS-IFA, and nested PCR RWW: 6/7 TWW: 0/8 Ben Ayed Khouja et al. (2010)  
Wastewater Molecular Nested PCR RWW: 42/110 TWW: 14/110 Ben Ayed et al. (2012)  
CountrySerial no. of reportsType of water investigatedSampling volume (L)Method of detectionMethod applied for concentration and detectionNo. of contaminated/no. of totalReference
Egypt DW 0.6 to 1.5 Non-molecular N/R Bottled water: 0/84 Abd El-Salam et al. (2008)  
DW 0.1 Non-molecular N/R Public coolers: 3/20 Hussein et al. (2009)  
SF 10 Non-molecular and molecular Filtration, concentration, staining, and MAS – PCR Canal: 19/24 Rayan et al. (2009)  
DW Tap: 2/64 
SwP NM Non-molecular Filtration, centrifugation, and staining 1/30 Abd El-Salam (2012)  
Medical water 0.5 Non-molecular Filtration and staining Dental irrigation water: 11/40 Hassan et al. (2012)  
SF 0.01 Non-molecular Filtration, centrifugation, and staining Total water samples:63/246
  • – River: 15/48

  • – Waterworks: 10/48

  • – Pumps: 9/48

  • – Ponds: 17/48

  • – Canal: 12/48

 
Khalifa et al. (2014)  
DW Total water samples:18/96
  • – Tap: 6/48

  • – CRT: 12/48

 
DW 10 Non-molecular and molecular Filtration, staining, nested PCR, and PCR-RFLP Tap: 29/80 Hamdy et al. (2019)  
SwP Non-molecular Filtration and staining 27/78 Hassanein et al. (2023)  
SF 10 Non-molecular and molecular Filtration, centrifugation, IMS-IFA, and PCR *Cryptosporidium was detected in 20.83% of the inlet (SF) and outlet (tap) samples at the DTWP Moussa et al. (2023)  
DW 
10 DW 25 Non-molecular and molecular IMS – IFA and PCR Tap: 2/50 Abou Elez et al. (2023)  
Iran SF 10 Molecular Nested PCR and PCR-RFLP River: 6/30 Manouchehri et al. (2011)  
SF 10 Non-molecular and molecular Filtration, IFA, nested PCR, and LAMP River: 11/20 Mahmoudi et al. (2013)  
SF 2–50 Non-molecular and molecular Concentration, IMS, and nested PCR River: 24/49 Mahmoudi et al. (2015a)  
SF 50 Non-molecular IMS- IFA *Cryptosporidium was detected in 73.68% of investigated river samples Hadi et al. (2016)  
SwP Molecular Nested PCR 0/13 Ghasemi et al. (2019)  
SF 10 Non-molecular and molecular Filtration, staining, and PCR River: 17/42 Sharafi et al. (2023)  
Iraq DW 0.01–0.02 Non-molecular Direct wet smear, and staining Tap: 21/100 Al-Samarrai et al. (2022)  
Israel Seawater 10 Non-molecular IMS- IFA Marine water: 5/10 Nasser et al. (2003)  
Wastewater RWW: 0.2 Non-molecular and molecular Filtration, concentration, IFA, and nested PCR 21/43 Taran-Benshoshan et al. (2015)  
2nd TWW: 10 27/43 
3rd TWW: 25–50 17/25 
Jordan DW 15 Non-molecular Filtration, staining, and IFA HBT
  • – Underground cisterns: 4/52

  • – Concrete reservoir: 0/31

  • – Metal tanks: 0/149

 
Abo-Shehada et al. (2004)  
Lebanon DW Non-molecular Filtration, sucrose flotation, and IFA Total water samples: 30/55
  • – Wells: 4/11,

  • – Bottled water: (vendors: 17/32 & shop: 4/4)

  • – Tap: (school: 3/5 & municipality: 2/3).

 
Khoury et al. (2016)  
Morocco SF Non-molecular Direct spawning, modified Bailenger method, and Faust flotation Cryptosporidium was detected in 50% of river samples. Ouarrak et al. (2022)  
 DW 40 Molecular Filtration and real-time qPCR Total water samples: 0/144
  • – Tap: 0/66

  • – Wells: 0/19

  • – Spring: 0/19

 
Berrouch et al. (2023)  
Palestine Seawater Non-molecular Direct smear, concentration, and staining Marine water: 21/52 Hilles et al. (2014)  
Saudi Arabia DW 10 Molecular Nested PCR Total water samples: 15/228
  • – Wells: 7/96

  • – Bottled water: 0/60

  • – DsW: 8/72

 
Hawash et al. (2015)  
Tunisia Wastewater Non-molecular and molecular Filtration, modified Bailenger method, IMS-IFA, and nested PCR RWW: 6/7 TWW: 0/8 Ben Ayed Khouja et al. (2010)  
Wastewater Molecular Nested PCR RWW: 42/110 TWW: 14/110 Ben Ayed et al. (2012)  

DW, drinking water; DTWP, drinking water treatment plant; SwP, swimming pools; SF, surface water; PCR-RFLP, PCR-restriction fragment length polymorphism; IMS-IFA, immunomagnetic separation coupled with immunofluorescence assay; HBT, home-based tanks; 2nd TWW, secondary treated wastewater; 3rd TWW, tertiary treated wastewater; LAMP, lateral flow loop-mediated isothermal amplification technique; IFA, immunofluorescence assay; MAS – PCR, multiplex allele-specific; *Total was not reported; N/R, not reported.

For G. duodenalis, Egypt is the leading country with eight included studies (22.8%), followed by Iran and Tunisia (4/35; 11.4% for each), then, respectively, by Morocco and Israel (3/35; 8.5% for each), Iraq, Lebanon, Palestine, and Saudi Arabia (1/35; 2.8% for each) (Table 3).

Table 3

Reports on Giardia contamination of water bodies in the Middle East and North Africa (MENA) countries

CountrySerial no. of reportsType of water investigatedSampling volume (L)Method of detectionMethod applied for concentration and detectionNo. of contaminated/no. of totalReference
Egypt DW NM Non-molecular Filtration, centrifugation and microscopy Tap water: 3/899 Sullivan et al. (1988)  
DW 0.6–1.5 Non-molecular N/A Bottled water: 2/84 Abd El-Salam et al. (2008)  
SwP NM Non-molecular Filtration, centrifugation and staining 2/30 Abd El-Salam (2012)  
SF 0.01 Non-molecular Filtration, centrifugation and staining Total water samples 8/240 - River 3/48 - Waterworks 0/48 - Pumps 0/48 - Ponds 2/48 - Canal 3/48 Khalifa et al. (2014)  
DW Total water samples: 0/96 - Tap water: 0/48 - CRT 0/48 
DW 10 Non-molecular and molecular Filtration, staining, nested PCR and PCR-RFLP Tap water: 20/80 Hamdy et al. (2019)  
SF 10 Non-molecular and molecular Filtration, centrifugation, staining
nested PCR, semi-nested PCR and PCR – RFLP 
Canal: 10/10 Abd El-Latif et al. (2020)  
DW Tap: 0/40 
SwP Non-molecular Filtration and staining 17/78 Hassanein et al. (2023)  
SF 10 Non-molecular and molecular Filtration, centrifugation, IMS-IFA, and PCR Giardia was detected in 12.5% of samples in inlet (SF) and outlet (tap) water at DWTP* Moussa et al. (2023)  
DW 
Iran SF 10 Non-molecular and molecular Filtration, IFA, LAMP, and semi-nested PCR River:13/20 Mahmoudi et al. (2013)  
SF Non-molecular and molecular Filtration, IMS, sucrose flotation, and PCR River: 27/55 Mahmoudi et al. (2015b)  
SF 50 Non-molecular IMS- IFA Giardia was detected in 73.68% of river samples Hadi et al. (2016)  
SwP Molecular Nested PCR 0/13 Ghasemi et al. (2019)  
Iraq DW 0.01–0.02 Non-molecular Direct wet smear and staining Tap: 23/100 Al-Samarrai et al. (2022)  
Israel Sea water 10 Non-molecular IFA Marine water: 4/10 Nasser et al. (2003)  
Wastewater RWW: 0.2 Non-molecular and molecular Filtration, concentration, IFA & nested PCR RWW: 42/43 Taran-Benshoshan et al. (2015)  
2nd TWW: 10 2nd TWW: 26/43 
3rd TWW: 25–50 Tertiary TWW: 19/25 
Wastewater RWW: 1 Non-molecular Filtration, centrifugation, and IMS-IFA Giardia was detected in 100% of RWW* Nasser et al. (2017)  
3rd TWW: 50 Absence* 
Lebanon DW Non-molecular Filtration, sucrose flotation &IFA Total water samples 28/55
  • – Wells: 6/1

  • – Bottled water: (vendors: 16/32 + +Shop: 2/4)

  • – Tap water (municipality: 2/3 + school: 2/5)

 
Khoury et al. (2016)  
Morocco Wastewater RWW: 1 Non-molecular Modified Bailenger Method RWW: 42/42 Bourouache et al. (2021)  
2nd and 3rd TWW: 10 3rd TWW: 0/21 
SF Non-molecular Direct spawning, concentration and Faust flotation Giardia was detected in 100% of river samples. Ouarrak et al. (2022)  
DW 40 Molecular Filtration and real-time qPCR Total water samples: 35/104
  • – Tap: 47/66

  • – Wells: 3/19

  • – Spring: 2/19

 
Berrouch et al. (2023)  
Palestine Sea water Non-molecular Direct smear, concentration, and staining Marine water: 1/52 Hilles et al. (2014)  
Saudi Arabia DW 10 Molecular Nested PCR Total water samples: 16/228
  • – Wells: 9/96

  • – Bottled water: 0/60

  • – DsW: 7/72

 
Hawash et al. (2015)  
Tunisia Wastewater Non-molecular Modified Bailenger method RWW: 174/174
TWW: 13/174 
Ben Ayed et al. (2009)  
Wastewater Non-molecular and molecular Filtration, modified Bailenger method, IMS-IFA, and nested PCR RWW: 6/7
TWW: 4/8 
Ben Ayed Khouja et al. (2010)  
Wastewater Molecular Nested PCR RWW: 47/110
TWW: 15/110 
Ben Ayed et al. (2012)  
DW Non-molecular Modified Bailenger method Underground HBT: 36/39 Ben Ayed et al. (2018)  
CountrySerial no. of reportsType of water investigatedSampling volume (L)Method of detectionMethod applied for concentration and detectionNo. of contaminated/no. of totalReference
Egypt DW NM Non-molecular Filtration, centrifugation and microscopy Tap water: 3/899 Sullivan et al. (1988)  
DW 0.6–1.5 Non-molecular N/A Bottled water: 2/84 Abd El-Salam et al. (2008)  
SwP NM Non-molecular Filtration, centrifugation and staining 2/30 Abd El-Salam (2012)  
SF 0.01 Non-molecular Filtration, centrifugation and staining Total water samples 8/240 - River 3/48 - Waterworks 0/48 - Pumps 0/48 - Ponds 2/48 - Canal 3/48 Khalifa et al. (2014)  
DW Total water samples: 0/96 - Tap water: 0/48 - CRT 0/48 
DW 10 Non-molecular and molecular Filtration, staining, nested PCR and PCR-RFLP Tap water: 20/80 Hamdy et al. (2019)  
SF 10 Non-molecular and molecular Filtration, centrifugation, staining
nested PCR, semi-nested PCR and PCR – RFLP 
Canal: 10/10 Abd El-Latif et al. (2020)  
DW Tap: 0/40 
SwP Non-molecular Filtration and staining 17/78 Hassanein et al. (2023)  
SF 10 Non-molecular and molecular Filtration, centrifugation, IMS-IFA, and PCR Giardia was detected in 12.5% of samples in inlet (SF) and outlet (tap) water at DWTP* Moussa et al. (2023)  
DW 
Iran SF 10 Non-molecular and molecular Filtration, IFA, LAMP, and semi-nested PCR River:13/20 Mahmoudi et al. (2013)  
SF Non-molecular and molecular Filtration, IMS, sucrose flotation, and PCR River: 27/55 Mahmoudi et al. (2015b)  
SF 50 Non-molecular IMS- IFA Giardia was detected in 73.68% of river samples Hadi et al. (2016)  
SwP Molecular Nested PCR 0/13 Ghasemi et al. (2019)  
Iraq DW 0.01–0.02 Non-molecular Direct wet smear and staining Tap: 23/100 Al-Samarrai et al. (2022)  
Israel Sea water 10 Non-molecular IFA Marine water: 4/10 Nasser et al. (2003)  
Wastewater RWW: 0.2 Non-molecular and molecular Filtration, concentration, IFA & nested PCR RWW: 42/43 Taran-Benshoshan et al. (2015)  
2nd TWW: 10 2nd TWW: 26/43 
3rd TWW: 25–50 Tertiary TWW: 19/25 
Wastewater RWW: 1 Non-molecular Filtration, centrifugation, and IMS-IFA Giardia was detected in 100% of RWW* Nasser et al. (2017)  
3rd TWW: 50 Absence* 
Lebanon DW Non-molecular Filtration, sucrose flotation &IFA Total water samples 28/55
  • – Wells: 6/1

  • – Bottled water: (vendors: 16/32 + +Shop: 2/4)

  • – Tap water (municipality: 2/3 + school: 2/5)

 
Khoury et al. (2016)  
Morocco Wastewater RWW: 1 Non-molecular Modified Bailenger Method RWW: 42/42 Bourouache et al. (2021)  
2nd and 3rd TWW: 10 3rd TWW: 0/21 
SF Non-molecular Direct spawning, concentration and Faust flotation Giardia was detected in 100% of river samples. Ouarrak et al. (2022)  
DW 40 Molecular Filtration and real-time qPCR Total water samples: 35/104
  • – Tap: 47/66

  • – Wells: 3/19

  • – Spring: 2/19

 
Berrouch et al. (2023)  
Palestine Sea water Non-molecular Direct smear, concentration, and staining Marine water: 1/52 Hilles et al. (2014)  
Saudi Arabia DW 10 Molecular Nested PCR Total water samples: 16/228
  • – Wells: 9/96

  • – Bottled water: 0/60

  • – DsW: 7/72

 
Hawash et al. (2015)  
Tunisia Wastewater Non-molecular Modified Bailenger method RWW: 174/174
TWW: 13/174 
Ben Ayed et al. (2009)  
Wastewater Non-molecular and molecular Filtration, modified Bailenger method, IMS-IFA, and nested PCR RWW: 6/7
TWW: 4/8 
Ben Ayed Khouja et al. (2010)  
Wastewater Molecular Nested PCR RWW: 47/110
TWW: 15/110 
Ben Ayed et al. (2012)  
DW Non-molecular Modified Bailenger method Underground HBT: 36/39 Ben Ayed et al. (2018)  

DW, drinking water; SwP, swimming pools; DTWP, drinking water treatment plant; SF, surface water; IMS – IFA, immunomagnetic separation coupled with immunofluorescence assay; HBT, home-based tanks; 2nd TWW, secondary treated wastewater; 3rd TWW, tertiary treated wastewater; LAMP, lateral flow loop-mediated isothermal amplification technique; IFA, immunofluorescence assay; *Total was not reported; N/R, not reported; NM, not mentioned.

Following eligibility criteria screening, five studies ‘Hadi et al. (2016), Hassan et al. (2012), Moussa et al. (2023), Nasser et al. (2017) and Ouarrak et al. (2022)’ were excluded from the current meta-analysis for several reasons: (i) Hadi et al. (2016), Nasser et al. (2017) and Ouarrak et al. (2022) failed to report the required numeric values; (ii) results of Moussa et al. (2023) were reported as dependent pooling different water categories; (iii) Hassan et al. (2012) is the only study that focused on medical water type. The classification of wastewater into RWW, 2nd TWW, and 3rd TWW sources is based on the distinct properties and characteristics of raw and TWW, which prompted the division of this water category, since Taran-Benshoshan et al. (2015) reported the 3rd TWW only once it was merged with the 2nd TWW to form the sole TWW subgroup.

Burden of Cryptosporidium sp. and G. duodenalis in MENA region water resources/categories

Almost all water categories in the MENA region were contaminated with Cryptosporidium sp. and G. duodenalis (oo)cysts.

Prevalence of Cryptosporidium sp. in the MENA water resources/categories

The number of Cryptosporidium-contaminated water types is detailed in Table 2 and Figure 2. When all the studies were incorporated, the overall random proportion meta-analysis revealed the prevalence of Cryptosporidium sp. within the various water categories at 24.6% (95% CI 16.3–33.8) based on an arbitrary proportional estimate of the combined 2,284 sample sizes derived from the 30 included studies. Since we observed a statistically significant heterogeneity index (Q: 671.8; p (Q): < 0.0001), a dependable subgrouping meta-analysis was conducted for each investigated type of water source, as detailed in Table S1 (Supplementary File, Table S1). Publication bias was identified in the seawater category (p (E): < 0.0001). This may be attributed to the limited number of studies included in the analysis, as only two studies (Nasser et al. 2003; Hilles et al. 2014) focused on this type of water. The proportional prevalence of Cryptosporidium sp. ranged from 10.8 to 50.3% and decreased progressively from RWW, SF, seawater, TWW, and SwP, with DW being the least contaminated source (Figure 2).
Figure 2

Proportional prevalence of Cryptosporidium sp. incidence within the different water categories. The descending order of prevalence by water category is denoted by numerical arrangement.

Figure 2

Proportional prevalence of Cryptosporidium sp. incidence within the different water categories. The descending order of prevalence by water category is denoted by numerical arrangement.

Close modal

Prevalence of G. duodenalis in MENA water resources/categories

G. duodenalis water contamination was reported within nine MENA countries, including five water categories (Table 3 and Figure 3). G. duodenalis prevalence was estimated to be 37.7% (95% CI: 21.9 to 55.1) based on a random proportional estimate of the combined 2,969 sample sizes derived from the 29 included studies. The selected data similarly demonstrated heterogeneity in Cryptosporidium (Q = 2,389.9; P < 0.0001). Therefore, we investigated correlations within water categories. Consistent with the findings of the Cryptosporidium sp. analysis, publication bias was identified within the seawater category as well (p (E) < 0.0001) (Supplementary File, Table S1). Comparable to Cryptosporidium, the two most contaminated sources were RWW and SF, with proportions of G. duodenalis ranging from 10.4 to 93.2%. Conversely, the prevalence of G. duodenalis decreases progressively and drastically in SwP, the least contaminated water source, compared to TWW, DW, and seawater (Figure 3).
Figure 3

Proportional prevalence of G. duodenalis incidence within the different water categories. The descending order of prevalence by water category is denoted by numerical arrangement.

Figure 3

Proportional prevalence of G. duodenalis incidence within the different water categories. The descending order of prevalence by water category is denoted by numerical arrangement.

Close modal

Methods applied and genotypes of Cryptosporidium sp. and G. duodenalis in MENA water resources/categories

The included studies of MENA used non-molecular (NM) and molecular methods to detect Cryptosporidium sp. and G. duodenalis (oo)cysts in their water resources and categories.

For Cryptosporidium sp., NM methods were used in 20 (57.14%) studies, while molecular techniques were used in 14 (40%). Nine studies (25.71%) combined both methods (Table 2). G. duodenalis was identified by NM techniques in 22 studies (62.85%) and by molecular ones in 11 studies (31.42%). Seven studies used both techniques (Table 3).

The MENA studies meticulously prepared water samples using a variety of concentration (sedimentation, for example, modified Bailenger method, Faust flotation) and filtration (cartridge filters) techniques. The NM methods employed included wet mount examination (saline and iodine), modified Ziehl–Nielsen staining (mZN), enzyme-linked immune-sorbent assays (ELISA), coagulation tests, and immunomagnetic separation followed by immunofluorescent technique (IMS-IFT), all of which were instrumental in detecting (oo)cysts in water samples.

Various molecular methods were applied within the MENA studies to detect the parasites in the concentrated water samples. Polymerase chain reaction (PCR) (nested, semi-nested, multiplex allele-specific, coupled with restriction fragment length polymorphism), lateral flow loop-mediated LAMP (isothermal amplification technique), and sequencing were explicitly applied for the identification, genotyping, and subtyping of Cryptosporidium sp. and G. duodenalis (oo)cysts (Tables 4 and 5).

Table 4

Molecular results of Cryptosporidium sp. in the Middle East and North Africa (MENA) water samples

CountryType of water samplesTarget geneSpecies identifiedGenotype/SubtypeReference
Egypt SF (canal)
DW (tap and HBT) 
DhR C. parvum, C. hominis N/R Rayan et al. (2009)  
DW (tap) COWP C. parvum, C. hominis N/R Hamdy et al. (2019)  
DW (tap) SSU rRNA
Actin gene 
C. parvum N/R Abou Elez et al. (2023)  
Iran SF (river) SSU rRNA C. parvum, C. hominis, and C. canis N/R Manouchehri et al. (2011)  
SF (river) SSU rRNA
gp60 
C. parvum, C. hominis, C. muris, C. andersoni, and C. canis C. parvum/ IId,
C. hominis/ Id 
Mahmoudi et al. (2015a)  
SF (river) SSU rRNA C. parvum N/R Sharafi et al. (2023)  
Israel Wastewater (RWW, 2nd TWW, and 3rd TWW) SSU rRNA C. parvum/bovis, C. hominis, C. andersoni, C. muris, and C. meleagridis N/R Taran-Benshoshan et al. (2015)  
Tunisia Wastewater (RWW and TWW) SSU rRNA
PCR – RFLP
gp60 
C. parvum, C. hominis, and
C. muris/C. andersoni 
C. hominis/ IaA27R3, IdA15G1
C. parvum/ IIaA21R1, IIcA5G3b 
Ben Ayed Khouja et al. (2010)  
Wastewater (RWW, and TWW) SSU rRNA
gp60 
C. parvum,
C. muris,
C. andersoni,
C. hominis, C. ubiquitum, rat genotype IV, unknown Cryptosporidium, sheep genotype, C. meleagridis, and avian genotype II 
C. hominis/
Ia, Id
C. parvum/
IIa, IIc 
Ben Ayed et al. (2012)  
CountryType of water samplesTarget geneSpecies identifiedGenotype/SubtypeReference
Egypt SF (canal)
DW (tap and HBT) 
DhR C. parvum, C. hominis N/R Rayan et al. (2009)  
DW (tap) COWP C. parvum, C. hominis N/R Hamdy et al. (2019)  
DW (tap) SSU rRNA
Actin gene 
C. parvum N/R Abou Elez et al. (2023)  
Iran SF (river) SSU rRNA C. parvum, C. hominis, and C. canis N/R Manouchehri et al. (2011)  
SF (river) SSU rRNA
gp60 
C. parvum, C. hominis, C. muris, C. andersoni, and C. canis C. parvum/ IId,
C. hominis/ Id 
Mahmoudi et al. (2015a)  
SF (river) SSU rRNA C. parvum N/R Sharafi et al. (2023)  
Israel Wastewater (RWW, 2nd TWW, and 3rd TWW) SSU rRNA C. parvum/bovis, C. hominis, C. andersoni, C. muris, and C. meleagridis N/R Taran-Benshoshan et al. (2015)  
Tunisia Wastewater (RWW and TWW) SSU rRNA
PCR – RFLP
gp60 
C. parvum, C. hominis, and
C. muris/C. andersoni 
C. hominis/ IaA27R3, IdA15G1
C. parvum/ IIaA21R1, IIcA5G3b 
Ben Ayed Khouja et al. (2010)  
Wastewater (RWW, and TWW) SSU rRNA
gp60 
C. parvum,
C. muris,
C. andersoni,
C. hominis, C. ubiquitum, rat genotype IV, unknown Cryptosporidium, sheep genotype, C. meleagridis, and avian genotype II 
C. hominis/
Ia, Id
C. parvum/
IIa, IIc 
Ben Ayed et al. (2012)  

DW, drinking water; SF, surface water; HBT, home-based tanks; COWP, Cryptosporidium oocyst wall protein; SSU rRNA, small subunit ribosomal RNA; gp60, 60-kDa glycoprotein; RWW, raw wastewater; TWW, treated wastewater; N/R, not reported; 2nd TWW, secondary treated wastewater; 3rd TWW, tertiary treated wastewater.

Table 5

Molecular results of G. duodenalis in the Middle East and North Africa (MENA) water samples

CountryType of water samplesMolecular method(s)Target geneSubtypesReference
Egypt DW (tap) and SF (canal) nPCR, semi-nPCR, and PCR-RFLP tpi
gdh 
Assem. AII Abd El-Latif et al. (2020)  
DW (tap) nPCR and PCR-RFLP bg Assem. A and B Hamdi et al. (2019)  
Iran SF (river) semi-nPCR gdh Assem. B Mahmoudi et al. (2015b)  
Tunisia Wastewater (RWW and TWW) nPCR tpi Assem. A (A-I/ A-II) and B (WB8/WB7) Ben Ayed Khouja et al. (2010)  
Wastewater (RWW and TWW) nPCR tpi Assem. A (A1, A2), B (B7, B8), and E Ben Ayed et al. (2012)  
CountryType of water samplesMolecular method(s)Target geneSubtypesReference
Egypt DW (tap) and SF (canal) nPCR, semi-nPCR, and PCR-RFLP tpi
gdh 
Assem. AII Abd El-Latif et al. (2020)  
DW (tap) nPCR and PCR-RFLP bg Assem. A and B Hamdi et al. (2019)  
Iran SF (river) semi-nPCR gdh Assem. B Mahmoudi et al. (2015b)  
Tunisia Wastewater (RWW and TWW) nPCR tpi Assem. A (A-I/ A-II) and B (WB8/WB7) Ben Ayed Khouja et al. (2010)  
Wastewater (RWW and TWW) nPCR tpi Assem. A (A1, A2), B (B7, B8), and E Ben Ayed et al. (2012)  

DW, drinking water; SF, surface water; tpi, triosephosphate isomerase; gdh, glutamate dehydrogenase gene; bg, β-giardin; RWW, raw wastewater; TWW, treated wastewater; nPCR, nested polymerase chain reaction; Assemb, assemblage.

Twelve genotypes and nine Cryptosporidium subtypes were identified in nine studies in the MENA water resources. They were reported only in SF, DW, and wastewater. C. hominis and C. parvum were the most frequently reported species. G. duodenalis assemblages A, B, and E were detected in five studies in the MENA water categories, with assemblage A being the most prevalent (Tables 4 and 5).

Water volume investigated and (oo)cysts concentrations in MENA water resources/categories

To determine the presence of Cryptosporidium sp. and G. duodenalis in water samples, the volume collected varied from one water category to the other. The volume of the water samples used to purify these two protozoa ranged between 0.01 and 40 L for DW, 0.01 and 50 L for SF, 5 and 8 L for SwP, 4 and 10 L for seawater; 0.5 L for medical water only for Cryptosporidium; 0.2 and 5 L for RWW; 5 and 10 L for 2nd TWW and finally between 25 and 50 L for 3rd TWW (Tables 2 and 3).

The concentration of (oo)cysts of Cryptosporidium sp. and G. duodenalis in MENA water categories was reported in a diverse range of studies, with 13 and 9 studies, respectively (Tables 6 and 7). The concentration of Cryptosporidium oocysts was determined in SF, SwP, DW, RWW, 2ndTWW, and 3rd TWW, with a wide range of values. It ranged from 0.001 to 450 oocysts/L in SF, 0 to 50 oocysts/L in DW, 0.1 to 124.5 oocysts/L in 2nd TWW, and between 0.03 and 5.4 oocysts/L for 3rd TWW. The lowest concentration was recorded in SwP with 0.166 oocysts/L and RWW with 17.3 oocysts/L.

Table 6

Cryptosporidium sp. oocysts concentration/liter of water categories of the Middle East and North Africa (MENA)

Country/CityType of waterCryptosporidium (oocyst/L)Reference
Egypt/Alexandria and Cairo DW (tap) N/I Abd El-Salam et al. (2008)  
Egypt/Alexandria DW (tap) N/I Hussein et al. (2009)  
Egypt SF (Canal) 50–450 Rayan et al. (2009)  
DW (tap) 20–30 
Egypt/Alexandria SwP N/I Abd El-Salam (2012)  
Egypt/Alexandria Medical N/I Hassan et al. (2012)  
Egypt/El Minia DW (tap) 0.355 Khalifa et al. (2014)  
SwP 0.166 
DW (CRT) 0.253–0.744 
SF (canal) 0.177–0.512 
Egypt/Beni Suef DW N/I Hamdy et al. (2019)  
Egypt/Alexandria SwP N/I Hassanein et al. (2023)  
Egypt/Cairo DW ≤ 3 oocysts/10L Moussa et al. (2023)  
Egypt DW N/I Abou Elez et al. (2023)  
Iran/Shahrekord SF (river) N/I Manouchehri et al. (2011)  
Iran/Rasht SF (river) 0.1–1.6 Mahmoudi et al. (2013)  
Iran/Guilan and Tehran SF (river) N/I Mahmoudi et al. (2015a)  
Iran/Tehran SF (river) 0.001–0.011 Hadi et al. (2016)  
Iran/Shiraz SwP N/I Ghasemi et al. (2019)  
Iran SF (river) N/I Sharafi et al. (2023)  
Iraq/Samarra DW (tap) N/I Al-Samarrai et al. (2022)  
Israel/Ramat Gan Seawater N/I Nasser et al. (2003)  
Israel Wastewater RWW: 17.3 Taran-Benshoshan et al. (2015)  
2nd TWW: 0.1–124.5 
3rd TWW: 0.03–5.4 
Jordan/Bani-Kenanh DW (HBT) 6–50 Abo-Shehada et al. (2004)  
Lebanon/Beirut DW (tap, wells) 0–5 Khoury et al. (2016)  
Morocco/Meknes SF (river) 0.12 × 103–0.3 × 103 Ouarrak et al. (2022)  
Morocco/Marrakesh DW (tap, wells, and spring) N/I Berrouch et al. (2023)  
Palestine /Gaza Seawater N/I Hilles et al. (2014)  
Saudi Arabia/Taif DW (DsW, wells, tap) N/I Hawash et al. (2015)  
Tunisia/Tunis Wastewater 1–21 Ben Ayed Khouja et al. (2010)  
Tunisia/All the country Wastewater N/I Ben Ayed et al. (2012)  
Country/CityType of waterCryptosporidium (oocyst/L)Reference
Egypt/Alexandria and Cairo DW (tap) N/I Abd El-Salam et al. (2008)  
Egypt/Alexandria DW (tap) N/I Hussein et al. (2009)  
Egypt SF (Canal) 50–450 Rayan et al. (2009)  
DW (tap) 20–30 
Egypt/Alexandria SwP N/I Abd El-Salam (2012)  
Egypt/Alexandria Medical N/I Hassan et al. (2012)  
Egypt/El Minia DW (tap) 0.355 Khalifa et al. (2014)  
SwP 0.166 
DW (CRT) 0.253–0.744 
SF (canal) 0.177–0.512 
Egypt/Beni Suef DW N/I Hamdy et al. (2019)  
Egypt/Alexandria SwP N/I Hassanein et al. (2023)  
Egypt/Cairo DW ≤ 3 oocysts/10L Moussa et al. (2023)  
Egypt DW N/I Abou Elez et al. (2023)  
Iran/Shahrekord SF (river) N/I Manouchehri et al. (2011)  
Iran/Rasht SF (river) 0.1–1.6 Mahmoudi et al. (2013)  
Iran/Guilan and Tehran SF (river) N/I Mahmoudi et al. (2015a)  
Iran/Tehran SF (river) 0.001–0.011 Hadi et al. (2016)  
Iran/Shiraz SwP N/I Ghasemi et al. (2019)  
Iran SF (river) N/I Sharafi et al. (2023)  
Iraq/Samarra DW (tap) N/I Al-Samarrai et al. (2022)  
Israel/Ramat Gan Seawater N/I Nasser et al. (2003)  
Israel Wastewater RWW: 17.3 Taran-Benshoshan et al. (2015)  
2nd TWW: 0.1–124.5 
3rd TWW: 0.03–5.4 
Jordan/Bani-Kenanh DW (HBT) 6–50 Abo-Shehada et al. (2004)  
Lebanon/Beirut DW (tap, wells) 0–5 Khoury et al. (2016)  
Morocco/Meknes SF (river) 0.12 × 103–0.3 × 103 Ouarrak et al. (2022)  
Morocco/Marrakesh DW (tap, wells, and spring) N/I Berrouch et al. (2023)  
Palestine /Gaza Seawater N/I Hilles et al. (2014)  
Saudi Arabia/Taif DW (DsW, wells, tap) N/I Hawash et al. (2015)  
Tunisia/Tunis Wastewater 1–21 Ben Ayed Khouja et al. (2010)  
Tunisia/All the country Wastewater N/I Ben Ayed et al. (2012)  

SwP, swimming pools; DW, drinking water; HBT, home-based tanks; CRT, city reservoir tanks; RWW, raw wastewater; 2nd TWW, secondary treated wastewater; 3rd TWW, tertiary treated wastewater; SF, surface water; N/I, not investigated.

Table 7

G. duodenalis cysts concentration/liter of water categories of the Middle East and North Africa (MENA)

Country/CityType of waterGiardiaReference
Egypt DW (tap water) N/I Sullivan et al. (1988)  
Egypt/Alexandria and Cairo DW (tap water) N/I Abd El-Salam et al. (2008)  
Egypt/Alexandria SwP 220 Abd El-Salam (2012)  
Egypt/El Minia SF (river, waterworks, pumps, ponds, canal)
DW (tap, CRT) 
N/I Khalifa et al. (2014)  
Egypt/Beni Suef DW (tap water) N/I Hamdy et al. (2019)  
Egypt/El-Beheira SF (canal)
DW (tap) 
N/I Abd El-Latif et al. (2020)  
Egypt/Alexandria SwP N/I Hassanein et al. (2023)  
Egypt/Cairo SF (river)
DW (tap) 
N/I Moussa et al. (2023)  
Iran/Rasht SF (river) 0.1–180 Mahmoudi et al. (2013)  
Iran/ Tehran and Guilan SF (river) NI Mahmoudi et al. (2015b)  
Iran/ Tehran SF (river) 0–1.380 Hadi et al. (2016)  
Iran/Shiraz SwP N/I Ghasemi et al. (2019)  
Iraq/Samarra DW (tap) N/I Al-Samarrai et al. (2022)  
Israel/Ramat Gan Seawater N/I Nasser et al. (2003)  
Israel Wastewater 10–12,225 Taran-Benshoshan et al. (2015)  
Israel Wastewater RWW: 0.1–91 Nasser et al. (2017)  
TWW: 0.02–7.75 
Lebanon/Beirut DW Well: 0–1
Vendor: 0–5
Shop: 0–3
Pre-school: 0–2 
Khoury et al. (2016)  
Morocco/Agadir Wastewater N/I Bourouache et al. (2021)  
Morocco/Meknes SF (river) N/I Ouarrak et al. (2022)  
Morocco/Marrakech DW (tap, wells, and spring) N/I Berrouch et al. (2023)  
Palestine/Gaza Seawater N/I Hilles et al. (2014)  
Saudi Arabia/Taif DW (wells and tap) N/I Hawash et al. (2015)  
Tunisia/All the country Wastewater RWW: 538–1,200 Ben Ayed et al. (2009)  
TWW: 0–417 
Tunisia/Tunis Wastewater 66–320 Ben Ayed Khouja et al. (2010)  
Tunisia/Kairouan DW (HBT) 13–393 Ben Ayed et al. (2018)  
Country/CityType of waterGiardiaReference
Egypt DW (tap water) N/I Sullivan et al. (1988)  
Egypt/Alexandria and Cairo DW (tap water) N/I Abd El-Salam et al. (2008)  
Egypt/Alexandria SwP 220 Abd El-Salam (2012)  
Egypt/El Minia SF (river, waterworks, pumps, ponds, canal)
DW (tap, CRT) 
N/I Khalifa et al. (2014)  
Egypt/Beni Suef DW (tap water) N/I Hamdy et al. (2019)  
Egypt/El-Beheira SF (canal)
DW (tap) 
N/I Abd El-Latif et al. (2020)  
Egypt/Alexandria SwP N/I Hassanein et al. (2023)  
Egypt/Cairo SF (river)
DW (tap) 
N/I Moussa et al. (2023)  
Iran/Rasht SF (river) 0.1–180 Mahmoudi et al. (2013)  
Iran/ Tehran and Guilan SF (river) NI Mahmoudi et al. (2015b)  
Iran/ Tehran SF (river) 0–1.380 Hadi et al. (2016)  
Iran/Shiraz SwP N/I Ghasemi et al. (2019)  
Iraq/Samarra DW (tap) N/I Al-Samarrai et al. (2022)  
Israel/Ramat Gan Seawater N/I Nasser et al. (2003)  
Israel Wastewater 10–12,225 Taran-Benshoshan et al. (2015)  
Israel Wastewater RWW: 0.1–91 Nasser et al. (2017)  
TWW: 0.02–7.75 
Lebanon/Beirut DW Well: 0–1
Vendor: 0–5
Shop: 0–3
Pre-school: 0–2 
Khoury et al. (2016)  
Morocco/Agadir Wastewater N/I Bourouache et al. (2021)  
Morocco/Meknes SF (river) N/I Ouarrak et al. (2022)  
Morocco/Marrakech DW (tap, wells, and spring) N/I Berrouch et al. (2023)  
Palestine/Gaza Seawater N/I Hilles et al. (2014)  
Saudi Arabia/Taif DW (wells and tap) N/I Hawash et al. (2015)  
Tunisia/All the country Wastewater RWW: 538–1,200 Ben Ayed et al. (2009)  
TWW: 0–417 
Tunisia/Tunis Wastewater 66–320 Ben Ayed Khouja et al. (2010)  
Tunisia/Kairouan DW (HBT) 13–393 Ben Ayed et al. (2018)  

SwP, swimming pools; DW, drinking water; HBT, home-based tanks; CRT, city reservoir tanks; RWW, raw wastewater; TWW, treated wastewater; SF, surface water; N/I, not investigated.

G. duodenalis cysts were determined in high concentrations in RWW, ranging from 10 to 12.225 cysts/L, and in the lowest ones in 3rd TWW, ranging from 0.02 to 7.75 cysts/L.

The current review provides insights into the prevalence and distribution of Cryptosporidium sp. and G. duodenalis in water resources/bodies/categories within the MENA region.

MENA countries reporting data and related risk factors

Cryptosporidium sp. and G. duodenalis contamination of water resources and categories was reported in 10 and 9 MENA countries. Regarding the number of studies included, Egypt has topped the MENA region, with Iran followed by Tunisia, Morocco, Israel, Iraq, Lebanon, Palestine, and Saudi Arabia. Egypt also led the statements in another review that dealt with waterborne parasites in Africa with 36/120 articles (Ahmed et al. 2018). There is a possibility that the increased reporting of the parasites' water contamination is mandated by the legislation of the Egyptian Ministry of Health & Population ( https://www.mohp.gov.eg/theducation/SecondGroup/Counseling_and_health_education/Term1/Environmental_health_and_lifestyle/Environmental_health_and_lifestyle.pdf).

The reporting system appears unrelated to high financial and diagnostic capabilities, returning instead to each country's stockholders' awareness of the current burden of parasites and their consequences. Almost half of the MENA countries (Algeria, Bahrain, Kuwait, Libya, Oman, Qatar, Syria, UAE, and Yemen) have not reported studies on the presence of Cryptosporidium sp. and G. duodenalis in their water resources/categories, reflecting MENA countries' underestimation of the magnitude of the water contamination problem and the common waterborne outbreaks.

Several risk factors have been linked to Cryptosporidium sp. and G. duodenalis in the MENA region. Poverty, illiteracy, population density, political conflicts, water crisis, social unrest, lack of waste management, excessive use of manure in agriculture, lack of hygiene and sanitation, poor water treatment, unclean water, climate change, contact with animals, and host susceptibility were all reported risk factors in the MENA (Iqbal et al. 2001; Lal et al. 2012; GBD 2015; Shalaby & Shalaby 2015; Aldeyarbi et al. 2016; Sterk et al. 2016; Ahmed et al. 2018, 2023; Gawad et al. 2018; Ahmed & Karanis 2020).

Burden of Cryptosporidium sp. and G. duodenalis in MENA water resources/categories

Overall prevalence of Cryptosporidium sp. and G. duodenalis in MENA water resources/categories

The MENA water resources/categories in this review exhibited a prevalence of 24.5% for Cryptosporidium sp. and 37.7% for G. duodenalis. These protozoa were identified in 2,284 and 2,969 water samples, respectively.

Evidenced by previous studies in the MENA region, the waterborne parasitic outbreaks are highly anticipated due to several factors: (i) contamination of water sources, supplies, and reservoirs, (ii) swimming in contaminated recreational water, and (iii) absence or a lack of coordination of the surveillance system (Abo-Shehada et al. 2004; Karanis et al. 2007; Baldursson & Karanis 2011; Hussein 2011; Abd El-Salam 2012; Hawash et al. 2015; Efstratiou et al. 2017a, 2017b; Ben Ayed et al. 2018).

Despite the factors above and the high prevalence in the current review, there have been no documented waterborne outbreaks caused by Cryptosporidium. and G. duodenalis in the MENA region, a paradox that underscores the urgent need for improved surveillance systems. This fact has been substantiated by the four comprehensive reviews conducted by Karanis et al. (2007), Baldursson & Karanis (2011), Efstratiou et al. (2017a) and Bourli et al. (2023).

Prevalence of Cryptosporidium sp. and G. duodenalis by water type, factors involved, and treatment processes

Raw wastewater (RWW) and surface water were the highest water resources/categories contaminated with Cryptosporidium sp. and G. duodenalis (oo)cysts.

The high prevalence of Cryptosporidium sp. and G. duodenalis in MENA RWW could be linked to several factors: (i) the source of the influent, (ii) the sanitation conditions and the socio-economic situation, (iii) the level of annual rainfall, (iv) the population size and the intensity of the infection within the inhabitants, and (v) the (oo)cysts survival and resistance to hostile conditions (Ben Ayed Khouja et al. 2010; Ben Ayed et al. 2012; Nasser et al. 2012). The prevalence of G. duodenalis was reported to be higher than that of Cryptosporidium sp. in the RWW of MENA, as has been previously reported in both developing and developed countries (Santos et al. 2004; Lim et al. 2007; Fu et al. 2010). This may be attributed to the lower infection rate of cryptosporidiosis in the investigated communities or to the detection techniques used in such studies (Stott et al. 2003).

The treatment processes applied depend on the wastewater composition or resource recovery processes (Mateo-Sagasta et al. 2022). In MENA countries, 60% of the domestically generated wastewater is treated (Mateo-Sagasta et al. 2022). The wastewater treatment processes comprise three phases in the MENA region: primary, secondary, and tertiary. For industrial effluents, a conventional pretreatment could be implemented before the primary treatment, which may involve a primary settlement or a coagulation-flocculation process. The secondary treatment process is primarily biological and includes activated sludge, oxidation channels, lagoons and ponds, trickling filters, and constructed wetlands (Ben Ayed et al. 2009; Abdel-Shafy & Dewedar 2012; Salama et al. 2014). Due to its high cost, the tertiary treatment process is implemented in a few countries (ex. Tunisia, and Egypt) of the MENA region (Ben Ayed et al. 2009; Micheal et al. 2022). It can remove nutrients or disinfection (UV, ozonation, filtration, chlorination, photocatalytic oxidation) (Ben Ayed et al. 2009). More technological treatments are applied in the industrial sector of MENA (ex., Saudi Arabia) using ultrafiltration with reverse osmosis or membrane bioreactor (Alahdal et al. 2021). Currently, the primary and secondary wastewater treatment processes in the MENA region are not sufficient to disinfect wastewater from Cryptosporidium sp. and Giardia duodenalis (Ben Ayed et al. 2009, 2012; Bourouache et al. 2021). Nevertheless, tertiary treatment may eradicate them (Bouhoum et al. 2000).

Surface water was clustered in the current review into rivers, canals, ponds, water pumps, and water works. In the MENA region, SF clusters were the second most contaminated water resource with (oo)cysts, following RWW. Other studies in MENA have confirmed this (Goher et al. 2014; Radwan et al. 2019). Surface water is the principal supply of irrigation and, more importantly, DW in Egypt and Tunisia, originating in the Nile and Medjerda Rivers, both of which are polluted by urban, industrial, and agricultural activities (Khalifa et al. 2014; Ben Ayed et al. 2022a, 2022b). In some Egyptian districts, sewage and industrial effluents could be released directly into the Nile River or with limited treatment (Sakran et al. 2017). In Tunisia, heavy metals and bacteria contaminated water and sediment samples (Ben Ayed et al. 2022a, 2022b). Such actions pose a substantial public health risk.

The current review clustered DW into various types: tap water, cooler water, bottled water (from shops, vendors, and mineral water), city reservoir tanks, roof/underground home-based tanks (HBT), wells, springs, and desalinated water. DW (potable water) was the least contaminated water category in MENA with Cryptosporidium sp. and the third least contaminated with G. duodenalis. Their (oo)cysts presence in DW may be connected with their small size and capacity to tolerate treatment processes (chlorination). Removing these two protozoa is a challenge for drinking water disinfection.

Water can be commonly stored in HBT or reservoirs, which can be underground or on the roof, and this will be useful in times of prolonged drought. This is a common practice in the MENA region. Home-based tank water is used for drinking, food preparation, personal hygiene, and utensils cleaning (Sakran et al. 2017; Ben Ayed et al. 2018). These household tanks could be filled with (i) roof-harvested rainwater, (ii) truck metallic cisterns that fill directly into the home-based cisterns, (iii) tap water, or (iv) well water (Ben Ayed et al. 2018). According to Xavier et al. (2011) and Chubaka et al. (2018), home-based tank contamination was previously linked to a variety of factors, including (i) fecal contamination from birds or other animals that may gain access to the tanks when they are left uncovered or poorly covered, (ii) the tanks' construction material, and (iii) inhabitants' unsanitary practices (the bucket was not cleaned, users did not wash their hands before manipulating it, etc.).

The water treatment processes for DW implemented in each MENA region are contingent upon the following:

  • 1. The economic status of the country

  • 2. The specific characteristics of raw water

  • 3. The quality requirements of drinking/potable water

To ensure a sufficient water supply during the summer, DW may be sourced from either surface water or groundwater in arid regions in MENA. In countries with low and middle incomes in MENA (Egypt, Tunisia, Morocco, etc.), the process of treating DW involves a pretreatment through screening to remove large debris, a pre-chlorination using chlorine gas, a coagulation-flocculation process, sedimentation, sand filtration, and ultimately, chlorination for disinfection (Geriesh et al. 2008; Farhaoui & Derraz 2016; Ghernaout et al. 2017; Azeddine et al. 2023). Nevertheless, in high-income MENA nations, including the Gulf Cooperation Council (GCC) and the Arabian Gulf, desalinated water is the primary DW source (Ghaffour et al. 2013). The desalination procedure may be conducted using either brackish water or seawater. The process is founded on reverse osmosis and ultra- or nano-filtration. The primary disadvantages of desalination are its energy consumption (El-Ghonemy 2012) and the production of saline that is non-treatable.

Although DW should be devoid of any pathogenic organisms after a series of treatment processes (Ramsay et al. 2014; Utaaker et al. 2019), the contamination of DW in the MENA region with Cryptosporidium sp. and G. duodenalis substantially threatens human health and raises noteworthy concerns.

Swimming pools were the second-last to be infected with Cryptosporidium sp. The last water category was contaminated with G. duodenalis. Two MENA countries (Egypt and Iran) monitored and reported the characteristics of swimming pools (Abd El-Salam 2012; Ghasemi et al. 2019). They recommended that the water quality in swimming pools must meet specific national standards throughout:

  • 1. Encouraging regular monitoring of the swimming pool quality (this assessment must be performed on working days, weekends, and holidays).

  • 2. Good pool maintenance and avoiding biofilm formation.

  • 3. Reducing the number and density of bathers.

The presence of G. duodenalis and Cryptosporidium sp. in swimming pools of MENA poses a significant health risk, underscoring the urgency and importance of addressing this issue.

Other water categories and subcategories in the MENA, including TWW, groundwater, and seawater, have exhibited diverse prevalences of Cryptosporidium sp. and G. duodenalis. They have been detected in the 2nd TWW in Tunisia (Ben Ayed et al. 2012) and Israel tertiary effluents after sand filtration and chlorination (Taran-Benshoshan et al. 2015). Due to the scarcity of conventional water supplies, TWW is a promising alternative to tackle this shortage as it provides a reliable water supply and could be reused in agriculture, irrigation of gardens or green spaces, car washing, toilet flushing, aquaculture, and firefighting (Friedler 2001; Fu et al. 2010). It will also reduce fertilizer consumption and eutrophication. However, only some MENA countries adopted wastewater reuse (Jeuland 2015). Only 8% of 230 Mm3 in Tunisia is reused in agriculture (ONAS 2022).

In the MENA region, groundwater is under investigation, and only one study in Saudi Arabia addressed the water quality of wells. Cryptosporidium sp. was found to contaminate 7/96 (7.3%), while G. duodenalis was found in 9/96 (9.4%) of water wells (Hawash et al. 2015). The contamination of the wells' water in the MENA region could occur through (i) inputs from domestic and wild animals, (ii) septic tank leaks, (iii) wastewater effluent, (iv) agricultural runoff, (v) well deterioration, (iv) insufficient or absence of wellhead protection, and (v) infiltration through porous alluvial deposits or fissured rock (Karanis et al. 1998; Kay et al. 2007; Karanis 2011; Hawash et al. 2015; Khoury et al. 2016; Murphy et al. 2016; Nsoh et al. 2016).

Seawater was the third water category contaminated with Cryptosporidium sp. and the second-last contaminated with G. duodenalis. Their existence in marine environments endangers human health due to their utilization for recreational, drinking, and fishing purposes (Nasser et al. 2003). Few studies, however, have investigated their prevalence and persistence in seawater. The primary cause of seawater contamination is the discharge of wastewater (Nasser et al. 2003; Hilles et al. 2014). It has been reported that the following factors influence protozoa inactivation: (i) water temperature, (ii) exposure to solar radiation, (iii) salinity, and (iv) the presence of predators, etc. (King & Monis 2007; Wang et al. 2023).

According to the 35 retrieved studies, the prevalence and distribution of Cryptosporidium sp. and G. duodenalis in untreated water, such as surface water, RWW, groundwater, and marine water, are linked to fecal contamination (Nasser et al. 2003; Ben Ayed et al. 2009, 2012, 2018; Mahmoudi et al. 2013, 2015a, 2015b; Hilles et al. 2014).

Disinfection applied in MENA region, water safety, and monitoring

Chlorine is a disinfectant that is frequently employed in a variety of forms at water treatment facilities in the MENA region, particularly DW and swimming pools. This is due to its ability to effectively eliminate a large microbial community, its affordability, convenience, and long-lasting residual effect on the network.

Chlorine is widely used as a disinfectant at water treatment plants in the MENA region in a variety of forms due to: (i) its effectiveness in the elimination of a large microbial community, (ii) its ease of use and its reasonable price, and (iii) its long-lasting residual effect on the network. The effectiveness of chlorine elimination is closely related to its dose, contact time, and pathogenic effluent concentration (Betancourt & Rose 2004). The use of chlorine must be carefully addressed due to the toxicity of by-products such as trihalomethanes (Rabhi et al. 2016), which is a vital issue influencing water management decisions on the appropriate level of disinfection that could ensure the microbiological safety of the water.

All MENA countries strive to ensure the safety of their DW by enacting standards and laws through each country's Ministry of Health to provide water quality and safety monitoring. The World Health Organization established a guideline value of one Cryptosporidium sp. oocyst per 1.600 L of DW to achieve a health-outcome target of 10−6 disabled adjusted life years (DALY) per person per year (World Health Organization 2003). DW standards in Tunisia declare permissible concentrations for mandatory physical properties, chemical elements, and microbiological agents. However, Cryptosporidium sp. and G. duodenalis are unrestricted (Norme Tunisienne NT 09.13 2014). Egypt has a similar situation to Tunisia; however, regarding parasites' presence in water, Egyptian standards stipulate that DW should be free of protozoa and worms, according to the Minister of Health Decree No: 108/95 (Hikal 2020).

UV and ozone are other disinfectants that could be applied to DW disinfection. They are both highly efficient at inactivating protozoa, produce no by-products, and require only brief contact. Their efficiencies, however, are correlated with turbidity, and they do not have a long-lasting residual disinfection effect like chlorine (Karanis et al. 2003; Betancourt & Rose 2004). However, they still need to be implemented in the MENA region.

In the MENA region, swimming pools' water is only disinfected through chlorination (Abd El-Salam 2012; Ghasemi et al. 2019; Hassanein et al. 2023). Chlorine disinfection is less effective against G. duodenalis cysts but ineffective against Cryptosporidium sp. oocysts (Sullivan et al. 1988). Cryptosporidium oocysts are exceptionally resistant to chlorine. Even in aquatic facilities, such as pools and water playgrounds, where free chlorine concentration is effectively regulated, Cryptosporidium oocysts can still propagate among swimmers (https://www.cdc.gov/model-aquatic-health-code/media/pdfs/hyperchlorination-to-kill-crypto-when-chlorine-stabilizer-is-in-the-water.pdf). Free chlorine concentration and pH must not be high because increasing pH results in only a small percentage of residual chlorine converted into hypochlorous acid (World Health Organization 2009). While hypochlorous acid is effective against waterborne pathogens, it may irritate swimmers' upper and lower respiratory tracts, eyes, and skin (Ishioka et al. 2008; Bernard et al. 2009). The same dilemma is faced with the concentration of chlorine that must be injected during the disinfection stage of the DW treatment process (Rabhi et al. 2016).

In swimming pools, fecal contamination incidents and filter malfunctioning cause higher infection risk (https://watertreatmentservices.co.uk/cryptosporidium-swimming-pools/#:∼:text=The%20most%20effective%20treatment%20for,times%20to%20remove%20them%20all). Filtration is the most effective method for removing Cryptosporidium sp. from swimming pools. The method is applied in Egypt (Abd El-Salam 2012). However, solitary pool water circulation through filtration systems fails to accomplish complete oocysts removal. It might be necessary to purify the pool water multiple times to eliminate them all (https://www.cdc.gov/model-aquatic-health-code/media/pdfs/hyperchlorination-to-kill-crypto-when-chlorine-stabilizer-is-in-the-water.pdf) which is not practised in the MENA region.

Detection methodologies and genotypes of Cryptosporidium sp. and G. duodenalis in MENA water resources/categories

Detection methods of (oo)cysts in MENA water varied in the current review (microscopic, immunological, and molecular analysis). The routine diagnosis of Cryptosporidium sp. and G. duodenalis (oo)cysts in the MENA region's water resources is primarily based on conventional techniques (microscopy and morphological identification), which could provide quantitative data at a lower cost (Chique et al. 2020). However, they are time-consuming and have lower specificity and sensitivity (Ben Ayed Khouja et al. 2010; Efstratiou et al. 2017b; Ahmed & Karanis 2020; Hijjawi et al. 2022).

Molecular tools such as PCR, PCR-RFLP, LAMP, and sequence analysis were applied in the MENA studies to identify Cryptosporidium sp. and G. duodenalis DNA in water samples (Rayan et al. 2009; Ben Ayed Khouja et al. 2010; Hussein 2011; Ben Ayed et al. 2012; Taran-Benshoshan et al. 2015; Mahmoudi et al. 2015a, 2015b; Ghasemi et al. 2019; Abd El-Latif et al. 2020). Such tools have been used to differentiate between species and combine genotyping and subtyping with epidemiological tracking. Although such techniques are more sensitive and increase epidemiological knowledge in the MENA region, their use could have been improved, probably due to financial constraints and a need for more expertise in the field.

Using conventional techniques and a lack of molecular instruments will make the accurate diagnosis and prevalence in the MENA region a cause for concern. This will harm estimating the actual distribution and prevalence of Cryptosporidium sp. and G. duodenalis in water categories, which is highly likely to be underestimated. The MENA water resources will continue to be contaminated, and other subtypes/assemblages will emerge.

In terms of Cryptosporidium genotyping data from the MENA region, the 18S rRNA gene was commonly used for Cryptosporidium sp. genotyping in Tunisia, Iran, and Israel water categories (Ben Ayed Khouja et al. 2010; Ben Ayed et al. 2012; Mahmoudi et al. 2013, 2015b; Taran-Benshoshan et al. 2015; Ghasemi et al. 2019). The DhR (dihydrofolate reductase) gene was used once in an Egyptian study (Rayan et al. 2009). Three MENA studies targeted the glycoprotein 60 (gp60) gene in wastewater and surface water to identify Cryptosporidium sp. at the subtype level (Ben Ayed Khouja et al. 2010; Ben Ayed et al. 2012; Mahmoudi et al. 2015b).

Twelve Cryptosporidium sp. were reported in MENA water resources (C. hominis, C. parvum, C. andersoni, C. muris, C. meleagridis, C. ubiquitum, rat genotype IV, an unknown Cryptosporidium sp., sheep genotype, avian genotype II, C. canis, and C. bovis). The most common species found in MENA waters were C. hominis and C. parvum. This latter was reported in nearly every study conducted in the MENA region. C. andersoni and C. muris were explicitly reported in wastewater and surface water (Ben Ayed Khouja et al. 2010; Ben Ayed et al. 2012; Taran-Benshoshan et al. 2015; Mahmoudi et al. 2015b).

Five Cryptosporidium sp. subtypes have been identified in MENA water resources: C. hominis Ia and Id and C. parvum IIa, IIc, and IId. C. hominis Ia and C. parvum subtype IIa and IIc were found in Tunisian wastewater (Ben Ayed Khouja et al. 2010; Ben Ayed et al. 2012; Mahmoudi et al. 2015b). In contrast, the anthroponotic subtype IId was identified in Iranian surface water (Mahmoudi et al. 2015b) as well as within humans and calves (Nazemalhosseini-Mojarad et al. 2011; Taghipour et al. 2011).

G. duodenalis genotyping in the MENA water resources performed by the amplification of the triosephosphate isomerase (tpi) gene, glutamate dehydrogenase (gdh), β giardin, S-adenosyl-1- methionine synthetase (SAM-1), and elongation factor 1α (ef1α) (Ben Ayed Khouja et al. 2010; Ben Ayed et al. 2012; Mahmoudi et al. 2013, 2015a; Abd El-Latif et al. 2020), either individually or through a combination of two or three loci. Mixed contamination by G. duodenalis assemblages A, B, and E was reported in Tunisian wastewater (Ben Ayed Khouja et al. 2010; Ben Ayed et al. 2012). Assemblage B was also reported in surface water in Iran (Mahmoudi et al. 2015a). Assemblage B2 was identified in Egyptian surface water and diarrheic children, implying that G. duodenalis is potentially transmitted through contaminated water (Abd El-Latif et al. 2020).

There is a high degree of similarity between Cryptosporidium sp. and Giardia duodenalis genotypes/subtypes reported in MENA human and animal populations (Hijjawi et al. 2022) and genotypes/subtypes reported in MENA water resources of the current review. The presence of the same genotypes/subtypes of Cryptosporidium and Giardia in MENA countries suggests various interfaces between humans, animals, and water, perpetuating the life cycle and transmissible (oo)cysts.

Water volume investigated in MENA water resources/categories

To recover Cryptosporidium and Giardia (oo)cysts, sample volume and whether to obtain grab or composite samples are crucial factors. According to Efstratiou et al. (2017b), the primary volume requirement is sufficiently large to detect the target organisms. The retrieved studies varied the volume by water resource/category and country. Cryptosporidium sp. and Giardia sp. were detected in the smallest volume (10 mL) of surface water sampled, with Cryptosporidium sp. predominating (Khalifa et al. 2014). Nevertheless, Cryptosporidium sp. was not identified in a 5-L sample that was subjected to molecular analysis in surface water. However, it was identified in a 50-L sample (Mahmoudi et al. 2015a). Cryptosporidium sp. was detected in 1 L of DW samples. Consequently, higher volumes do not enhance the detection rate, even when advanced techniques are implemented. Although it relates more to the purity of the analyzed water and the procedures used (concentration, staining, etc.), the number of reported studies remains restricted, a limitation for the current meta-analysis review.

In the reports of MENA countries, no studies were conducted to quantify consumer risks of infection and illness using the Quantitative Microbiological Risk Assessment (QMRA). However, it is a reliable risk management tool that has been widely used to predict infectious pathogens' health risks in DW (Xiao et al. 2012), surface water (Adell et al. 2016; Xiao et al. 2018), and reclaimed water (Zhang et al. 2015). In national policies, it could help improve water safety, reduce disease burden, and adjust the present limits of infectious pathogens like Cryptosporidium sp. and G. duodenalis.

Impact of climate change on water scarcity in MENA region

The MENA countries are the driest globally (Qadir et al. 2010) and are currently experiencing severe water scarcity (Ouda et al. 2021). In terms of climate change, it is one of the most vulnerable regions on the planet. The Intergovernmental Panel on Climate Change (IPCC) projects significant changes in climate across the MENA, exacerbating the pressure on available water resources (Terink et al. 2013). Summer temperatures are expected to increase by up to 4 °C by 2071–2100 compared to pre-industrial levels, as the MENA region is warming at a higher rate than the global average (UNICEF 2024).

Within this century, it is anticipated that the thresholds of human tolerance and adaptability will be reached or exceeded in some areas of the Middle East due to the combination of heat and humidity. Combined heat and drought in other regions of the MENA will accelerate desertification and result in an increase in dust cyclones, which will have a severe impact on the health of children (UNICEF 2024). The current crisis is unparalleled in terms of its scope and severity. With approximately 41 million individuals in the MENA region lacking access to adequately managed DW services and 66 million lacking basic sanitation services, the survival of children is at risk, resulting in increased disease and fragility (UNICEF 2024). The changing climate will further strain the limited water resources, as water consumption for both domestic and agricultural purposes will increase due to the elevated temperatures.

Cryptosporidium sp. and G. duodenalis are widespread in water sources and categories of MENA, with a predominance in wastewater and surface waters due to water pollution by urban, industrial, and agricultural runoff.

The applied water treatment in MENA countries is more effective for G. duodenalis but ineffective for Cryptosporidium sp. This is most likely because of its size, density, and resistance to usual disinfectants.

MENA water has similar Cryptosporidium sp. or G. duodenalis genotypes/subtypes reported in humans and animals, suggesting water-human-animal interfaces.

Development of public policies for water resources and human health protection to reduce the load of pollutants in water supply sources of the MENA region in the context of climate change are then extensively required.

Further research is necessary to assess the Cryptosporidium sp. and G. duodenalis burden, particularly in countries with few or no reports.

To better understand the transmission dynamics and human or animal health impacts of Cryptosporidium sp. and G. duodenalis, expertise in molecular epidemiology and viability must compare the prevalence of these protozoa in water samples to MENA epidemiological data.

With the rising utilization of water resources for DW preparation across various environments of the largely inhomogeneous MENA region countries, it is fundamental that future studies address the demand for water utilization with good quality regarding the pathogenic microorganisms and the one-health-concept.

To address the many knowledge gaps regarding removing the (oo)cysts during the water treatment preparation, related studies must be initiated to investigate the prevalence, distribution, removal and dispersion of waterborne parasites in water resources.

MENA countries should prioritize the welfare of their populations. Surveillance systems and relevant training and education should be established to identify Cryptosporidium sp. and G. duodenalis and other waterborne pathogens in various water resources and investigate underreported waterborne outbreaks.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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