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Heliyon 10 (2024) e27271
Available online 2 March 2024
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Research article
Tracking enteric pathogen contamination from on-site sanitation
facilities to groundwater in selected rural areas of Vhembe
District Municipality, Limpopo Province, South Africa
Jeridah Matlhokha Sekgobela
a
,
*
, Colette Mmapenya Khabo-Mmekoa
b
, Maggy
Ndombo Benteke Momba
a
,
**
a
Tshwane University of Technology, Department of Environmental, Water and Earth Sciences, Arcadia Campus, P/B X 680, Pretoria, 0001, South
Africa
b
Tshwane University of Technology, Department of Biomedical Sciences, Arcadia Campus, P/B X 680, Pretoria, 0001, South Africa
ARTICLE INFO
Keywords:
Household boreholes
Groundwater
Pathogens
On-site sanitation
Contamination
ABSTRACT
Groundwater is valued as a source of potable water, although it is vulnerable to environmental
pollution. The aim of this study was to track enteric pathogen contamination from on-site sanitation
(OSS) facilities to 70 household boreholes used by four villages of the Vhembe District Municipality.
Two objectives were pursued: to measure the lateral distance between the borehole and the sani-
tation facilities in household yards, and to track the enteric pathogens. The borehole abstraction
point and OSS system distance were determined using a steel measuring tape. Real-time PCR was
used to track Shigella exneri, Salmonella typhimurium, Campylobacter jejuni, and enterotoxigenic
Escherichia coli (ETEC) from Wastewater (WW) from domestic septic tank and sludge from pit la-
trines to boreholes. Escherichia coli was used as an indicator of faecal contamination. Results showed
that 25% of households kept a distance of ≥50 m between the OSS facilities and the boreholes. In
total, 87.5% of household boreholes in the rainy season and 72.5% in the dry season were
contaminated with E. coli and pathogenic bacteria: Shigella exneri, Salmonella typhimurium, and
ETEC. The concentrations of the pathogens ranged from 2.03 to 2.12 LogEGC/100 mL. A very weak
(r = − 0.093) to moderate (r = − 0.541) association was found between pathogens in groundwater
and on-site sanitation systems (WW from septic tank and sludge from pit latrine). This suggests that
the pathogens were not present in the sanitation compartment when they were found in the
groundwater and vice versa. Moreover, a very weak (r =0.007) to moderate (r =0.525) association
was found between the detected contaminants in groundwater and the lateral distance between the
OSS facilities and the boreholes. The pathogens detected in all samples showed consistent con-
centrations, suggesting potential contamination from OSS systems’ waste, possibly in groundwater,
indicating potential contamination. The siting of OSS facilities at the yards in this study appeared to
have a slight inuence on the contaminants detected in groundwater. This study calls for an edu-
cation program to be implemented by the Water and Sanitation Services Authorities to prevent
contamination of groundwater and the risk of waterborne diseases.
* Corresponding author.
** Corresponding author.
E-mail addresses: sekgobelajeridah@gmail.com, 211140178@tut4life.ac.za (J.M. Sekgobela), MmekoaKCM@tut.ac.za (C.M. Khabo-Mmekoa),
momba1958@gmail.com (M.N.B. Momba).
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
https://doi.org/10.1016/j.heliyon.2024.e27271
Received 10 August 2023; Received in revised form 5 February 2024; Accepted 27 February 2024
Heliyon 10 (2024) e27271
2
1. Introduction
Access to continuous water piped water from the treatment plant is not always available, there are often water cuts due to treatment
plant not working. Groundwater is thought to be an important source of drinking water, particularly in places where access to clean
water is scarce. In 2020, globally, 771 million people did not have access to services that provided safe drinking water, and 80% lived
in rural areas of which over 50% reside in sub-Saharan Africa [1]. The use of groundwater from household boreholes is increasing in
developing countries [2]. South Africa (SA) is a water-stressed country and groundwater is a valuable and essential water source.
According to data from Stats SA [3], 20 378 households in the Vhembe District Municipality (VDM) relied on groundwater from
household boreholes as their primary drinking water source. Groundwater from household boreholes is considered of exceptional
quality and an independent water supply, making it accessible and convenient for household members. Groundwater is currently the
most favored source of drinking water worldwide [4] and it is regarded as one of the enhanced supplies of drinking water [5]. Despite
all the benets listed above, environmental hazards such as fertilisers, poor sanitation, inadequate sewerage infrastructure, on-site
sanitation (OSS) systems located in close proximity of boreholes, and surface water-groundwater interactions as well as improperly
sealed, abandoned household water wells and lead to the deterioration of its quality [6–10].
There have been numerous reports from earlier and more recent studies on the contamination of water sources within the VDM
region. In a microbiological study of the river water sources used by the Venda rural community [11], it was found that the river water
contained microorganisms such as Escherichia coli, Shigella spp. And Salmonella spp., and that the water is not safe for human con-
sumption. Another study in the Tshitale-Hlanganani region detected E. coli in groundwater from the borehole used by communities for
drinking [12]. In 2006, between June and July, there was an outbreak of diarrhea in Tshikuwi (a rural area in Venda) [13]; the authors
also indicated that most of the river water and groundwater used by households in the rural areas of the VDM is of poor microbial
quality. Taonameso and co-workers [14] also pointed out that groundwater from the boreholes used in Dididi village (in VDM) tested
positive for enteropathogenic Escherichia coli (EPEC) and enterotoxigenic Escherichia coli (ETEC). In Muledane (in Thulamela Local
Municipality, VDM) [15], detected high faecal coliform bacteria (E. faecalis and E. coli) in groundwater from boreholes. In a separate
study conducted by Ref. [16], Salmonella Typhimurium, Shigella exneri, and E. coli were detected in groundwater used by school
children in the Vhuronga 1 Circuit of the VDM. Based on these ndings, monitoring of microbial contamination in groundwater within
the VDM sites is critical.
A report by Ref. [17] pointed out that on-site sanitation systems are used by more people in the sub-Saharan Africa region (44%)
than those having sewer connections (7%) in 2020. Pit latrines are one of the world’s most common primary types of improved on-site
sanitation systems in this region, and in South Africa, a ventilated improved pit (VIP) latrine is the minimum acceptable level of
sanitation [18]. A recent study by Ref. [19] has highlighted that the majority of households in the VDM use on-site sanitation facilities
in the form of pit latrines and septic tanks. These sanitation systems are prevalent due to the country’s overall relative lack of water and
frequent water outages. Additionally, these OSS systems are used in areas where housing density is low and thus centralised waste-
water treatment plant (WWTP) is not economically feasible; or where resource limitations do not permit centralised wastewater
treatment. On-site sanitation is a much-overlooked source of faecal contamination in groundwater; however, these systems pose a
serious threat to groundwater because faecal matter accumulates in one location, and contaminants may seep into the subsurface [20].
The waste generated by these OSS systems is underground; therefore, it is easy to ignore and not put a proper management system in
place. However, what goes down the drain and into the ground is not gone forever; these OSS systems have an impact on the envi-
ronment. If the waste generated by these on-site sanitation systems is not adequately managed, groundwater sources will be at risk of
contamination.
Recommendations for the siting of pit latrines differ across countries; they range from 15 to 75 m between the groundwater source
and the sanitation unit. Ensuring an adequate distance between wastewater disposal facilities and drinking water wells is crucial to
safeguard the water sources against microbial contamination [21]. To our knowledge, no research has been done to link on-site
sanitation facilities to the faecal contamination of boreholes that are located on the same household premises at the specic sites
investigated in the present study. Assessing groundwater quality in boreholes is crucial, especially in challenging water supply areas
with frequent contamination issues. This study aimed to track the selected enteric pathogens from OSS facilities to household bore-
holes used as the main water sources by four selected villages of the Vhembe District Municipality; as well as to establish the lateral
distances between the sanitation facilities and the boreholes where groundwater samples were collected, and to determine the rela-
tionship between the OSS facilities and the contaminants in the groundwater. The following objectives were set to achieve the aim of
the study: The rst step was to ascertain whether the communities apply the National Norms and Standards for Domestic Water and
Sanitation Services [18], by measuring the lateral distance between the borehole and the sanitation facility in household yards across
the four villages; and the second step was to track the presence of the selected pathogens from WW from septic tank and from sludge
from pit latrines to groundwater abstracted from the household boreholes.
2. Methods
2.1. Description of study sites and ethical approval
The current investigation was carried out for a total of 28 days between March 2021 and August 2021 in the Limpopo Province’s
Vhembe District Municipality (VDM), which is situated in the far north of South Africa. The study was conducted in four (4) villages:
Tshilapfene-Village A, (Tsianda-Village B, Ha-Mutsha-Village C, and Njhakanjhaka-Village D (Fig. 1). Information from the South
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
3
African Geomatics Council was used to determine the geology of the study sites (Table 1). Although Village B and Village C share the
same geology and are separated by a road, Village B village stands out due to its steep slopes. The study was reviewed and approved by
the Tshwane University of Technology’s Faculty of Science Research Ethical Committee, with the approval number: [2019/09/017
(FCPS 03) (SCI)] and after describing the project’s goals to the municipal committee, access to VDM villages was granted. All par-
ticipants provided informed consent to participate in the study.
2.2. Selection of study households and sampling points
A systematic sampling criterion was used for the selection of study households (HHs). Before the study was conducted, a survey was
conducted to identify villages and HHs that fall within the study criteria. The study aimed at assessing the impact of OSS systems on the
quality of groundwater. The study households were selected based on the following criteria: (i) Use groundwater from drilled elec-
tricity borehole (ii) Use on-site sanitation facility and (iii) Both the borehole and sanitation facility are located in the yard. To make it
easier to generalize the ndings to the entire village population while reducing the need to sample all the HHs, the number of
households selected per village represents 5% of the households in that village that fall under the study criteria.
2.3. Outline of the methodology
Fig. 2 provides a detailed layout of the research method followed in this study. The distance between the Submerged electricity
borehole (drilled holes in the ground that access groundwater, with the added feature of electrical equipment submerged within the
borehole) and the on-site sanitation facility was measured, followed by the collection of samples. Groundwater samples were collected
at 70 household boreholes, while wastewater was collected from 18 household septic tanks and human waste from 52 pit latrines.
Escherichia coli was quantied using a culture-based method and quantitative polymerase chain reaction (qPCR) was used to track the
target pathogenic bacteria.
2.4. Measurement of the distance
The boreholes in the study area were equipped with electric submersible pumps. The lateral distance between the borehole
abstraction point and the OSS system (pit latrine or a septic tank system) was determined using a steel measuring tape as used in
previous studies [22,23]. The distance between OSS facilities and boreholes was measured at 70 HHs in the selected villages. Ten HHs
were chosen for Village D village, while twenty HHs were taken into consideration for each of the following three villages: Village A,
Village B, and Village C. The measurements were recorded in metres.
2.5. Collection of samples
Samples were collected from a total of 70 HHs, during the rainy season (March 2021 and April 2021) and the dry season (June and
Fig. 1. A map indicating the sites where the study was conducted. This gure indicates the four villages, namely: Village A, Village B, Village C, and
Village D.
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
4
Table 1
Geological data of the sampling sites.
Villages Geology
Village A - Basaltic and andesitic lavas with subordinate interbedded pyroclastic and clastic sedimentary rocks
- Diabase
- Sandstone (locally quartzitic), subordinate conglomerate, basaltic lava, tuff, shale, and siltstone
Village B & Village C - Basaltic and andesitic lavas with subordinate interbedded pyroclastic and clastic sedimentary rocks.
- Conglomerate, quartzitic or feldspathic sandstone, greywacke, shale
- Leucocratic, tonalite-trondhjemite-granodiorite (TTG) gneisses.
Village D - Leucocratic, tonalite-trondhjemite-granodiorite (TTG) gneisses.
- Metapelite
Fig. 2. Research methodology ow chart. The gure indicates the study site’s sampling points and the number of boreholes, pit latrines and septic
tanks sampled as well as the total number of samples collected. The gure further shows the methods used for the analysis of the samples.
Table 2
Borehole groundwater, WW from septic tank, and sludge from pit latrine samples collected during the study period.
Villages
Households
Number of boreholes, septic tanks and pit latrines sampled Number of groundwater, wastewater and human waste samples collected
Groundwater Wastewater Human waste
Wet Dry Wet Dry Wet Dry
Village A
20 HHs
20 BHs
6 STs
14 PLs
80 80 24 24 56 56
Village B
20 HHs
20 BHs
4 STs
16 PLs
80 80 16 16 64 64
Village C
20 HHs
20 BHs
5 STs
15 PLs
80 80 20 20 60 60
Village D
10 HHs
10 BHs
3 STs
7 PLs
40 40 12 12 28 28
Total 70 BHs
18 STs
52 PLs
280 280 72 72 208 208
Grand Total 560 144 416
Boreholes (BHs); pit Latrines (PLs); septic tanks (STs).
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
5
August 2021). In each HH there were two sampling points, namely OSS compartment and the borehole. For each sampling point,
samples were collected four times per season. In each season sample collection took place for two months (8 weeks). Samples were
collected weekly (Mondays)/once per week. On each sampling day we collected samples from 35 households/week). To minimize
contamination samples were all collected using sterile bottles. The total number of sampling days was 32, 16 days for each season.
Sample collection took place twice a week (a total of 8 weeks per season). Table S1 (Supplementary Table 1) represents the geological
coordinates (latitude, longitude) associated with a specic location of the sampling points. Table 2 provides a summary of the total
number of samples collected for the study during the wet and dry seasons. Before collecting the groundwater samples, the tap was run
for a few minutes to clear the plumbing system of any standing water. In total, 560 groundwater samples were collected from 70
household boreholes, namely 20 boreholes in each of the following villages: Village A, Village B and Village C and 10 boreholes in
Village D using standard methods [24]. A total of 144 wastewater samples were collected from 18 household septic tanks (ST) in
Village A (n =6 STs), Village B (n =4 STs), Village C (n =5 STs), and in Village D (n =3 STs). A modied method described by
Ref. [25] was used to collect the wastewater samples. The collection of wastewater samples is described in our previous study [26]. For
the sampling of human waste from pit latrines, 416 faecal sludge samples were collected from 52 household pit latrines (PLs)
distributed across four villages: Village A (n =14 PLs), Village B (n =16 PLs), Village C (n =15 PLs), and Village D (n =7 PLs). Human
waste samples were collected from pit latrines using a modied method described by Strande et al. (2014). Briey, a sterile stool
collection cup was rmly attached to the metal rod and inserted into the drop hole in the oor connected to the toilet seat to obtain
faecal sludge. The sludge was collected multiple times at different sites within the pit, mixed, and added to a stool collection tube. To
prevent the growth and degradation of the microorganisms during transport to the laboratory, all samples were kept cold inside the
cooler box containing ice packs. All samples were clearly labelled with unique identication number. Human waste samples were
transported to the University of Venda in the Parasitology Laboratory for DNA extraction. To maintain the viability and slow down the
metabolic activity of any present microorganisms, groundwater and wastewater samples were kept cool (between 2 and 8 ◦C) on ice
and transported to the Microbiology Laboratories at the Tshwane University of Technology in Pretoria and analysed within 24 h. To
ensure that the sample temperature was not affected during transportation, upon arrival at the laboratory the temperature of the
samples was measured aseptically using a liquid-in-glass thermometer. A portion of the water samples originally held in the sample
bottles was transferred into the sterile sample container for the purpose of temperature analysis. The liquid-in-glass thermometer was
rinsed with distilled water and immersed into the water sample without touching the sides or bottom of the container.
2.6. Detection and enumeration of Escherichia coli
The membrane ltration technique was used for the detection and enumeration of E. coli according to the standard methods [24]
using Chromocult® Coliform Agar (CCA) (Merck, Darmstadt, Germany). All of the equipment needed for the membrane ltering
process, including the forceps, collecting jars, and ltration apparatus, was sanitized to prevent contamination and guarantee accurate
results. The ltration gear was cleaned with sterile water before ltering to get rid of any leftover impurities. Groundwater (100 mL)
was ltered through a sterile 0.45
μ
m pore size membrane lter (47 mm diameter, Sartorius Stedim Biotech GmbH, G¨
ottingen,
Germany). The membrane lter was taken out of the equipment and placed into an agar plate using sterile forceps. To rule out
contamination, blank samples (sterile distilled water) were also ltered and plated onto CCA. The agar plates were prepared according
to the manufacturer’s instructions. Incubation of the agar plates was performed at 36 ±1 ◦C for 18–24 h. Plates were always prepared
in triplicate. Following incubation, quantication of E. coli was performed by counting household dark blue/violet colonies [27] which
were recorded as colony-forming units (CFU/100 mL). A mean value of the three replicates from all samples was obtained.
Furthermore, E. coli counts (ECC) were averaged over the four sampling cycles for each season and borehole.
2.7. DNA extraction
Before DNA extraction the equipment and instruments, such as pipettes, centrifuges, and thermocyclers were calibrated. Modied
methods from previous studies were used for DNA extraction [28,29]. For the groundwater samples and the WW from septic tank
samples, DNA was obtained using a combination of two concentration methods (membrane ltration and centrifugation) as well as a
pre-enrichment step. Membrane ltration and centrifugation were used to concentrate the groundwater and WW from septic tank
samples and increase the detection sensitivity, while the pre-enrichment step was used to resuscitate the cells and allow them to
proliferate. Sample volumes of 1000 mL of groundwater and 90 mL of wastewater were ltered through a 0.22
μ
m pore size membrane
lter (47-mm diameter, Sartorius). The lters were transferred into 15 mL screw-cap tubes containing Campylobacter enrichment broth
(Bolton Broth) (Merck, 67454), which supports the growth of Campylobacter species, and Gram Negative (GN) enrichment broth
(Separations, 1248-CONDA) (developed by Hajna, 1955), which supports the growth of Salmonella spp., Shigella spp. As well as
Escherichia coli. The lters were placed such that the broth covered the lter; this was followed by incubation at 37 ◦C for 24 h (GN
Broth) and the Bolton Broth was rstly incubated at 37 ◦C for 6 h and then for another 24 h at 42 ◦C. Following incubation, 500
μ
L of
each enrichment culture was transferred to a microcentrifuge tube. The tubes were centrifuged for 20 min at 13 000 rpm at 4 ◦C to
obtain a pellet; centrifugation was repeated two to three times until desired/some visible pellet was obtained. The supernatant was
discarded, and the pellet was re-suspended in 2 mL of sterile distilled water. The DNA was extracted from this re-suspended pellet using
the ZR Soil Microbe DNA MiniPrep™ Kit (Zymo Research, USA), following the manufacturer’s protocol. For DNA extraction from the
human waste samples, a bead-beating step was included, following a modied method as described by Ref. [30]. Approximately 200
mg of each human waste sample was used for DNA extraction (the extracted DNA was frozen at −80 ◦C and transported to Tshwane
University of Technology, Microbiology Laboratory for further analysis). The elution volume in DNA extraction was 35
μ
L. Finally, a
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
6
NanoDrop 2000 spectrophotometer (Thermo Scientic, South Africa) was used to determine the quantity and quality of the DNA using
the (A260/A280 ratio of 1.8–2.0) of the extracted DNA. All the DNA samples were stored at −80 ◦C until further processing.
2.8. Molecular analysis
The primers and probes of the target pathogens and the target genes are indicated in Table 3. All the target genes are virulence
genes and species-specic, except for ipaH gene in Shigella exneri, which is also found in Enteroinvasive E. coli. Internal positive and
negative controls were used to identify contamination from PCR reagents and DNA extraction. Positive controls included Campylo-
bacter jejuni (ATCC33291), Shigella exneri (ATCC12022), ETEC (ATCC35401), and Salmonella typhi (ATCC13311) bacterial strains.
These strains were grown and maintained in culture media, and genomic DNA was extracted using a Zymo DNA extraction kit (Zymo
Research, USA). Positive controls were added to the PCR reaction mix as a DNA solution. Negative controls included PCR (nuclease-
free) water, a no template control (NTC), and an extraction blank. To ensure that the primers and probes bind to and amplify the target
sequences in real-time, standard curves were created using positive controls of target pathogens, serially diluted ten times. The ef-
ciency of all PCR assays was determined using the formula E =[10 (−1/M)]-1 [31], where M is the slope and E is the assay efciency
and ranged between 106% and 110% (Table S2).
The stock solution for all the primers and probes was 100
μ
M. From the stock solution, a 10
μ
M working stock for PCR reactions was
prepared. This was achieved by preparing a 10-fold dilution and doing a 1:10 dilution (one part of the stock solution was mixed with
nine parts of sterile PCR water). The PCR amplication reactions were performed using the Bio-Rad CFX96 with a 96-well design Touch
Deep Well Real-time PCR Detection System (Bio-Rad Laboratories, Inc., Hercules, CA, USA). All the nucleic acid extracts were analysed
via a multiplex qPCR for the detection of Shigella exneri, Campylobacter jejuni and Salmonella typhimurium. Each PCR reaction was
performed in a volume of 25
μ
L consisting of 12.5
μ
L of GoTaq® Probe qPCR Master Mix [contains GoTaq® Hot Start Polymerase,
MgCl
2
, dNTPs and a proprietary reaction buffer (Promega)], 3
μ
L of PCR/nuclease-free water, and 2.0
μ
L of DNA template. For each of
the three target genes, 1
μ
L of forward primer, 1
μ
L of reverse primer and 0.5
μ
L of the probe were used. Amplication was performed
using the cycling conditions outlined in Table 3. For the detection of ETEC, the singleplex assay was employed. Amplication reactions
were performed in a total of 25
μ
L, which contained 12.5
μ
L of GoTaq® Probe qPCR Master Mix, 3
μ
L of PCR nuclease-free water, 2.0
μ
L
of DNA template, 1
μ
L of forward primer, 1
μ
L of reverse primer, and 0.5
μ
L of the TaqMan probe. To maintain the stability of the
reagents and minimize the risk of non-specic amplication or contamination, all the PCR master mixes were prepared on ice. To
ensure the reliability and reproducibility of your results, all PCR reactions were run in duplicates. Following amplication, the data
were processed using Rotor-Gene 6000 software, which automatically interprets the data and generates cycle threshold (Ct) values and
uorescence curves. The Ct values were compared to the positive controls of each target. Samples that tested positive for the target
genes were noted and recorded.
2.9. Data analysis
The data were analysed using a combination of data analysis tools on Excel (365) and IBM SPSS statistics (Version 28.0.1.1 (15)).
General descriptive statistics were used to obtain summary statistics. For every sample, quantication of every pathogen was carried
out by calculating the mean Ct value by averaging the Ct values from duplicate wells. The equivalent genome copies (EGC) were
calculated by interjecting the mean Ct value to the standard curve for all target pathogens and the dilution factor of the PCR assay. For
the groundwater and wastewater samples, quantication was given as log10 EGC per 100 mL, and for the faecal sludge samples, log10
EGC per gram. A Pearson’s correlation test was used to measure the degree of association between (i) the presence/absence of
pathogens and lateral distance between boreholes and the OSS facility, and (ii) the linear association between E. coli concentration in
Table 3
Primer and probe sequences of the target pathogens.
Pathogen (Gene) Primer Sequence 5
′
to 3
′
Cycling conditions Reference
Campylobacter jejuni subsp. jejuni
(GyrA)
366F CTA TAA CAA CTG CAC CTA CTA AT initial incubation at 95 ◦C for 1 min, 45 cycles for 15 s at
94 ◦C, 20 s at 50 ◦C, 30 s at 72 ◦C and a nal extension at
72 ◦C for 30 s
[49]
614R ATG AAA TTT TTG CCA GTG GTG
409P Fam-CTT AAT AGC CGT CAC CCC AC-
Tam
Shigella exneri (ipaH) 1635F CAG AAG AGC AGA AGT ATG AG [50]
1804R CAG TAC CTC GTC AGT CAG
1747P ROX-ACA GGT GAT GCG TGA GAC TG-
BHQ2
Salmonella enterica subsp. enterica
serovar typhimurium LT2
(TtrC)
4136F AAT TAG CCA TGT TGT AAT CTC [51]
4315R ATT GTT GAT TCA GGT ACA AAC
4163P JOE-CAA GTT CAA CGC GCA ATT TA-
BHQ1a
Enterotoxigenic Escherichia coli
(STh)
F GCTAAACCAGYAGRGTCTTCAAAA 3 min at 95 ◦C for initial denaturation, 45 cycles at 95 ◦C
for 10 s, and at 60 ◦C for 1 min.
[52]
R CCCGGTACARGCAGGATTACAACA
P Quasar-705
TGGTCCTGAAAGCATGAA-BHQ2
Forward (F); Reverse (R); Probe (P); Primer (’).
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
7
groundwater and the lateral distance between the boreholes and OSS facilities. A point-biserial correlation test was used to nd the
association between the detected pathogens in groundwater and those in on-site sanitation systems (wastewater and sludge from pit
latrine). To determine signicance, an alpha value of ≤0.05 was used. Pearson’s r was used to indicate the strength of the associations,
where values of r =0–0.19 were regarded as very weak, r =0.2–0.39 as weak, r =0.40–0.59 as moderate, r =0.6–0.79 as strong, and r
=0.8–1 as a very strong correlation. Statistical analysis was not calculated where there were low or no detection rates.
3. Results
3.1. The lateral distance between OSS facilities and boreholes
The lateral distance between borehole and OSS facility for each of the 70 households distributed across four villages is indicated in
Table S3. Table 4 indicates the summary statistics of the measured distance between boreholes and sanitation facilities per village. The
ndings revealed that throughout the four villages, the lateral distance between the OSS facilities and household boreholes located on
the same properties ranged from 11 to 81 m. In Village A, the measured distance ranged from 15 to 75 m, for Village B from 11 to 66 m,
for Village C from 22 to 81 m, and for Village D from 12 to 55 m. The overall mean distance was 38.1 m and a total of 22.9% (n =16) of
HHs exhibited a distance of ≥50 m between the OSS facility and the borehole. These include 7 HHs in Village C, 5 HHs in Village A and
2 HHs in Village B, and another 2 HHs in Village D. The results showed that the household with the longest measured distance between
the sanitation facility and the borehole was recorded in Village C village; the average mean was 44.75 m. The ndings also revealed
that in all four villages, the standard deviations were less than their respective means.
3.2. Prevalence of pathogens
The study found that 87.5% of boreholes had detectable E. coli during the rainy season and 72.5% during the dry season. Escherichia
coli was detected in groundwater samples from all BHs during the rainy season, except for Village A village, where only 50% of BHs
tested positive for E. coli in both dry and rainy seasons. The WHO states that drinking water should not contain any detectable E. coli.
The prevalence of pathogens in sludge from pit latrine (HW) (Fig. 3) and WW from septic tank (Fig. 4) from the on-site sanitation
systems across the four villages. Overall, ETEC was the most common pathogen in both faecal sludge and wastewater and Shigella
exneri was the least prevalent pathogen. Campylobacter was not detected in any of the sites, while in Village D village, all the target
pathogens were not detected in both faecal sludge and WW from septic tank. The highest ETEC incidence was found in faecal sludge
from Village C throughout both the wet (75%) and dry (40%) seasons. The WW from septic tank from Village A exhibited the highest
ETEC incidence in the wet (66.7%) and the dry (45.8%) seasons among the target pathogens. Shigella exneri and Salmonella Typhi-
murium were only detected at low rates in human waste (6.7% & 1.7%) and WW from septic tank (5% & 10%) from Village C during
the rainy season. The presence of the target pathogens in groundwater differed across the four villages (Fig. 4). Except for
Campylobacter jejuni which was not detected in any of the groundwater samples from all four villages, these water sources displayed all
the target pathogens, with ETEC and Salmonella typhimurium being the most prevalent pathogens. The prevalence of pathogens in
groundwater samples from the Village A and Village B villages was low. In Village A, Salmonella typhimurium was detected in 21.3% of
groundwater samples in the dry and ETEC was detected in 7.5% of groundwater samples in the wet and 6% of groundwater samples in
the dry season. Salmonella typhimurium was the only pathogen that was detected in Village B village in 25% of the groundwater
samples during the dry season. Salmonella typhimurium, Shigella exneri and ETEC were detected in groundwater samples from Village
C and Village D villages and they were mainly prevalent during rainy seasonal conditions. The ndings further demonstrated that the
target pathogens were not detected in all of the sampled boreholes (Table 5); in fact, none of the target pathogens were present in
several boreholes sampled in the Village B and Village A villages. The overall results showed that Shigella exneri was detected in 21.4%
(n =15) of the boreholes in the rainy season and 2.9% (n =2) in the dry season. Salmonella typhimurium was detected in 22.7% (n =
18) of the boreholes in the wet and 18.6% (n =13) in the dry season. At the same time, ETEC was detected in 24.3% (n =17) of the
boreholes in the wet and 5.7% (n =4) in the dry season. A summary of the concentration of the detected pathogens in groundwater,
faecal sludge and wastewater is displayed in Table 6 as log copies per 100
μ
L or per gram. The concentration of the detected pathogens
was the same across all samples. Overall, the concentrations ranged from 1.99 to 2.11 EGC/gram in faecal sludge; 2.05 to 2.11 EGC/
100 mL in wastewater and 2.03 to 2.12 EGC/100 mL in groundwater.
Table 4
Summary statistics of the measured lateral distance (m) between on-site sanitation facilities and boreholes.
Village A
20 HHs
Village B
20 HHs
Village C
20 HHs
Village D
10 HHs
Overall
70 HHs
Minimum 15 11 22 12 11
Maximum 75 66 81 55 81
Mean 41.25 32.4 44.75 33.9 38.1
≥50 m 5 (25%) 2 (10%) 7 (35%) 2 (10%) 16 (22.9%)
SD 13.68 13.92 15.24 13.84 14.17
Standard deviation (SD); metre (m); greater or equal to (≥).
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
8
3.3. Relationship between pathogens in boreholes and sanitation systems
The results of a point-biserial correlation analysis between the presence/absence of pathogens in boreholes and OSS facilities
(wastewater and human waste) ranged from very weak (r = − 0.093) to moderate (r = − 0.358) correlation (Table 7). In Village A, a
negative moderately signicant correlation was established for the presence of ETEC in the wet (r = − 0.514; p =0.020*) and a weak
negative correlation in the dry season (r = − 0.333; p =0.151). In Village B, no signicant correlation was established between
boreholes and sanitation facilities in terms of Salmonella typhimurium (r =0.145; p =0.541). In Village C, low negative correlations
Fig. 3. Prevalence of pathogens (Namely: Salmonella typhimurium, Shigella Flexneri, and ETEC) in human waste from pit latrines and wastewater
from septic tanks across four villages for the wet and dry seasons. The bar charts are displayed with percentage error bars.
Fig. 4. Prevalence of pathogens (Namely: Salmonella Typhimurium, Shigella Flexneri, and ETEC) in groundwater samples from household boreholes
during wet and dry seasons. The bar charts are displayed with percentage error bars.
Table 5
Overall number of boreholes contaminated with the target pathogens.
Target pathogen Season A
20 BHs
B
20 BHs
C
20 BHs
D
10 BHs
Overall
70 BHs
Shigella exneri Wet 0 0 14 (70%) 1 (5%) 15 (21.4%)
Dry 0 0 1 (5%) 1 (5%) 2 (2.9%)
Salmonella typhimurium Wet 0 0 14 (70%) 4 (20%) 18 (25.7%)
Dry 5 (25%) 6 (30%) 2 (10%) 0 13 (18.6%)
ETEC Wet 2 (10%) 0 10 (50%) 5 (25%) 17 (24%)
Dry 2 (10%) 0 1 (5%) 1 (5%) 4 (5.7%)
Note: Village A (A); Village B (B); Village C (C); Village D (D); boreholes (BHs); enterotoxigenic E. coli (ETEC).
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
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for Shigella exneri, Salmonella typhimurium, and ETEC were determined in the rainy season. A similar result was also observed in
Village D village, where no relationship was established between the pathogens detected in groundwater and those in household WW
from septic tank and human waste from the pit latrines.
3.4. The relationship between contaminants in groundwater and the lateral distance
In this study, E. coli was used as an indicator bacterium for the presence of faecal pollution, the results of average E. coli counts for
each borehole are displayed in (Table S4). The results of Pearson’s correlation between E. coli concentrations in groundwater and the
measured distance between OSS facilities and boreholes are displayed in Table 8. All the correlations were positive except for one,
namely Village A in the dry season (r = − 0.1155). The results ranged from very weak to moderate positive correlations. In general, no
correlation was recorded (r =0.1642, p =0.1744) for the rainy season, while statistically, a signicant difference between the two
parameters was found, although the correlation was not established (r =0.2504, p =0.0365*) for the dry season. In Village C, a
signicant moderate correlation was established for the dry season (r =0.5481, p =0.0123*).
Figs. 5–8 displays the association between quantities of E. coli in groundwater during the wet and dry seasons and the lateral
distance between the borehole and the on-site sanitation facility in the yards of households located in the four villages. Overall,
variations were observed in lateral distances between the boreholes and the sanitation facilities located across the four villages. The
results also showed that the concentration of E. coli was high in groundwater samples even though the household sanitation facility was
located far away from the borehole. For example, in Village D (Fig. 8), borehole BH7 was found to have the highest E. coli counts (117
CFU/100 mL), while the measured distance between the OSS and the borehole was 55 m. The same was evident in Village C (Fig. 7),
where BH14 was found to have the highest E. coli concentration (169 CFU/100 mL) during the rainy season and the measured distance
was 81 m. However, the opposite was observed for BH9 in Village A (Fig. 5), where the measured distance was 75 m and the E. coli
concentration was zero for the dry season and very low (10 CFU/100 mL) for the rainy season.
The overall results of the association between the presence/absence of pathogens in groundwater and the measured distances of on-
site sanitation facilities to boreholes at the abstraction point ranged from very weak (r =0.0071) to moderate (r =0.5258) correlations
(Table 9). The correlation in Village A and Village B villages was not calculated because most of the target pathogens were not detected
in groundwater samples. In Village D, weak correlations were established between most pathogens and the borehole distance to
Table 6
Concentrations of pathogens (equivalent genome copies (EGC) per 100 mL or per gram) in groundwater, faecal sludge, and wastewater.
Village
Shigella exneri Salmonella typhimurium Enterotoxigenic Escherichia coli
Mean (std) Mean (std) Mean (std)
Village A Total (n) Wet Dry Wet Dry Wet Dry
Groundwater 80 0 0 0 2.08 (0.04) 2.12 (0.01) 2.09 (2.02)
Faecal Sludge 56 0 0 0 0 2.06 (0.02) 2.07 (2.02)
Wastewater 24 0 0 0 0 2.07 (0.02) 2.06 (0.02)
Village B
Groundwater 80 0 0 0 0 2.03 (0.04) 0
Faecal Sludge 64 0 0 0 0 2.11 (0.005) 0
Wastewater 16 0 0 2.05 (1.02) 0 2.11 (0) 0
Village C
Groundwater 80 2.14 (0.17) 2.09 (0) 2.90 (3.95) 2.10 (0) 2.09 (0.007) 2.09 (0)
Faecal sludge 60 2.05 (0.01) 0 1.99 (0) 0 2.02 (0.05) 2.06 (0.03)
Wastewater 20 2.08 (0) 0 2.06 (0.04) 0 2.22 (0.30) 2.09 (0)
Village D
Groundwater 40 2.04 (0.01) 2.02 (0.02) 2.05 (0.03) 2.08 (0.01) 2.10 (0.42) 2.10 (0.01)
Faecal sludge 28 0 0 0 0 0 0
Wastewater 12 0 0 0 0 0 0
Table 7
Correlations between the presence/absence of pathogens in boreholes and OSS systems (wastewater and sludge from pit latrine).
Shigella exneri Salmonella typhimurium ETEC
Wet Dry Wet Dry Wet Dry
Village A NC NC NC NC r = − 0.514
p =0.020*
r = − 0.333
p =0.151
Village B NC NC NC r =0.145
p =0.541
NC NC
Village C r = − 0.096
p =0.686
NC r = − 0.111
p =0.641
NC r = − 0.229
p =0.331
NC
Village D NC NC NC NC NC NC
Overall r = − 0.093
p =0.429
NC r = − 0.111
p =0.360
r =0.145
p =0.231
r =-0.358
p =<0.01*
r =-0.333
p =0.004*
Pearson’s correlation (r); p-value (p); signicant (*); not calculated (NC) due to low pathogen numbers or pathogens not detected.
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
10
sanitation facilities, while in Village C, the correlation was recorded to be moderately signicant, especially for Shigella exneri in the
dry season (r =0.5458; p =0.0128).
4. Discussion
Pit latrines and ush toilets connected to septic tanks are effective in reducing disease spread, but improper construction can lead to
groundwater contamination. The minimum recorded distance between the OSS facility and the borehole was 11 m, which was in line
with the ndings of a study conducted by Ref. [15] in Muledane. The measured distances in homes were clustered around the mean, as
the standard deviations were less than their respective means for all four villages. Furthermore, the results revealed that overall, 22.9%
of HHs complied with the national norms and standards of SA. The yards in Village C households were oversized compared to other
villages, 35% of households could maintain a ≥50 m distance. Households with two to three yards and farms have sufcient space to
maintain distance between boreholes and OSS facilities. Maintaining safe spaces is crucial to protect groundwater sources from faecal
Table 8
Correlations between E. coli concentration in groundwater and distance between OSS facilities
and boreholes in household yards across the four villages.
Villages Season Correlation
Village A Wet r =0.08833, p =0.7112
Dry r = − 0.1155, p =0.6277
Village B Wet r =0.279, p =0.233
Dry r =0.2981, p =0.2018
Village C Wet r =0.1015, p =0.6703
Dry r =0.5481, p =0.0123*
Village D Wet r =0.5452, p =0.1031
Dry r =0.288, p =0.419
Overall Wet r =0.1642, p =0.1744
Dry r =0.2504, p =0.0365*
Pearson’s correlation (r); p-value (p); *signicant.
Fig. 5. Concentrations of E. coli (CFU/100 mL) in groundwater samples during the wet and dry seasons and the measured distance between OSS
facilities and boreholes in household yards in Village A village. This gure displays the association between the E. coli concentration in groundwater
and the measured distance between the OSS facility and borehole for each sampled household. The concentration differences are also indicated.
Fig. 6. Concentrations of E. coli (CFU/100 mL) in groundwater samples during the wet and dry seasons and the measured distance between OSS
facilities and boreholes in household yards in Village B village. This gure displays the association between the E. coli concentration in groundwater
and the measured distance between the OSS facility and borehole for each sampled household. The concentration differences are also indicated.
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
11
contamination. The WHO states that water intended for drinking should not contain any detectable E. coli. Only 45 samples in the rainy
and 90 samples in the dry seasons met the WHO standard for drinking water. In Village A, 50% of BHs had zero E. coli counts, with a 41
m lateral distance between boreholes and OSS systems, ranging from 15 to 75 m. The presence of E. coli in boreholes indicates that
groundwater from these specic sites is at greater risk of possible enteric pathogens being present [32]. The results showed that one or
more of the following pathogens were detected in groundwater: Shigella exneri, Salmonella typhimurium and ETEC. The ndings are
comparable to those of [16], in which the same pathogens were detected in groundwater samples from boreholes used by school-
children in the Vhuronga 1 Circuit in the VDM region.
Evidence suggests that during the rainy season, faecal contamination is frequently detected at higher concentrations [33,34]. The
Fig. 7. Concentrations of E. coli (CFU/100 mL) in groundwater samples during the wet and dry seasons and the measured distance between OSS
facilities and boreholes in household yards in Village C village. This gure displays the association between the E. coli concentration in groundwater
and the measured distance between the OSS facility and borehole for each sampled household. The concentration differences are also indicated.
Fig. 8. Concentrations of E. coli (CFU/100 mL) in groundwater samples during the wet and dry seasons and the measured distance between OSS
facilities and boreholes in household yards in Nkhakanjhaka village. This gure displays the association between the E. coli concentration in
groundwater and the measured distance between the OSS facility and borehole for each sampled household. The concentration differences are
also indicated.
Table 9
Correlations between the presence/absence of pathogens in groundwater samples and the distance between the borehole and OSS facility in
household yards across the four villages.
Pathogen Season Village A Village B Village C Village D Overall
Shigella exneri Wet NC NC r = − 0.3186
p =0.1709
r =0.291
p =0.414
r = − 0.014
p =0.908
Dry NC NC r =0.5458
p =0.0128*
r =0.5083
p =0.1336
r =0.5258
p =<0.0001*
Salmonella typhimurium Wet NC NC r =0.0465
p =0.8455
r =0.316
p =0.374
r =0.1812
p =0.1333
Dry r =0.4284
p =0.0595
r =0.5441
p = − 0.1442
r =0.1477
p =0.5344
NC r =0.3734
p =0.0014*
ETEC Wet r =0.1645
p =0.4883
NC r = − 0.3380
p =0.1450
r =0.195
p =0.589
r =0.0071
p =0.9534
Dry r =0.1767
p =0.4562
NC r =0.2597
p =0.2688
r =0.412
p =0.237
r =0.2828
p =0.017*
Not calculated (NC); Pearson’s correlation (r); p-value (p); *moderately signicant.
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
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study found a higher prevalence of Salmonella typhimurium, Shigella exneri and ETEC in Village C and Village D during the rainy
season, while Salmonella typhimurium was detected in Village A and Village B villages during the dry season. Enterotoxigenic
Escherichia coli and Salmonella typhimurium were the most prevalent pathogens in groundwater. Shigella exneri was the least prevalent
pathogen; this nding agrees with the results of a study by Ref. [35] where Shigella was found to be the least dominant pathogen in
groundwater from boreholes. Shigella exneri is among the most common diarrhoeagenic pathogens in groundwater in the rural
districts of the Limpopo Province [36]. In a study conducted by Ref. [14], ETEC was isolated from groundwater in the VDM region.
Despite using a probe-based real-time PCR assay, there was no presence of Campylobacter jejuni in any of the borehole groundwater
samples. Campylobacter concentrations in contaminated drinking water are typically low, with less than ten CFU per litre. Due to their
microaerophilic properties, they have a low environmental survival probability. In Village B, pathogens were found in 6 boreholes
during the dry season, while in Village A, they were found in 2 and 7 boreholes during the wet and dry seasons, respectively. The
presence of pathogens in groundwater raises concerns about its suitability for drinking, as it is often used without treatment,
potentially posing health risks to community members, particularly children and immunocompromised households. Many believe it
requires little treatment before consumption [37]. According to data from our previous study [26] most households (92.9%) in these
sites do not treat water before use, and 34.3% are unaware of household water treatment methods.
The study revealed signicant variations in pathogen presence in sludge from pit latrines and WW from septic tanks. The most
prevalent pathogen was ETEC in both human waste (75%) and wastewater (66.7%), and the least prevalent pathogen was Shigella
exneri in human waste (1.7%) and wastewater (1.4%). Enterotoxigenic Escherichia coli was prevalent primarily in wastewater and
human waste from Village A and Village C villages. Sludge characteristics in pit latrines vary signicantly within the same municipality
or town [38]. The difference depends on user practices, such as diets and anal cleansing products [39]. The study reveals that
pathogens detected in human waste from pit latrines and septic tanks in the VDM region are common or endemic, as conrmed by
studies on diarrheal diseases and enteric pathogen infections. For example, in a cross-sectional study by Ref. [40], ETEC was detected
in 27.9% of stool specimens, and it was concluded that enteric pathogen co-infection is the major cause of diarrhea in children in the
VDM region. Enterotoxigenic Escherichia coli is a pathogenic agent causing acute diarrhea in children under ve years in underde-
veloped nations [41].
The study found a very weak (r = − 0.093) to moderate (r = − 0.541) association between pathogens in groundwater and on-site
sanitation systems. This implies that when the pathogens were detected in groundwater, they were absent in the sanitation
compartment and vice-versa. For ETEC, there was a statistically signicant moderate negative correlation in the rainy season (r =
−0.358; p =0.01*), implying that there was some relationship between detected ETEC in groundwater and OSS systems, though it was
not particularly strong. Consequently, the detected pathogens in groundwater samples from the boreholes could be directly originating
from the waste generated by the OSS systems. Nevertheless, in Village D village, none of the target pathogens were detected in
wastewater and human waste, and yet the pathogens were detected in groundwater samples. In our previous research [26] the faecal
pollution sources found in the groundwater of Village D village were (Cytb-Chicken, BacCan-Dogs as well as Pig-2Bac-Pig). None of the
human markers were detected. This implies that animals are the sources of faecal contamination in groundwater from this village and
that the OSS systems in Village D village might not have an impact on the quality of groundwater. There was no association between
the pathogens in boreholes and those in OSS systems in this village.
Regarding the relationship between E. coli in groundwater and the lateral distance between OSS facilities and boreholes, the
statistical analysis indicated a very weak non-signicant association (r =0.1642, p =0.1744) for the rainy season and a weak sig-
nicant positive correlation (r =0.2504, p =0.0365) for the dry season. In Village C, a signicant moderate correlation was estab-
lished for the dry season (r =0.5481, p =0.0123*). The positive correlation indicates that as the borehole distance from the OSS
increases, so do the levels of contaminants, and vice versa. Despite the household sanitation facility’s distance from the borehole, some
boreholes had high E. coli concentrations in groundwater samples (Fig. 5). The concentration of E. coli in groundwater was not strongly
inuenced by the measured distance between the OSS facility and the borehole. The literature suggests that the geological structure of
water points, well design, and proximity to OSS facilities are the primary factors inuencing E. coli occurrence [42]. The study found
that the distance between OSS facilities and boreholes in the same yard did not signicantly impact the presence of E. coli in
groundwater samples from the boreholes, suggesting that the concentration of E. coli does not signicantly depend on the distance. The
study hypothesized that on-site sanitation facilities might have an impact on the groundwater quality, i.e. the shorter the distance
between the borehole and the OSS facility, the higher the E. coli concentrations. The study results showed that pathogens were detected
in groundwater even when the OSS facility was located far away from the borehole abstraction point. This was evident in Village C,
where the distance between OSS facilities and boreholes was measured to be ≥50 m in 60% of HHs; however, most of the target
pathogens were detected in the borehole water samples.
The study found no signicant correlation between the distance between OSS facilities and boreholes and pathogens’ existence or
lack in groundwater. The results align with previous research in Zambia, where [43] found no strong relationship between the distance
from a borehole to a soakaway and groundwater quality. In another study in Zambia [44], found no distinct relationship between the
distance from the borehole to the septic tank and the quality of borehole water in Kitwe West Township. These ndings suggest that
groundwater quality is not signicantly inuenced by the distance between boreholes and septic tanks. Conversely [45], found a
positive correlation between mean length (23.48 m) and E. coli in dry and rainy seasons. Contaminants were found to increase with
distance from septic tank systems. A study by Ref. [46] found a moderate negative correlation between distance from the latrine and
coliform count. While [47] found a signicant increase in TCC and FCC with a decrease in distance between wells and latrines. In South
Africa, the national norms and standards released by the Department of Water and Sanitation in 2017, mandate sanitation facilities to
be at least 50 m away from any groundwater source. Groundwater contamination is more common in sedimentary [48]. Village B and
Village C villages share similar geology, however, pathogen detection in groundwater differed. Pathogens in Village B’s groundwater
J.M. Sekgobela et al.
Heliyon 10 (2024) e27271
13
were low compared to those in Village C, despite the average lateral distance between the borehole and sanitation facility being 32.4
m, which is signicantly shorter than the measurement in Village C (44.75 m). The study suggests neither geology nor distance
signicantly affects pathogen presence/absence.
5. Conclusion
This study aimed to track enteric pathogens from OSS facilities to boreholes and assess the sitting of OSS facilities in relation to
boreholes. The ndings showed that most households were unable to comply with national norms and standards regarding the distance
between OSS facilities and groundwater sources. The lowest measured distance between the borehole and the OSS facility was 11 m.
Proper management and maintenance of OSS facilities and waste are crucial to protect groundwater sources. Groundwater samples
from boreholes tested positive for E. coli, Shigella exneri, Salmonella typhimurium, and ETEC, but not all the boreholes. The con-
centration of the detected pathogens was similar across all samples. The presence of the same concentration of the pathogen in
groundwater, fecal sludge and wastewater could indicate a potential contamination source. This suggests that the pathogens detected
in groundwater could be from the waste generated by the OSS systems. The study recommends strategic measures to protect
groundwater sources and education of community members on safe management of sanitation facilities and groundwater to counteract
public health risks.
5.1. Study limitations
The current study focused on microbiology and molecular analysis, by detecting pathogens in groundwater, septic tank WW and
faecal sludge. There was no data on the depth of the sampled boreholes and geohydrology of the study sites. For future studies, there
should be a collaboration between microbiologists, hydrogeologists, and environmental engineers to have more comprehensive data
on groundwater contamination assessment.
Data availability statement
The data associated with this study has not been deposited into a publicly available repository. All the data that support the ndings
of this study are available on request, from the corresponding author.
CRediT authorship contribution statement
Jeridah Matlhokha Sekgobela: Writing – review & editing, Writing – original draft, Methodology, Formal analysis. Colette
Mmapenya Khabo-Mmekoa: Writing – review & editing, Supervision. Maggy Ndombo Benteke Momba: Writing – review & editing,
Visualization, Validation, Supervision, Resources, Project administration, Funding acquisition, Conceptualization.
Declaration of competing interest
We can disclose that we have no conicts of interest. The study was conducted based on the requirement of the ethics clearance
approved by the Faculty of Science Research Ethics Committee (FCRE) at the Tshwane University of Technology (TUT) (FCRE 2019/
09/017 (FCPS 03) (SCI)).
Acknowledgments
The authors gratefully acknowledge the national research foundation (NRF) and the Department of Science and Innovation (DSI)
for funding our research under the South African Research Chairs Initiatives (SARChI) for Water Quality and Wastewater Management
(UID87310). Additional funding was received from Tshwane University of Technology. Special thanks to the chiefs of the villages, as
well as the members of the households, for their participation in this study. The authors would like to acknowledge the assistance of
Tshwane University of Technology Water Research Group Students: Arinao Murei, Mulalo Mudau, Barbara Mogane, Dikeledi Mothiba,
Opelo Mochware and Ndamulelo Musumuvhi for their assistance during sample collection and analysis.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e27271.
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