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Article

Antibiotic Resistance Patterns of Escherichia coli from Children’s Sandpits in Durban, South Africa: A Point Prevalence Study

by
Tasmiya Rangila
1,†,
Andiswa Zondo
1,†,
Andiswa Mtshali
1,†,
Najiha Ismail Suleman Tar
1,†,
Uzair Shabbir Dada
1,†,
Etando Ayukafangha
2 and
Akebe Luther King Abia
2,3,4,*
1
College of Health Science, University of KwaZulu-Natal, Private Bag X54001, Durban 4000, KwaZulu-Natal, South Africa
2
Antimicrobial Research Unit, College of Health Science, University of KwaZulu-Natal, Private Bag X54001, Durban 4000, KwaZulu-Natal, South Africa
3
Total Environment Research (TEN-R) Group, College of Health Science, University of KwaZulu-Natal, Private Bag X54001, Durban 4000, KwaZulu-Natal, South Africa
4
Environmental Research Foundation, Westville, Durban 3630, KwaZulu-Natal, South Africa
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Hygiene 2026, 6(1), 3; https://doi.org/10.3390/hygiene6010003
Submission received: 17 November 2025 / Revised: 15 December 2025 / Accepted: 9 January 2026 / Published: 11 January 2026
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Abstract

Background/Objectives: Although children’s playgrounds foster physical, cognitive and emotional health, sandpits can harbour antibiotic-resistant bacteria, representing a health concern for kids. Therefore, this point prevalence study investigated the presence and antimicrobial resistance of Escherichia coli in sandpits at four schools in Durban to ascertain the potential risk to schoolchildren and inform school authorities of the need to prevent such occurrences. Methods: Twenty samples were collected from schools on a single day. E. coli was isolated using colilert-18® and confirmed using PCR. Antibiotic susceptibility testing was performed against 19 antibiotics using the disc diffusion method and Clinical and Laboratory Standards Institute (CLSI) guidelines. Results: E. coli was detected in 2/4 schools (50%), yielding 100 pure isolates. Of these, 71% (31 Site B and 40 Site C isolates) were resistant to at least one of the antibiotics tested, displaying 36 antibiograms. The highest resistance was to CFX (n = 40), and the lowest was to AMK and MEM (n = 1). All isolates were susceptible to CIP, CHL, GEN and TZP. At Site B, the highest resistance was against CFX (n = 16) and the lowest against AMK, CTX and NAL (n = 1). The highest resistance at Site C was against TET (n = 26), and the lowest against ATH and AUG (n = 1). Twenty isolates (20%) were multidrug-resistant, displaying resistance to at least one antibiotic from 3 classes. Conclusions: These results show that children with poor hygiene practices could get sick from playing in sandpits. Schools must change their sand regularly and ensure that sandpits are constantly exposed to the sun.

1. Introduction

Children’s playgrounds are crucial for fostering physical health through active play, developing essential social skills like cooperation and conflict resolution, enhancing cognitive functions such as problem-solving, and supporting emotional well-being by promoting autonomy and resilience through safe risk-taking and creative exploration in an unstructured environment [1,2,3,4]. However, these essential structures must be properly designed to ensure that children are free from injury [5,6]. Although different materials have been used to design these spaces to improve safety, research shows that children prefer natural materials like wood and loose-fill options such as sand, dirt, leaves, and twigs, as these create a sense of the natural environment [7]. Specifically, in addition to being readily accessible and cost-effective, some studies have shown that sand can significantly reduce injuries during play by attenuating impact during falls [8,9,10].
Despite their demonstrated benefits, sandpits could harbour microorganisms, including potentially pathogenic ones, thus representing a health concern for users of these spaces. For example, a Polish study that collected sand from different localities within an urban area found that over 94% of the samples contained potentially pathogenic fungi [11]. Another study in Bulgaria showed that while sand samples collected from public playgrounds were free of toxic chemicals and parasites, bacterial species, including total coliforms, Escherichia coli, Enterococcus spp., and Clostridium perfringens, were identified. The authors attributed these findings to potential faecal contamination from external sources [12].
Due to the ubiquity of microorganisms in the environment, it is usually not feasible to investigate their full diversity and abundance. Although advanced methods like metagenomics have shown significant improvements in the way microorganisms are studied in the environment, they are limited by the fact that the cultivability or viability of the organisms cannot be ascertained since the technique heavily relies on nucleic materials (DNA or RNA), regardless of whether they are alive, dormant or dead [13,14]. Thus, many studies rely on investigating the presence of microbial indicators, the most frequently used faecal indicator being Escherichia coli [15,16,17]. However, in addition to being an indicator organism, E. coli has evolved to include several pathotypes capable of causing infections in humans and animals [18,19,20]. More disturbing is the fact that many of the pathotypes have also become resistant to most antibiotics used in human and veterinary medicine. These resistant strains are no longer confined to healthcare settings and are increasingly detected in community environments, including soil, water, and children’s play areas [21], making them the best organism to study antimicrobial resistance in humans, animals and the environment, as recommended by the World Health Organization (WHO) [22].
Although studies on sandboxes have been conducted in many countries, microbial quality studies of sand pits (like sandboxes) in South Africa are limited or nonexistent. Furthermore, most studies have focused on sandpits in public places, while those within schools have not been thoroughly investigated. Moreover, studies that explore the antibiotic resistance profiles of the isolated species are limited or nonexistent. This poses a potentially unidentified health risk to children using these sandpits in school premises, as children are particularly vulnerable to infections caused by diarrheagenic E. coli, primarily due to underdeveloped immune systems and frequent hand-to-mouth behaviour [23,24], especially under conditions of poor hygiene and sanitation. Therefore, this point prevalence study investigated the presence and antimicrobial resistance patterns of E. coli isolated from various schools in Durban, KwaZulu-Natal, to assess the potential risk to school children and to inform school authorities of the need to prevent such occurrences.

2. Materials and Methods

2.1. Sample Collection

This was a point prevalence study, and samples were collected on a single day from four different school sandpits within Durban. Five grab samples were collected aseptically from each sandpit; one from each corner of the pit and one from the centre to ensure coverage of the area. Approximately 250 g of sand were collected from each sampling point and transferred into a sterile, plastic, wide-mouth container with a lid. The samples were transported to the laboratory in cooler boxes containing ice (between 4 and 8 °C) for processing and E. coli isolation within 6 h of collection.

2.2. Enumeration and Molecular Confirmation of E. coli

Once in the laboratory, 50 g of each sample was weighed and transferred into 100 mL of distilled water. The mixture was shaken manually for about 2 min to dislodge the bacteria, then allowed to stand for 1 min. After that, 50 mL of the supernatant was transferred into a 100 mL sterile bottle and analysed using the Colilert-18® from IDEXX (IDEXX Laboratories (Pty) Ltd., Johannesburg, South Africa), according to the manufacturer’s instructions [25]. Samples were incubated at 35 °C for 24 h. After incubation, plates with wells showing growth (yellow colour due to the presence of total coliforms) were examined under UV light for fluorescence, indicating the presence of E. coli. Microbial counts will be expressed as the Most Probable Number (MPN) of bacteria per gram of sand.
The contents of 10–20 randomly selected fluorescent wells were aseptically collected and streaked onto Oxoid BrillianceTM E. coli/Coliform Selective Medium (Thermo Fisher Scientific, Randburg, South Africa) to obtain pure, presumptive E. coli isolates. The pure isolates were then streaked further onto Neogen® Nutrient Agar (Neogen Coorperation, MI, USA) and incubated at 35 °C for 24. After incubation, DNA was extracted from the isolates using the boiling method [26,27]. The extracted DNA was then used to confirm E. coli by polymerase chain reaction (PCR) using primers and optimised cycling conditions previously described [28]. Briefly, using the primers mdh-forward 5′-GGTATGGATCGTTCCGACCT-3′ and mdh-reverse 5′-GGCAGAATGGTAACACCAGAGT-3′, we amplified the E. coli housekeeping gene, malate dehydrogenase, under the following PCR cycling parameters: enzyme activation (98 °C for 50 s), denaturation (95 °C for 10 s), annealing (62 °C for 30 s), and final extension (72 °C for 20 s). This was followed by a melt-curve analysis from 73 °C to 95 °C, ramping at 0.2 °C per step, with a 2-s hold between steps. All reactions included a no-template control (the reaction mixture without template DNA) and a positive control (DNA from E. coli ATCC (American Type Culture Collection) 25922. The reactions were carried out on a QuantStudioTM 5 real-time PCR system (Thermo Fisher Scientific, Randburg, South Africa).

2.3. Determination of Antibiotic Resistance Profile of Isolates

For antibiotic resistance testing, the PCR-confirmed E. coli isolates were subcultured onto nutrient agar and incubated at 37 °C for 24 h. After incubation, the isolates were tested for susceptibility to 19 antibiotics using the Kirby–Bauer method [29] on Muller–Hinton Agar, according to the Clinical and Laboratory Standards Institute (CLSI) guidelines as previously described [30]. The antibiotics tested are listed in Table 1 (Davies Diagnostics [Pty], Ltd., Randburg, South Africa). The reference strain E. coli ATCC 25922 was used for quality control.

3. Results

3.1. Enumeration of E. coli from Sand Samples

The microbial counts (total coliforms and E. coli) were reported in most probable number (MPN) per 50 g of sand. The microbial counts varied across sites, with E. coli detected only at Sites B and C (Table 2). Furthermore, Site B harboured overall more E. coli per 50 g of sand than Site C.

3.2. Antimicrobial Susceptibility of Isolates

3.2.1. Overall Susceptibility

Isolates were classified as susceptible or resistant. A total of 100 pure isolates were obtained from both schools (50 from Site B and 50 from Site C). Seventy-one of the 100 isolates showed resistance to at least one of the 19 antibiotics tested in this study. Of these, 31 were from Site B and 40 from Site C, with the overall highest resistance observed against CFX (n = 40) and the lowest against AMK and MEM (n = 1 each). All isolates were susceptible to CIP, CHL, GEN and TZP (Figure 1).
However, the percentage of resistance to the various isolates varied across sites. At Site B, the highest resistance was against CFX (n = 16) and the lowest was against AMK, CTX and NAL (n = 1 each); all Site B isolates were susceptible to MEM, CAZ, CIP, CHL, TET, CRO, GEN, CPM, TZP, and PRL (Figure 2A). On the other hand, the highest resistance at Site C was against TET (n = 26) and the lowest was against ATH and AUG (n = 1 each); all Site C isolates were susceptible to AMK, CIP, CHL, IMI, GEN and TZP (Figure 2B).

3.2.2. Antibiograms and Multidrug Resistance

The 71 isolates that were resistant to at least one of the antibiotics tested displayed 26 distinct antibiograms; 20 of these isolates were multidrug-resistant (Table 3).

4. Discussion

The current study was a point prevalence assessment of the presence and antibiotic susceptibility profile of E. coli isolated from sand collected from children’s playgrounds in Durban, KwaZulu-Natal. E. coli was isolated from two of the schools investigated. Furthermore, 71 of the 100 pure isolates tested for antimicrobial susceptibility were resistant to at least one of the antibiotics tested, displaying diverse antibiograms. A considerable number of isolates were considered multidrug-resistant, with some simultaneously resistant to eight antibiotics.

4.1. Enumeration of E. coli

Sand from different environments has been reported to harbour different microbial species, including E. coli. A study in Australia reported that almost 50% of sandpits sampled were positive for E. coli, with counts reaching 104 per 100 g of sand [31].
In this point prevalence study, E. coli was detected in two of the four sandpits sampled (Table 2). Both sites operated an outdoor sandpit. Site B, with the highest E. coli count, was the largest of all the study sandpits and was uncovered. This exposed the sandpit to birds, rodents and monkeys. Birds have been reported to harbour and disseminate human pathogenic bacteria, including E. coli [32,33,34,35]. Studies have also reported similar roles with rodents [36,37,38] and monkeys [39,40]. Durban is particularly known for its large monkey population [41]. This could have contributed to the high number of E. coli isolated from Site B. Furthermore, the school authorities confirmed that the pit was usually visited by monkeys, especially after school hours (personal communication). Although Site C was also external, it was covered and closer to the classrooms, which may have kept animals away. Also, the school management reported that they usually sprayed the sand in the pit with diluted chlorine solution. Chlorine is well known as a disinfectant due to its excellent bactericidal properties [42,43,44,45,46]. Unlike Sites B and C, Sites A and B were not large sandpits that allowed full-body access for schoolchildren. These were relatively small sand basins where the kids could only play with their hands, and they were indoors. The sand in these smaller pits was also changed regularly, at times weekly, as reported by Site A’s management.
While E. coli is commonly used as an indicator of faecal pollution in the environment, some strains have acquired pathogenic potential over time and are now responsible for numerous human infections, including diarrhoea [47], urinary tract infections [48], neonatal meningitis [49] and haemolytic uraemic syndrome [50]. Although the E. coli isolated in the current study were not analysed for their pathotypes, they could still pose a potential health threat, given that the users of the sandpits investigated were children whose immune systems are still not fully developed. Furthermore, it has been reported that children aged 6–11 frequently engage in hand-to-mouth behaviours, up to 15 times per hour during outdoor activities [51]. Such practices have been associated with the transfer of E. coli and other pathogens from sand to mouth, potentially leading to gastrointestinal infections [24,52].

4.2. Antimicrobial Susceptibility of Isolates

Antibiotics, once considered the magical solution of modern medicine, are now associated with one of the biggest health challenges humanity faces. Bacteria are becoming resistant to almost all antibiotics known to man [53]. This is even more concerning because children are among the most vulnerable populations affected by this threat worldwide [20,54,55,56,57,58,59,60]. However, although current efforts to address antimicrobial resistance advocate a one health approach that calls for effective communication between all stakeholders, the environment has not received equal consideration as its human and animal sector counterparts [61].
In the current study, a remarkably high percentage (71%) of the isolates tested was resistant to at least one of the 19 antibiotics tested (Figure 1). This percentage was higher than that reported in the Austrian study, which found 19% resistance among its 98 isolates [31]. Although the study analysed a comparable number of isolates (98 vs. 100 in the current study), it included only eight antibiotics in its susceptibility testing, with the highest nonsusceptibility observed to ampicillin. The difference in the number of antibiotics tested could have accounted for the difference in the highest and overall percentage resistance observed between the two studies.
The highest overall resistance in the current study was recorded against cephalexin (Site B) and tetracycline (Site C) (Figure 2). Cephalexin is widely used in children due to its effectiveness in treating various bacterial infections, such as middle ear infections (otitis media), pharyngitis and tonsillitis (as an alternative for children allergic to penicillin), bone and joint infections, respiratory tract infections, skin and soft tissue infections, and uncomplicated genitourinary/urinary tract infections [62,63]. On the other hand, tetracycline is generally not recommended for children under 8 years of age due to the risk of permanent tooth discolouration and effects on bone growth. However, in specific, severe circumstances, certain tetracyclines, such as doxycycline, may be used in younger children for limited durations when other options are ineffective or contraindicated [64,65]. The high resistance of the study isolates to these two critical antibiotics, therefore, raises concerns about the use of these pits. Apart from these two, the isolates also showed considerable resistance to other critical antibiotics used in paediatric medicine. Examples include resistance against Ceftriaxone (effective and widely used to treat severe bacterial infections in children, such as meningitis, sepsis, and pneumonia) [66], azithromycin (widely used for specific bacterial infections, primarily respiratory tract, ear, and skin infections) [67] augmentin (amoxicillin/clavulanate potassium; used effective against paediatric bacterial infections, including otitis media, sinusitis, pneumonia, bronchitis, urinary tract infections, and skin and soft tissue infections [68].
Of greater concern regarding the isolates, 20% were multidrug-resistant (Table 3). Multidrug resistance (MDR) is resistance to at least one drug in three or more antimicrobial classes [69]. Multidrug resistance is associated with several problems, including increased mortality, higher healthcare costs, and treatment failure because infections become difficult or impossible to treat [70]. Beyond the clinical setting, MDR is a major challenge because the presence of multidrug-resistant bacterial species in non-clinical settings poses significant public health problems by acting as environmental reservoirs of resistant bacteria and resistance genes [71], facilitating their spread to the broader community, and complicating the treatment of common infections. This becomes particularly important in resource-limited settings, as they could increase the rate of community-acquired infections.
While the current findings show contamination of the sandpits studied, especially with antibiotic-resistant E. coli, the findings should be applied cautiously and should not be generalised for all sandpits in Durban. Given that this was a once-off sampling, a “hit” may not necessarily mean extreme microbial pollution, the same way a “miss” does not exclude the absence of pollution. Furthermore, the sampling approach, while presenting a snapshot of the microbial status of these sandpits on the sampling day and time, did not capture potential seasonal variations. Nevertheless, such sampling would not be valuable in terms of risk as the kids only use the sandpits during the warm summer months when the study was conducted, and the pits are closed during winter due to the bad weather conditions. Moreover, given children’s less developed immune systems, the presence of antibiotic-resistant bacteria in their playground should not be regarded as less important, even if determined only on a single day.

5. Conclusions

This point-prevalence study presents a snapshot of the antibiotic resistance profile of E. coli isolated from children’s sandpits in Durban, South Africa. Two of the four sites harboured E. coli exceeding 2 × 103 counts per 50 g of sand. Only outdoor pits were contaminated, due to their frequent exposure to animals, including birds. Furthermore, the results showed that outdoor sandpits were more susceptible to microbial contamination. Also, the isolates obtained showed a high percentage of resistance to most of the antibiotics evaluated, many of which are used to treat infections in children. The high number of isolates showing multidrug resistance is concerning, as the users of these pits are children with less developed immune systems. This also calls for studies using a One Health approach that considers samples from sandpits, kids using them, and commonly found animals around the sandpits.
However, it should be noted that the current study was a one-off sampling, and further studies with a larger number of samples collected across multiple rounds could provide a clearer picture of the actual situation. Also, a more in-depth analysis involving advanced genomic methods would be necessary to fully characterise the isolates, elucidating their pathogenic potential and genotypic resistance profiles. Furthermore, phylogenetic analysis could shed further light on the origin of these isolates by performing whole-genome sequencing and comparing their genomes with those of clinical and animal isolates. Notwithstanding these limitations, the current findings represent essential information for school authorities and call for improved hygiene and sanitation measures within school premises to protect the health of vulnerable children. When the kids are not using the pits, they must be covered using tight-fitting animal-proof covers specifically designed for sandpits. This would prevent contamination from animals. Exposing the sand to high-intensity sunlight while turning it regularly will allow for aeration, exposure to heat and UV light that act as natural disinfectants. Most importantly, the children must be taught to wash their hands after playing in the pit and not to eat when playing in the pit.

Author Contributions

Conceptualization, A.L.K.A.; methodology, T.R., A.Z., A.M., N.I.S.T., U.S.D. and E.A.; validation, A.L.K.A.; formal analysis, T.R., A.Z., A.M., N.I.S.T., U.S.D. and E.A.; investigation, T.R., A.Z., A.M., N.I.S.T., U.S.D. and E.A.; resources, A.L.K.A.; writing—original draft preparation, T.R., A.Z., A.M., N.I.S.T., U.S.D. and E.A.; writing—review and editing, A.L.K.A.; supervision, A.L.K.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Biomedical Research Ethics Committee of the University of KwaZulu-Natal (BREC/00009197/2025; 9 October 2025).

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Hygiene 06 00003 g001
Figure 1. Overall susceptibility across the schools studied. Only antibiotics with resistance were recorded and are presented on the graph. AMK = amikacin, AMP = ampicillin, ATH= azithromycin, AUG = augmentin, CPM = cefepime, CTX = cefotaxime, FOX = cefoxitin, CAZ = ceftazidime, CRO = ceftriaxone, CFX = cephalexin, IMI = imipenem, MEM = meropenem, NAL = nalidixic, acid, PRL = piperacillin, TET = tetracycline.
Figure 1. Overall susceptibility across the schools studied. Only antibiotics with resistance were recorded and are presented on the graph. AMK = amikacin, AMP = ampicillin, ATH= azithromycin, AUG = augmentin, CPM = cefepime, CTX = cefotaxime, FOX = cefoxitin, CAZ = ceftazidime, CRO = ceftriaxone, CFX = cephalexin, IMI = imipenem, MEM = meropenem, NAL = nalidixic, acid, PRL = piperacillin, TET = tetracycline.
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Figure 2. Susceptibility of the isolates, distributed according to School. (A) = School B; (B) = School C. AMK = amikacin, AMP = ampicillin, ATH = azithromycin, AUG = augmentin, CPM = cefepime, CTX = cefotaxime, FOX = cefoxitin, CAZ = ceftazidime, CRO = ceftriaxone, CFX = cephalexin, CIP = ciprofloxacin, CHL = chloramphenicol, GEN = gentamicin, IMI = imipenem, MEM = meropenem, NAL = nalidixic, acid, PRL = piperacillin, TZP = piperacillin–tazobactam, TET = tetracycline.
Figure 2. Susceptibility of the isolates, distributed according to School. (A) = School B; (B) = School C. AMK = amikacin, AMP = ampicillin, ATH = azithromycin, AUG = augmentin, CPM = cefepime, CTX = cefotaxime, FOX = cefoxitin, CAZ = ceftazidime, CRO = ceftriaxone, CFX = cephalexin, CIP = ciprofloxacin, CHL = chloramphenicol, GEN = gentamicin, IMI = imipenem, MEM = meropenem, NAL = nalidixic, acid, PRL = piperacillin, TZP = piperacillin–tazobactam, TET = tetracycline.
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Table 1. List of antibiotics used in the study.
Table 1. List of antibiotics used in the study.
Antibiotic ClassAntibioticAbbreviationDisk Concentration (µg)
Aminoglycoside Amikacin AMK30
AminoglycosideGentamicinGEN10
Beta-lactamAmpicillinAMP10
Beta-lactamPiperacillinPRL 100
Beta-lactamAugmentin AUG30
Beta-lactamPiperacillin–tazobactam TZP110
MacrolideAzithromycinATH15
Cephalosporin (4th Generation)Cefepime CPM 10
Cephalosporin (3rd Generation)CefotaximeCTX30
Cephalosporin (3rd Generation)CeftazidimeCAZ30
Cephalosporin (3rd Generation)CeftriaxoneCRO30
Cephalosporin (2nd Generation)CefoxitinFOX30
Cephalosporin (1st Generation)CephalexinCFX30
FluoroquinoloneCiprofloxacinCIP5
AmphenicolChloramphenicolCHL30
CarbapenemImipenemIMI10
CarbapenemMeropenemMEM10
Quinolone Nalidixic acidNAL30
TetracyclineTetracyclineTET30
Table 2. Microbial count per sampling site.
Table 2. Microbial count per sampling site.
SiteTotal Coliform Counts (MPN/50 g) *E. coli Counts (MPN/50 g)
School AA17.4ND
A23.0ND
A3>2419.6ND
A4195.6ND
A54.1ND
School BB1>2419.6>2419.6
B2>2419.6>2419.6
B3>2419.6>2419.6
B4>2419.6>2419.6
B5>2419.6275.5
School CC1102.298.1
C234.131.3
C3NDND
C4>2419.61.0
C5307.690.8
School DD1>2419.6ND
D226.5ND
D3NDND
D42.0ND
D51.0ND
* ND = Not Detected; > Indicates that the microbial count was above the detection limit of the Colilert-18®/Quantitray-2000® methods.
Table 3. Antibiograms of E. coli isolated from sandpits.
Table 3. Antibiograms of E. coli isolated from sandpits.
AntibiogramNumber of IsolatesIsolates
School BSchool C
ATH4B30, B23, B28,C46
CFX15B7, B9, B11, B12, B14, B15, B16, B35, B46,C32, C33, C34, C41, C42, C43
AUG3B25, B39, B43
TET9 C16, C17, C18, C20, C21, C22, C23, C24, C29
NAL5B22, B29, B33, B37, B44
AMK-AUG1B38
AUG-CFX3B8, B41, B40
AUG-NAL1B42
CFX-TET3 C25. C27, C31
CFX-AMP1 C36
ATH-CFX3B2, B6, B10
ATH-NAL1B19
NAL-TET5 C2, C4, C5, C13, C14
CTX-TET1 C19
CFX-AMP-TET1 C30
CFX-NAL-TET1 C10
MEM-CFX-TET1 C28
CFX-AMP-NAL-TET1 C26
ATH-FOX-CFX-IMI-AMP1B4
ATH-AUG-FOX-CFX-IMI-NAL1B1
CTX-CAZ-CFX-NAL-CPM-CRO1 C50
CTX-CFX-AMP-CPM-CRO-PRL4 C8, C11, C12, C25
AUG-CTX-FOX-CAZ-CFX-AMP-CRO1 C7
CTX-CFX-AMP-NAL-TET-CPM-CRO-PRL1 C9
AUG-CTX-FOX-CAZ-CFX-AMP-NAL-TET-CRO2 C3, C6
AUG-CTX-FOX-CAZ-CFX-AMP-TET-CRO-PRL1 C1
AMK = amikacin, AMP = ampicillin, ATH = azithromycin, AUG = augmentin, CPM = cefepime, CTX = cefotaxime, FOX = cefoxitin, CAZ = ceftazidime, CRO = ceftriaxone, CFX = cephalexin, IMI = imipenem, MEM = meropenem, NAL = nalidixic, acid, PRL = piperacillin, TET = tetracycline.
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Rangila, T.; Zondo, A.; Mtshali, A.; Tar, N.I.S.; Dada, U.S.; Ayukafangha, E.; Abia, A.L.K. Antibiotic Resistance Patterns of Escherichia coli from Children’s Sandpits in Durban, South Africa: A Point Prevalence Study. Hygiene 2026, 6, 3. https://doi.org/10.3390/hygiene6010003

AMA Style

Rangila T, Zondo A, Mtshali A, Tar NIS, Dada US, Ayukafangha E, Abia ALK. Antibiotic Resistance Patterns of Escherichia coli from Children’s Sandpits in Durban, South Africa: A Point Prevalence Study. Hygiene. 2026; 6(1):3. https://doi.org/10.3390/hygiene6010003

Chicago/Turabian Style

Rangila, Tasmiya, Andiswa Zondo, Andiswa Mtshali, Najiha Ismail Suleman Tar, Uzair Shabbir Dada, Etando Ayukafangha, and Akebe Luther King Abia. 2026. "Antibiotic Resistance Patterns of Escherichia coli from Children’s Sandpits in Durban, South Africa: A Point Prevalence Study" Hygiene 6, no. 1: 3. https://doi.org/10.3390/hygiene6010003

APA Style

Rangila, T., Zondo, A., Mtshali, A., Tar, N. I. S., Dada, U. S., Ayukafangha, E., & Abia, A. L. K. (2026). Antibiotic Resistance Patterns of Escherichia coli from Children’s Sandpits in Durban, South Africa: A Point Prevalence Study. Hygiene, 6(1), 3. https://doi.org/10.3390/hygiene6010003

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