Bacteriological Profile and Antibiotic Resistance Patterns of Wastewater Effluents in 2 Hospitals of Ethiopia

Abstract

The wastewater effluent is a hotspot for a multitude of microorganisms, including environmental pathogens, true human pathogens, and animal pathogens. In the absence of standardized wastewater treatment facilities, these pathogens contaminate surface and groundwater, further contributing to the spread of drug-resistant bacteria. This study aimed to investigate the bacteriological profiles and antibiotic resistance patterns in hospital wastewater in Addis Ababa, Ethiopia. A cross-sectional study was conducted from September 2023 to March 2024. Wastewater samples were collected from 2 hospitals using a grab sampling technique. Bacteria were identified using standard biochemical tests and MALDI-TOF Mass Spectrometry. Antibiotic susceptibility testing was performed using the Kirby-Bauer disk diffusion method. Data were verified for completeness and analyzed using the Statistical Package for the Social Sciences version 27. From the total samples collected, 219 bacterial isolates were recovered. The dominant bacteria were K. pneumoniae (57/219; 26%) and E. coli (47/219; 21.5%). K. pneumoniae showed the highest resistance levels to cefuroxime and tetracyclines, each (32/57; 85.1%). The magnitude of ESBLs and carbapenemase producers were (37/195; 19%), and (6/195; 3.1%), respectively. Overall, (115/219; 52.5%) of the isolates were multidrug-resistant. Wastewater generated from hospitals contaminate downstream rivers and pose public health risk. Therefore, proper wastewater treatment is needed.

Keywords

multidrug resistance infection control public health hospital environment

Introduction

Antimicrobial resistance (AMR) particularly antibiotic resistance (ABR) is the main global public health problem that threatens drug efficacy and jeopardizes countless lives and decades of medical achievements. Recognizing this problem, the World Health Organization (WHO) has declared ABR as 1 of the top 10 global health challenges facing humanity.¹ The spread of drug-resistant bacterial infections was estimated to cause 4.95 million deaths in 2019, and projections suggest that this number could exceed 10 million by 2050.²

Hospital wastewater (HWW) is a critical hotspot where pathogenic bacteria and opportunistic pathogens interact with high concentrations of antibiotic residues, disinfectants, and other pharmaceutical agents. Each inpatient is estimated to use 40 to 60 L of water per day, resulting in significant wastewater production in hospital settings.³ Untreated or inadequately treated wastewater effluents released into water bodies contribute to the development of superbugs that are resistant to many antibiotics, including the last-resort option. This condition exacerbates the spread of drug-resistant bacteria in natural ecosystems and poses a threat to public health.^4,5

Many resistant bacteria, such as Klebsiella species, Pseudomonas species, E. coli, Enterococcus species, and Staphylococcus aureus, were reported from HWW, which come from different patient wards.^6-8 Studies have also shown that HWW often harbors extended-spectrum beta-lactamases (ESBLs) and carbapenemase-producing (CP) bacteria, which are major obstacles to treating patients with ABR in the clinical setting, as they confer resistance to many antimicrobial classes.^9-11 ESBL-producing E. coli and CP K. pneumoniae were detected in Ethiopian and Indian hospital effluent, with a percentage of 21.8% and 17%, respectively.^10,12 Similarly, carbapenem-resistant bacteria were reported from Nepal, where E. coli (44%) were the dominant species followed by K. pneumoniae (24%).¹³

WHO also released its first worldwide study on ABR in April 2014, which shows high rates of resistance in both the community and nosocomial infections, and published lists of bacterial species in 2024 for which research and drugs were frequently needed.¹⁴ These bacterial species are grouped as ESKAPEE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and E. coli).¹⁵ Therefore, WHO statistics indicate that wastewater from clinical settings is a major worldwide source of ABR bacteria.¹⁶

The lack of standardized wastewater treatment facilities in sub-Saharan countries, including Ethiopia, leads to the presence of pathogenic bacteria in wastewater effluents.¹⁷ These pathogens contaminate both surface and groundwater, which in turn contributes to the increasing burden of ABR in the population. Our understanding of ABR in HWW still has critical gaps. Many studies have focused mainly on specific regions, resulting in disparities in our knowledge of ABR dynamics. The impact of HWW on the spread and occurrence of multidrug-resistant (MDR) bacteria, particularly ESBLs and CP isolates, is not well investigated in the study hospitals. Therefore, there is a pressing need for a comprehensive investigation into the persistence of MDR bacteria, including ESBLs and CP in HWW.

The findings from this study will provide significant insight into how HWW serves as a vital hub for the spread of ABR, which is crucial for addressing the environmental aspect of ABR, guiding infection control policymakers, and developing effective treatment strategies. Thus, the main aim of this study was to investigate bacteriological profiles and ABR patterns and to explore the magnitudes of ESBLs and CP isolates in HWW at Menelik II Comprehensive Specialized Hospital and Tirunesh Beijing General Hospital, Addis Ababa, Ethiopia.

Material and Methods

Study Setting

A cross-sectional study was conducted from September 2023 to March 2024 in Addis Ababa, Ethiopia, a city with a population of approximately 6 million people. Two hospitals were selected: Menelik Comprehensive Specialized Hospital (MIISH) and Tirunesh Beijing General Hospital (TBGH). These hospitals were chosen due to their geographical features, proximity to downstream rivers, the ability to give several medical services to the capital city and nearby rural populations, higher bed capacity, a lack of existing data, and large patient flows.

MIISH, one of the country’s oldest public hospitals, is situated in Yeka Kefle Ketema, north-east of Addis Ababa. It offers health services with a capacity of 135 surgical beds to a catchment population of approximately 1.6 million people. One of the primary departments is the department of surgery, which includes 3 wards, each with a separate ward for adults, 2 referral clinics, 1 operating room with 3 large operating tables, and an intensive care unit. The division performs emergency, general, gynecological, orthopedic, cardiothoracic, and urologic procedures.¹⁸

TBGH was established in 2012. It serves the residents of Akaki-Kality sub-city, surrounding sub-cities, and other local communities in the Oromia Regional State. Outpatients, inpatients, and emergency care are the hospital’s primary medical service.¹⁹ A 2017 study revealed that TBGH generated approximately 9.55 kg of biomedical waste daily, including 2.265 kg of infectious waste. In comparison, MIICSH produced 13.65 kg of biomedical waste each day, with 3.91 kg categorized as infectious waste.²⁰ Additionally, Wastewater generated by hospitals in Addis Ababa, including these 2, typically ranges from 400 to 1200 L/bed/day, according to regional studies.²¹ However, specific records for individual hospitals are limited. Current wastewater treatment systems do not effectively treat existing wastewater. There is a lack of reliable and documented data about HWW treatment technology in hospitals in Addis Ababa, Ethiopia. Some studies showed that their wastewater effluents are connected to the municipal sewer system and disposed of at the city’s wastewater treatment plant via trucks.¹⁷ Solid waste is excluded from this study, and only liquid wastewater from each ward and unit was included.

Sample Collection and Sampling Techniques

There were manholes at both hospitals that received wastewater from the patient ward or unit. The inclusion criteria include the manhole that receives wastewater from a patient ward or unit, exhibits functional and observable wastewater flow during the sampling period, and a ward or unit that was physically accessible and safe for sampling. Conversely, the exclusion criteria include inactive or temporarily closed wards, physically inaccessible wards, wards that recently subjected to high levels of chemical disinfection, and any spills or maintenance activities.

Samples were collected from 5 manholes, namely, the gynecology ward, the pediatric ward, the surgery ward, the laboratory unit, and the laundry unit. Additionally, a manhole was designated for mixed-source effluents. Information about the sampling locations was obtained from hospital environmental departments.

From these sampling locations, 104 discrete wastewater samples were taken. These included 60 and 44 effluents samples from MIISH and TBH respectively. “Grab sampling technique” was used to collect the samples following wastewater sampling recommendations published by the American Public Health Association (APHA) and the Environmental Protection Agency (EPA).²²

According to Nunez and Morton’s technique,²³ wastewater samples were collected from each ward or unit during their peak activity period, which is typically from 10:00 am to 2:30 pm.

At both hospitals, the manhole covers were carefully lifted to collect 50 mL wastewater samples in sterile Falcon tubes. Samples were collected twice daily, in the morning at 10:00 A.M and in the afternoon at 2:00 P.M from sampling wards or units, within a 4-hour interval. All samples were collected near the center of the following channel at a water depth of approximately 10 to 15 cm. Then, they were transported via a cold chain for bacteriological analysis within 4 hours of sample collection to the Health Biotechnology laboratory at the Institute of Biotechnology, Addis Ababa University. The samples were kept at 4°C in a refrigerator until they were processed.

Isolation and Identification of Bacterial Isolates

One mL of HWW effluent samples was suspended in 9 mL of buffered peptone water and vortexed to homogenize the samples and allow large debris settle. Then, 1 mL of the wastewater effluent was added to 9 mL of sterile buffered peptone water and mixed under aseptic conditions. Serial dilutions ranging from 10⁻¹ to 10⁻⁷ were prepared by adding 1 mL of a homogenized sample to a sterilized test tube with 9 mL of physiological saline solution and mixing properly.

From the 10⁻³, 10⁻⁴, and 10⁻⁵ dilutions, 0.1 mL of each aliquot was cultured on blood agar (blood agar base, HiMedia, India, with 5% sheep blood) using a glass spreader and incubated for 24 to 48 hours at 37°C. After proper incubation, each colony was selected based on its colony morphology and hemolytic properties, and then purified through successive subculturing using a sterile inoculating loop.²⁴ After getting pure culture on blood agar (BA), bacterial isolates were classified as Gram-positive bacteria (GPB) and Gram-negative bacteria (GNB) using 3% KOH and Gram staining. GPB were identified using biochemical tests, such as oxidation and fermentation (OF), oxidase, catalase, coagulase, bacitracin, optochin, and salt tolerance test, as described previously.^25,26 GNB were subcultured on MacConkey (MAC) agar and classified as lactose fermenters (LF) or non-fermenters (LNF) based on their lactose fermentation ability and oxidative and fermentative using the oxidation and fermentation (OF) test. Then, GNB isolates were identified at the species level using standard biochemical tests, such as Oxidase, Catalase, Urease, Indole, Methyl red, Voges–Proskauer, Citrate utilization, Mannitol, Malonate, and Lysine iron agar tests, and growing on 44°C.²⁵ The results from each biochemical test were then compared with Bergey’s Manual of Determinative Bacteriology.²⁷

Matrix-assisted laser desorption/ionization-time of flight Mass Spectrometry (MALDI-TOF MS)²⁸ has also been utilized for the identification of bacterial isolates that were difficult to identify using biochemical tests, and for those for which reagents are not readily available on the local market. All isolates were processed for antibiotic susceptibility testing (AST) directly after identification without a longer gap between isolation and the AST assay. The bacterial isolates were then preserved in a 30% glycerol solution with tryptone soy broth (TSB) and stored at −80°C for future experiments.

Phenotypic Antibiotic Susceptibility Testing

AST was performed via the Kirby–Bauer disk diffusion method in accordance with the Clinical and Laboratory Standards Institute (CLSI) guidelines, 34th edition.²⁹ This procedure was applied to both GPB and GNB. GPB were tested against gentamicin (10 μg), clindamycin (2 μg), vancomycin (30 μg), cefoxitin (30 μg), penicillin (10 μg), nitrofurantoin (30 μg), ciprofloxacin (5 μg), erythromycin (15 μg), oxacillin (10 μg), and sulfamethoxazole-trimethoprim (1.25/23.75 μg). The GNB isolates were also tested against ampicillin (10 μg), cefotetan (30 μg), cefuroxime (30 μg), cefotaxime (30 μg), ceftriaxone (30 μg), ceftazidime (30 μg), cefepime (30 μg), ciprofloxacin (5 μg), sulfamethoxazole trimethoprim (25 μg), gentamycin (10 μg), amikacin (10 μg), meropenem (10 μg), ertapenem (10 μg), piperacillin (100 μg), amoxicillin/clavulanic acid (20/10 μg), and piperacillin-tazobactam (100/10). These antibiotic disks were used because they were available on the local market and commonly prescribed in clinical settings. Moreover, the selection process was in accordance with the CLSI 34th edition guidelines to ensure standardized interpretation.

For AST, a suspension of 3 to 5 distinct colonies from each isolate was prepared in 5 ml of saline solution that matched 0.5 McFarland standards. The bacteria were then spread on Müller‒Hinton agar (MHA) via a sterile swab to achieve confluent growth. After the discs were placed on top of the media, the plates were incubated for 24 hours at 37°C. A graduated ruler was used to measure the diameters of the zones of inhibition, and the results were recorded in millimeters (mm). Finally, the bacterial isolates were categorized as susceptible, intermediate, or resistant according to the CLSI standards, 34th edition.²⁹ MDR bacterial isolates were classified as nonsusceptible (resistant or intermediate) to at least 1 agent in 3 or more antimicrobial categories.³⁰

Phenotypic Detection of ESBL-Producing Bacterial Isolates

Enterobacterales that were resistant to at least one-third-generation cephalosporin were screened for the production of ESBLs. Bacterial isolates suspected of producing ESBLs exhibited an inhibition zone of ⩽27 mm for cefotaxime (30 μg) and/or ⩽22 mm for ceftazidime (30 μg). These isolates were then selected for confirmatory testing using a combination disc-diffusion test (CDT) in accordance with the CLSI 34th edition guidelines.²⁹ CDT was conducted using ceftazidime (30 μg) and cefotaxime (30 μg), both individually and in combination with ceftazidime-clavulanic acid (CAZ/CLA) and cefotaxime-clavulanic acid (CTX/CLA), following the CLSI 2024 guidelines.²⁹ A zone of inhibition with a difference of ⩾5 mm between CAZ/CLA and CTX/CLA indicated that the organism was an ESBL producer, in accordance with the 34th edition of CLSI guidelines.

Phenotypic Detection of Carbapenemase-Producing Bacterial Isolates

Bacterial isolates that were nonsusceptible to either meropenem or ertapenem were screened for carbapenemase production using the modified carbapenem inactivation method (CIM) as described in the 34th edition of the CLSI guidelines.²⁹ Briefly, a loop of bacterial colony was suspended in 2 mL of tryptone soya broth (Hi Media, India) from an overnight culture grown on a tryptone soya agar plate. A 10 μg meropenem disk was then added and fully immersed in the broth. The tubes were incubated at 37°C for 4 hours without agitation. After incubation, the meropenem disks were removed with a 10 μL inoculation loop and placed on Mueller-Hinton agar (MHA; Oxoid, UK), which had been freshly inoculated with a 0.5 McFarland suspension of a carbapenem-susceptible strain (E. coli ATCC 25922). The results were interpreted after overnight incubation in accordance with CLSI guidelines.

Data Quality Assurance

Quality control procedures were implemented throughout the laboratory process to ensure the accuracy and reliability of the study results. Each new batch of culture media was assessed for sterility. To verify the performance of biochemical tests, reference strains such as the K. pneumoniae ATCC 700603, E. coli ATCC 25922, and S. aureus ATCC 25923 were utilized. The quality and effectiveness of the antibiotics were assessed using standard E. coli strains ATCC 25922 and ATCC 35218. AST was performed using E. coli ATCC 25922 (ESBL-negative) and K. pneumoniae ATCC 700603 (ESBL-positive) as control strains to confirm ESBL-producing isolates. In addition, the control strains K. pneumoniae ATCC BAA-1705 (positive) and E. coli ATCC 25922 (negative) were employed for confirmatory testing of CP bacterial species. The bacterial strains were obtained from the Ethiopian Public Health Institute (EPHI).

Data Analysis

The data were entered into Microsoft Excel and then exported to the Statistical Package for the Social Sciences (SPSS) Version 27 software (IBM Corporation, USA) for analysis. The frequency and percentages of bacterial isolates, along with their antimicrobial resistance profiles, were calculated.

Results

Bacteriological Profiles of HWW Samples

Among the total of 104 HWW collected, 95.2% were culture-positive. From these positive samples, 219 bacterial isolates were recovered. Among these 219 bacterial isolates, (24/219; 11%) were GPB, and (195/219; 89%) were GNB. For GPB, the dominant isolate was S. aureus (15/24; 62.5%), while the dominant isolate was K. pneumoniae (57/195; 29.2%) among GNB. Of the total 219 isolates, (175/219; 79.9%) were ESKAPEE pathogens.

A total of 12 different bacterial species were identified. Among these, the most frequently isolated bacterium was K. pneumoniae (57/219; 26.3%), followed by E. coli (47/219; 21.5%; Table 1).

Table 1.

Distribution of Bacterial Isolates From Hospital Wastewater in Addis Ababa, Ethiopia, in 2023/2024.

Bacterial isolates
Gram-negative bacteria (%)	N (%)	ESKAPEE pathogen
A. baumannii	7 (3.6)	7 (4.4)
Acinetobacter spp	6 (3.1)	-
E. coli	47 (24.1)	47 (29.4)
Enterobacter spp	21 (10.8)	21 (13.1)
K. pneumoniae	57 (29.2)	57 (35.6)
K. oxytoca	6 (3.1)	-
P. aeruginosa	28 (14.4)	28 (17.5)
P. vulgaris	9 (4.6)
P. mirabilis	5 (2.6)	-
Raoultella. spp	5 (2.6)	-
Salmonella spp	4 (2)	-
Total (N)	195 (100)	160 (82)
Gram-positive bacteria (%)
S. haemolyticus	3 (12.5)	-
E. faecalis	6 (25)	-
S. aurues	15 (62.5)	15 (100)
Total (N)	24 (100)	15 (62.5)

Distribution of Bacterial Isolates in Each Hospital Ward and Unit Wastewater

Of the 219 bacterial isolates recovered, the highest proportion was detected from surgery ward (44/219; 20.1%), followed by the gynecology ward and the laboratory unit, with a similar frequency of (38/219; 17.4%). The highest proportion of K. pneumoniae was isolated from mixed sources (12/37; 32.4%), and the dominant frequency of E. coli was isolated from the laboratory unit, (10/38; 26.3%), as depicted in Figure 1.

Figure 1.

Distribution of bacterial isolates in hospital wastewater from different wards/units in Addis Ababa city, 2023/2024.

Antibiogram Profiles of GPB Isolates

The highest resistance proportions in GPB were observed for penicillin and tetracycline each accounting for (13/24; 54.2%). In contrast, a lower proportion of resistance was observed for gentamicin (2/24; 8.3%). Among S. aureus isolates, 6 out of 24 (6/24; 40%) were classified as methicillin-resistant S. aureus (MRSA) using the cefoxitin disk as a surrogate marker. Additionally, half (3/6; 50%) of the Enterococcus faecalis displayed Vancomycin resistance (Table 2).

Table 2.

Antibiotic Resistance Profiles of Gram-Positive Bacterial (GPB) Isolates From Hospital Wastewater in Addis Ababa, Ethiopia, in 2023/2024.

Bacterial isolates (%)	Antibiotic agent (%)
Bacterial isolates (%)	PEN	OXA	AMP	ERY	TET	CIP	NIT	CLO	SXT	GEN	VAN	FOX
E. faecalis(6)	1 (16.7)	NT	2 (33.3)	3 (50)	4 (66.7)	1 (16.7)	3 (50)	NT	NT	NT	3 (50)	NT
S. aureus (15)	9 (60)	5 (33.3)	NT	6 (40)	8 (53.3)	4 (26.7)	3 (20)	4 (26.7)	2 (13.3)	1 (6.7)	NT	6 (40)
S. haemolyticus (3)	3 (100)	1 (33.3)	NT	0 (0)	1 (33.3)	0 (0)	1 (33.3)	0 (0)	3 (100)	1 (33.3)	NT	2 (66.7)
Total (24)	13 (54.2)	6 (25)	2 (8.3)	9 (37.5)	13 (54.2)	5 (20.8)	7 (29.2)	4 (16.7)	5 (20.8)	2 (8.3)	3 (12.5)	8 (33.3)

Abbreviations: AMP, ampicillin; CIP, ciprofloxacin; CLO, clindamycin; ERY, erythromycin; FOX, cefoxitin; GEN, gentamycin; NIT, nitrofurantoin; NT, not tested; OXA, oxacillin; PEN, penicillin; TET, tetracycline; VAN, vancomycin.

Antibiogram of GNB Isolates

The highest proportions of resistance in GNB were found for cefuroxime, (88/195; 45.1%) followed by tetracycline, (85/195; 43.5%). In contrast, the lowest resistance proportion was also obtained for meropenem (31/195; 15.9%), ertapenem (18/195; 9.2%), and amikacin (19/195; 9.7%).

Among the bacterial isolates tested, A. baumannii exhibited the highest proportions of resistance to tetracycline (7/7; 100%). The bacterium also showed a significant resistance level against ceftazidime (5/7; 71.4%). E. coli was another bacterial isolate that showed the highest levels of resistance to ampicillin (40/47; 85.1%). Moreover, no resistance (0%) was observed in Raoultella spp. and Salmonella spp. to cefepime, ertapenem, meropenem, and amikacin. Generally, out of 195 GNB tested, (186/195; 95.4%) were found to be non-susceptible to at least one of the tested antibiotic agent (Table 3).

Table 3.

Antibiotic Resistance Profiles of Gram-Negative Bacterial Isolates From Hospital Wastewater in Addis Ababa, Ethiopia, in 2023/2024.

Bacterial isolates (%)	Antibiotic agent (%)
Bacterial isolates (%)	AMP	AMC	FEP	CTX	CRO	CTT	CXM	CAZ	AT	MEM	ETP	GM	AN	CIP	SXT	TET
A. baumannii (7)	6 (85.7)	5 (71.4)	5 (71.4)	5 (71.4)	5 (71.4)	NT	NT	5 (71.4)	NT	5 (71.4)	NT	6 (85.7)	3 (42.8)	6 (85.7)	4 (57.1)	7 (100)
Acinetobacter spp (6)	5 (83.3)	5 (83.3)	5 (83.3)	6 (100)	6 (100)	NT	NT	6 (100)	NT	4 (66.7)	NT	5 (83.3)	3 (50)	5 (83.3)	6 (100)	6 (100)
Enterobacter spp (21)	NT	NT	1 (4.8)	3(14.3)	6 (28.6)	13 (61.9)	13 (61.9)	5 (23.8)	4 (19)	1 (4.8)	2 (9.5)	4 (19)	1 (4.8)	4 (19)	3 (14.3)	12 (57.1)
E. coli (47)	40 (85.1)	21 (44.7)	9 (19.1)	20 (42.6)	9 (19.1)	31 (66)	27 (57.4)	10 (21.3)	11 (23.4)	2 (4.3)	3 (6.4)	12 (25.5)	4 (8.5)	7 (14.9)	7 (14.9)	15 (31.9)
K. oxytoca (6)	5 (100)	1 (20)	0 (0)	0 (0)	1 (20)	2 (40)	2 (40)	0 (0)	0 (0)	0 (0)	1 (20)	0 (0)	0 (0)	0 (0)	1 (20)	1 (20)
K. pneumoniae (57)	NT	27 (47.4)	12 (21.1)	17(29.8)	16 (28.1)	25 (43.9)	32 (56.1)	19 (33.3)	13 (22.8)	11 (19.3)	9 (15.8)	14 (24.6)	7 (12.3)	15 (26.3)	24 (42.1)	32 (56.1)
P. aeruginosa (28)	9 (32.1)	7 (25)	2 (7.1)	NT	NT	NT	NT	5 (17.9)	10 (35.7)	5 (17.9)	NT	NT	1 (3.6)	7 (25)	NT	NT
P. vulgaris (9)	6 (66.7)	4 (44.4)	2 (22.2)	3 (33.3)	2 (22.2)	4 (44.4)	3 (33.3)	1 (11.1)	3 (33.3)	2(22.2)	2 (22.2)	2 (22.2)	0 (0)	1 (11.1)	4 (44.4)	5 (55.6)
P. mirabilis (5)	4 (80)	1 (20)	0 (0)	1 (20)	1 (20)	3 (60)	4 (80)	0 (0)	2 (40)	1 (20)	1 (20)	1 (20)	0 (0)	2 (40)	2 (40)	3 (60)
Raoultella Spp (5)	4 (80)	1 (20)	0 (0)	0 (0)	0 (0)	3 (60)	3 (60)	1 (20)	3 (60)	0 (0)	0 (0)	1 (20)	0 (0)	1 (20)	0 (0)	1 (20)
Salmonella Spp (4)	2 (40)	2 (40)	0 (0)	1 (20)	1 (20)	3 (60)	4 (80)	1 (20)	1 (20)	0 (0)	0 (0)	1 (20)	0 (0)	2 (40)	1 (20)	3 (60)
Total (195)	81 (41.5)	74 (37.9)	36 (18.5)	56 (28.7)	47 (24.1)	84 (43.1)	88 (45.1)	53 (27.2)	47 (24.1)	31 (15.9)	18 (9.2)	46 (23.6)	19 (9.7)	50 (25.6)	52 (26.7)	85 (43.5)

Abbreviations: AMP, ampicillin; AMC, amoxicillin/clavulanic acid; AN, amikacin; CAZ, ceftazidime; CIP, ciprofloxacin; CRO, ceftriaxone ; CTT, cefotetan; CTX, cefotaxime; CXM, cefuroxime; ETP, ertapenem; FEP, cefepime; GM, gentamycin; MEM, meropenem; NT, not tested; SXT, sulphamethoxazole – trimethoprim; TET, tetracycline.

Piperacillin and Piperacillin/tazobactam were tested for A. baumannii, Acinetobacter spp and P. aeruginosa instead of Ampicillin and Amoxicillin- Clavulanic acid, respectively.

MDR Profiles of Bacterial Isolates

As revealed by our study, the magnitude of MDR was (115/219; 52.5%). Of the total bacterial isolates, the highest magnitude of MDR was observed for K. pneumoniae (32/219; 14.6%), followed by E. coli (28/219; 12.8%), and Enterobacter spp. (13/219; 5.9%). Moreover, the proportion of MDR among GNB and GPB isolates was (105/195; 53.8%) and (10/24; 41.7%), respectively (Table 4).

Table 4.

Level of Antibiotic Resistance of Bacterial Isolates Recovered From Hospital Wastewater in Addis Ababa, Ethiopia, in 2023/2024.

Bacterial isolates (%)	Antibiotic resistance pattern of isolates (%)
Bacterial isolates (%)	R0	R1	R2	R3	R4	R5	R6	R7	R8	>R8	MDR
A. baumannii (7)	0 (0)	0 (0)	0 (0)	0 (0)	2 (28.6)	0 (0)	0 (0)	0 (0)	0 (0)	5 (71.4)	7 (100)
Acinetobacter spp (6)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	1 (16.7)	1 (16.7)	4 (66.7)	6 (100)
Enterobacter spp (21)	1 (5.9)	3 (14.3)	3 (14.3)	10 (47.6)	1 (5.9)	0 (0)	3 (14.3)	0 (0)	0 (0)	4 (23.5)	13 (11.3)
E. coli (47)	1 (2.1)	1 (2.1)	13 (27.7)	6 (12.8)	4 (8.5)	5 (10.6)	9 (19.1)	1 (2.1)	1 (2.1)	6 (12.8)	28 (59.6)
K. oxytoca (6)	0 (0)	0 (0)	2 (33.3)	3 (50)	1 (16.7)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	2 (33.3)
K. pneumoniae (57)	0 (0)	13 (26)	11 (19.3)	6 (10.5)	9 (15.8)	3 (5.3)	2 (3.5)	3 (5.3)	4 (7)	9 (15.8)	32 (56.1)
P. aeruginosa (28)	7 (25)	10 (35.7)	3 (10.7)	6 (3.8)	0 (0)	1 (0)	0 (0)	7 (0)	0 (0)	0 (0)	8 (28.6)
P. vulgaris (9)	0 (0)	1 (11.1)	5 (55.6)	0 (0)	0 (0)	0 (0)	1 (11.1)	0 (0)	1 (11.1)	1 (11.1)	3 (33.3)
P. mirabilis (5)	0 (0)	0 (0)	2 (40)	1 (20)	0 (0)	0 (0)	0 (0)	0 (0)	1 (20)	1 (20)	2 (40)
Raoultella Spp (5)	0 (0)	0 (0)	3 (60)	0 (0)	0 (0)	1 (20)	1 (20)	0 (0)	0 (0)	0 (0)	2 (40)
Salmonella Spp (4)	0 (0)	0 (0)	3 (74)	0 (0)	0 (0)	0 (0)	1 (25)	0 (0)	0 (0)	1 (25)	2 (50)
E. faecalis (6)	0 (0)	2 (33.3)	1 (16.7)	1 (16.7)	1 (16.7)	0 (0)	1 (16.7)	0 (0)	0 (0)	0 (0)	3 (50)
S. aureus (15)	0 (0)	5 (33.3)	3 (20)	2 (13.3)	2 (13.3)	0 (0)	0 (0)	1 (6.7)	1 (6.7)	0 (0)	4 (26.7)
S. haemolyticus (3)	0 (0)	0 (0)	0 (0)	2 (66.7)	1 (33.3)	0 (0)	0 (0)	0 (0)	0 (0)	0 (0)	3 (100)
Total (219)	9 (4.1)	35 (16)	49 (22.4)	37 (17)	21 (9.6)	10 (4.6)	18 (8.2)	13 (5.9)	9 (4.1)	31 (14.2)	115 (52.5)

Abbreviations: MDR, multidrug resistance; R0, susceptible to all drug tested; R1, resistance to 1 drug; R2, resistance to 2 drugs; R3, resistance to 3 drugs; R4, resistance to 4 drugs; R5, resistance to 5 drugs; R6, resistance to 6; R7, resistance to 7; R8, resistance to 8 and >R8, resistance to greater than 8 drug tested.

Magnitudes of ESBL and Carbapenemase-Producing (CP) Bacterial Isolates

Among GNB isolates, (77/195; 39.5%) were presumptive ESBL producers. Out of 77 ESBL potential bacteria, (37/77; 48%) were confirmed to be ESBL-producing isolates. The overall distribution of ESBL-producing bacteria was (37/195; 19%), with the highest proportion found in K. pneumoniae (20/195; 10.3%) and E. coli (14/195; 7.2%). The maximum proportion of ESBLs within-species was found among K. pneumoniae (20/37; 54%), followed by E. coli (14/37; 37.8%). All ESBL producers were 100% resistant to ceftazidime, cefotaxime, and ceftriaxone. However, 100% susceptible to meropenem, and cefoxitin.

Among the GNB isolates, (31/195; 15.9%) were assumed to be possible CP. Out of 31 CP, (6/31; 19.3%) were confirmed to be CP isolates. The overall distribution of CP bacteria was (6/195; 3.1%), with the highest proportion found in K. pneumoniae (3/195; 1.5%). The maximum proportion of CP isolates within species was found among K. pneumoniae (3/6; 50%). However, the least carbapenemase production was recorded in P. aeruginosa (1/6; 16.7%), as shown in Figure 2.

Figure 2.

Magnitudes of ESBLs and CP isolates from hospital wastewater in Addis Ababa city, 2023/2024.

Discussion

This study provides a comprehensive analysis of the bacteriological profiles and ABR patterns of bacteria from HWW effluent samples in Addis Ababa, Ethiopia. In contrast to earlier studies that focused on clinical samples, these findings reveal a significant presence of ABR bacteria, particularly ESBLs and CP, in waste effluents from different hospital wards and units. This underscores the role of hospital environments as a reservoir for the spread of ABR into downstream rivers, which are used for irrigation and even drinking water by the nearby communities. The presence of ESBLs and CP pathogens in the hospital environment reflects their spread to the downstream communities and poses a potential risk for human exposure. This issue is often linked with improper wastewater treatment and abuse of antimicrobials in hospital settings. While ESKAPEE pathogens are primarily reported in clinical isolates, their occurrence has not yet been extensively studied in hospital environments in Ethiopia. Therefore, this study provides comprehensive information on their distribution in this setting.

Frequency of Bacterial Isolates

Similar studies were reported in Ethiopia,^31,32 Cameroon,³³ and Pakistan³⁴ regarding the frequency of bacterial isolates from HWW. K. pneumoniae and E. coli were the most prevalent bacterial species in a study conducted in Addis Ababa, Ethiopia.¹⁰ Another finding from Bahirdar, Ethiopia, reported that S. aureus has the highest percentage, followed by E. coli.²⁴ A report in Bahirdar also found that E. coli was the most prevalent bacterium.³⁵ These discrepancies may be attributed to differences in study design, wastewater treatment strategies, infection prevention and control methods, as well as geographical and seasonal differences in bacterial distribution.

Of the total isolates recovered, 79.9% were identified as ESKAPEE pathogens. There are limited reports about ESKAPEE under this collective term from the hospital environment in Ethiopia. However, species-specific reports for K. pneumoniae (1 member of ESKAPEE pathogens) were found in 25.77% in Malaysian hospital effluents.³⁶ Our finding was higher than the pooled prevalence of 41.7%, reported in a meta–analysis conducted in Africa, which emphasized ESKAPE pathogens recovered in milk and meat samples.³⁷ It was also higher than a study from the USA, where they reported with 42.2% ESKAPEE pathogens from bloodstream infections.³⁸ However, lower percentage was found in southern Ethiopia, where 65.3% of this group of pathogens were identified in clinical samples.³⁹ These discrepancies may be due to differences in sample sources, study design protocols, and exposure to antimicrobials.

ABR Profiles of Bacterial Isolates

In this study, GNB isolates exhibited the highest resistance to cefuroxime (45.1%), and tetracycline (41%). Among GPB isolates, penicillin and tetracycline showed similar resistance proportion (54.2%). Comparable findings have been reported in Gondar, Ethiopia, where 97% of the isolates were resistant to ampicillin and 49% to cephalothin.⁷ Our results were also consistent with a study conducted in Jimma, Ethiopia, where they reported the highest magnitude of resistance were found for cefuroxime (100%), followed by ampicillin (61%). Similarly, a study in Taiwan revealed that the isolates from both clinical and sewage sources had the highest resistance profiles to ampicillin, cefazolin, and cefuroxime .⁸ This finding also agreed with a study conducted in Jimma, Ethiopia.⁴⁰ Amikacin (9.7%) showed the lowest resistance proportion. This might be because it was only used to treat rifampicin-resistant or MDR-TB and isn’t used for routine purposes .⁴¹

A study conducted in Northwest Ethiopia showed the highest resistance rates against ampicillin were found for E. coli, Klebsiella spp., Citrobacter spp., and Enterobacter spp (100%).⁷ Another report from Bahirdar, Ethiopia, showed the highest resistance profile in S. aureus, 69 (95.8%), against ampicillin and Citrobacter spps, 46 (86.8%) against tetracycline.³⁵ In the same city, the highest prevalence of resistance profiles was reported for K. pneumoniae (100%) and E. coli (52.4%) against ceftazidime. These findings are comparable with our findings.

According to our findings, Acinetobacter spp exhibited the highest resistance pattern to tetracycline, ceftriaxone, ceftazidime, and cefotaxime, each (100%). E. coli is another bacterial isolate that displayed the highest resistance pattern to ampicillin (85.1%). This disagrees with a study from Brazil, which reported low overall resistance rates in isolates of Acinetobacter spp. P. aeruginosa, K. pneumoniae, and E. coli, where the resistance levels of K. pneumoniae and E. coli for ampicillin were 70% and 40%, respectively.⁴² These findings are also inconsistent with the results previously reported in Ethiopia.³⁵ This difference may be attributed to factors such as sample size, study design, waste management strategies, antimicrobial usage at clinical settings, and the number of antimicrobial agents tested.

Of the bacterial species recovered, 52.5% showed MDR. This is higher compared with reports from Bahirdar, Ethiopia, where 22.2% of isolates were MDR.²⁴ However, it was lower than a report from Gondar, Ethiopia, where overall MDR rate was 69.9%.⁷ This variation may be due to differences in sample size, study design, waste management strategies, antimicrobial usage, and the number of antimicrobial agents tested.

Magnitude of ESBL-Producing Bacterial Isolates

Among the GNB isolates recovered from HWW, 19% were confirmed to be ESBL producers. The largest percentages were found in K. pneumoniae (10.3%) and E. coli (7.2%). A higher proportion of ESBL producers was observed compared to reports from Nepal,⁴³ Brazil,⁴⁴ Nigeria,⁴⁵ and Jimma, Ethiopia,⁴⁰ where they reported 57.72%, 39%, 29.1%, and 49.2% ESBL producers, respectively.

The highest proportion of ESBL bacteria was found for K. pneumoniae, 54% (within ESBL producers), followed by E. coli (37.8%). Nevertheless, the lowest proportion of ESBLs was found in P. mirabilis (2.7%). This is greater than a report in Addis Ababa, Ethiopia, with the highest distribution was found for E. coli (21.8%) and K. pneumoniae (4.8%).¹⁰ Tesfaye et al also showed that 33.3% of K. pneumoniae and 27.3% of E. coli were ESBL producers, which is lower than our results.⁴⁶ These discrepancies in the magnitude of ESBL-producing isolates may be attributed to variations in geographic regions, sampling site, sample size, ESBL screening and confirmation methods, and infection control systems.

Magnitude of CP Isolates

Regarding CP isolates, 3.1% were found to be carbapenemase producers. To the best of our knowledge, there are no findings on CP bacteria from HWW in Ethiopia. However, many studies detected CP outside Ethiopia. Our finding is lower than reports from the Philippines (41%), Germany (66.4%),^11,47 and China (15.4%) from hospital sewage and receiving rivers.³ These discrepancies may arise from variations in carbapenem prescriptions, sample sizes, waste effluent management strategies, and geographical regions.

Limitations of the Study

The limitations of this study include that the sampling sites were limited to 2 hospitals in Addis Ababa, Ethiopia, which may not accurately represent other hospitals in the country. The minimum inhibitory concentration (MIC) for a more precise assessment of bacterial susceptibility could not be determined. The 16S RNA analysis for better identification of isolates was not performed. The composite sampling method was not used to collect representative samples.

Future research with wider geographic coverage, larger sample sizes with a composite sampling technique, and Metagenomic studies is needed to gain a more complete understanding of the bacteriological profiles and antimicrobial resistance patterns in hospital settings.

Conclusion

This study shows that the hospital environment serves as a critical reservoir for MDR bacteria, including ESBL and carbapenemase producers, particularly E. coli, K. pneumoniae, and A. baumannii, which may cause the spread of resistant bacteria within communities and contaminate the receiving rivers. It emphasizes the need for collaborative efforts in managing wastewater and antibiotic use and calls for further research into the specific mechanisms and drivers of resistance development.

Additionally, a temporal analysis of ABR in the hospital environment is essential to address seasonal variations in antibiotic use in the hospital setting in response to infection incidences. Raising awareness about antibiotic use and reinforcement of hospital administration to use proper wastewater treatment strategies, particularly treatment technologies that can remove antibiotic residues, which act as a selective pressure that contributes to the development of resistance in HWW. Furthermore, conducting of AST on bacterial isolates and screening AMR genes from the hospital environment at the National Public Health Referral Laboratories is important for gaining a detailed understanding of the MDR bacterial species or genes circulating in Ethiopia.

Footnotes

Acknowledgements

The authors would like to acknowledge the support from the Vice President for the research and technology transfer office, Addis Ababa University, thematic research program led by Prof. Tesfaye Sisay Tessema.

ORCID iDs

Baye Maru Derso

Bayable Atnafu Kassa

Tesfaye Admassu Abate

Alemayehu Godana Birhanu

Misganu Yadesa Tesema

Tesfaye Sisay Tessema

Ethical Consideration

This study was approved by Addis Ababa University, Institute of Biotechnology Ethical Review Committee (IoB-IRB; Minute No IoB/L-7/2016/2024).

Author Contributions

Baye Maru Derso: Conception, investigation, execution, acquisition of data, writing original draft, analysis, and interpretation. Dr. Bayable Atnafu Kassa: Supervision, conception, investigation, writing, review, and editing. Dr. Tesfaye Admassu Abate: Supervision, conception, investigation, writing, review, and editing. Dr. Alemayehu Godana Birhanu: Supervision, investigation, writing, review, and editing. Misganu Yadesa Tesema: Conception, investigation, writing, review, and editing. Professor. Tesfaye Sisay Tessema: Main supervision, conception, investigation, resource, writing, review, and editing.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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