Occurrence and Antimicrobial Resistance Profiles of Bacteria from Dairy Farm Environments in Addis Ababa, Ethiopia

Occurrence and Antimicrobial Resistance Profiles of Bacteria from Dairy Farm Environments in Addis Ababa, Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Occurrence and Antimicrobial Resistance Profiles of Bacteria from Dairy Farm Environments in Addis Ababa, Ethiopia Baye Maru Derso, Bayable Atnafu Kassa, Tesfaye Admassu Abate, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7577060/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Feb, 2026 Read the published version in BMC Microbiology → Version 1 posted 19 You are reading this latest preprint version Abstract Background Wastes generated from dairy environments are critical hotspots where pathogenic and opportunistic pathogens interact with high concentrations of antibiotic residues and normal flora, potentially contributing to the occurrence of superbugs. Therefore, this study aimed to isolate bacteria from dairy environmental feces, manure, and waste effluent, determine their antimicrobial resistance patterns, and examine the distribution of extended-spectrum beta-lactamase and carbapenemase-producing bacterial isolates in Addis Ababa, Ethiopia. Methods A cross-sectional study was conducted in Addis Ababa, Ethiopia, from June 2023 to November 2024. A total of 88 samples, including feces, manure, and wastewater effluent, were collected from the dairy farm environment. The samples were transported and processed under sterile conditions. Following this, bacterial isolation, identification, and antimicrobial susceptibility testing were performed in accordance with standard microbiological protocols. Results Out of the total samples collected, 137 bacterial isolates were recovered from the dairy farm environment, with the highest proportion, 76(50.7%), found in fecal samples. Enterobacter spp. (28, 20.4%) and E. coli (20, 13.3%) were the most frequently isolated species among the bacterial isolates. E. coli showed the highest percentage of multidrug resistance, 12 (60%), among the tested isolates. Overall, 45.3% of the bacterial isolates were ESKAPE pathogens. Of these, 53 (85.5%) were gram-negative bacteria, while 9 (14.5%) were gram-positive bacteria. Gram-positive bacteria had the highest resistance rates against penicillin (12, 52.2%) and tetracycline (11, 47.8%), whereas Gram-negative bacteria showed the highest resistance against ampicillin (68, 73.9%). Multidrug resistance was present in 46% of the bacterial isolates. Conclusion Wastes generated from dairy farm environments contain multidrug-resistant bacterial isolates, which may contaminate nearby environments, crops, and water bodies and affect public health. Therefore, there must be proper antibiotic usage in dairy farm settings and adequate management of dairy manure and wastewater effluent before they are discharged into the environment. Antimicrobial resistance Infection control MDR Environment Figures Figure 1 Figure 2 Figure 3 Introduction Antimicrobial resistance (AMR) stands out as a critical challenge facing global public health in the 21st century (1). This threatens the efficient treatment capacity of drugs against infectious diseases by jeopardizing decades of medical achievements. A report from the OIE states that this burden will significantly increase future human mortality rates (2). The United States Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) have identified AMR as one of the top ten global public health threats. Antimicrobial-resistant bacterial infections were estimated to have caused 4.95 million deaths in 2019, and by 2050, resistant infections could account for 10 million deaths annually (3). Antibiotics are widely used in both human and veterinary medicine to treat infectious diseases. They are also essential for promoting growth and preventing illness. On dairy farms, antimicrobial agents are administered to manage common diseases such as lameness, mastitis, and respiratory diseases in cattle, as well as to optimize the nutritional component in the feed efficiently (4). However, irrational use of these antimicrobial agents leads to the emergence of multidrug-resistant (MDR) bacteria, which are excreted and released into the environment as harmful microbes (5). The dairy farm environment is a significant hotspot for the development and spread of antimicrobial-resistant bacteria (ARB) and genes, largely due to the routine use of antibiotics for both clinical and non-clinical purposes. These activities serve as selection pressures for AMR pathogens, thereby promoting the emergence and spread of such superbugs and/or resistance genes (6). According to studies, ARB from dairy farm environments frequently exhibit resistance to three or more antibiotic classes, such as β-lactams, sulfonamides, aminoglycosides, fluoroquinolones, and tetracyclines (7,8). ARB and their genes, have been found in various environmental matrices, including municipal sewage (9,10), medical wastewater (11), beef waste and wastewater, dairy farm waste and wastewater (12,13), and soil samples from an unspoiled environment (14). Studies have shown that dairy manure, feces, and wastewater often contain a variety of resistance genes, such as extended-spectrum beta-lactamases (ESBLs) (15,16), AmpC (17,18), and carbapenemase-producing Enterobacterales (CPEs) (19). The findings of another study also showed that the dairy farm environment is a highly selective environment that increases the prevalence of resistant bacteria released into the environment, including E. coli , Klebsiella spp., Pseudomonas spp., Enterococcus spp., and Aeromonas spp. (20,21). Owing to its high nutrient content, dairy manure is frequently used in agriculture as an organic fertilizer. However, manure samples contain ARB and ARB genes, as the use of antibiotic agents in dairy cows is irrational, and when these agents are applied to crops, they pose a significant human health risk, as they contain ARB and antibiotic residues (AR) and are transported to plant tissues, where they cause food-borne diseases (22). In April 2014, the World Health Organization (WHO) published its inaugural global report on antimicrobial resistance, highlighting the levels of resistance both within community settings and among bacteria responsible for nosocomial infections (23). Additionally, the WHO released a prioritized list of bacteria urgently requiring new research and therapeutic development in 2017, which was subsequently updated in 2024 to reflect evolving resistance patterns (24). Bacteria classified as having critical priority include carbapenem-resistant A. baumannii , P. aeruginosa , and ESBL-producing Enterobacterales. The priority pathogens on the list include E. faecium , S. aureus , Campylobacter spp., and Enterobacter spp. Consequently, WHO data underscore that AMR at the human, animal, and environmental interface represents a significant global reservoir for the emergence and dissemination of pathogenic microorganisms. Various studies that have been conducted in Ethiopia involving samples from dairy cows, slaughterhouses, dairy products, and dairy farm workers (25,26). However, research on the occurrence and AMR profiles of bacterial species, including ESBLs and CPEs in the dairy farm environments remains limited. Drug resistance is a growing concern that worsens each day. Consequently, there is an urgent need for through investigation into the persistence of ARB in dairy farm environmental samples (16). Understanding AMR profiles in dairy farm environments is essential for addressing the environmental aspect of AMR and controlling transmission pathways from farms to humans, which can occur through edible crops and direct contact. Research has shown that as ESBL- E. coli strains isolated from dairy cows share genetic similarities with human isolates (27). This information is vital for guiding antibiotic stewardship and shaping manure and waste management policies (18). The findings of this study will provide valuable insights into the dairy farm environment as a potential hotspot for the development and spread of ARB and contribute to evidence-based antibiotic stewardship and proper manure and waste disposal strategies to mitigate the rise of AMR. This study aimed to investigate the occurrence of bacterial species, including ESKAPE pathogens, and their antimicrobial-resistant profiles. Additionally, it aimed to generate information on the occurrence of ESBL- and carbapenemase-producing bacterial species in environmental samples from dairy farms in Addis Ababa, Ethiopia. Materials and methods Study Setting This study was conducted in Addis Ababa, Ethiopia, a city with approximately 6 million residents, situated at about 9°1′48″ N latitude and 38°44′24″ E longitude. The city experiences a subtropical highland climate characterized by moderate temperatures and distinct wet and dry seasons, at an average elevation of 2355 m above sea level (Alene et al., 2025). As Ethiopia's political, economic, and cultural center, Addis Ababa’s diverse and growing population is driving an increasing demand for livestock products such as meat and milk. The study was carried out across six of the city’s 11 sub-cities: Akaki Kality, Bole, Yeka, Arada, Nefassilk, and Kolfe Keranyo, as depicted in Fig. 1 . (All figures are located at the end of this main text file.). Figure 1 Map of the study area (Addis Ababa, Ethiopia) Sample collection and preparation A cross-sectional study was conducted between June 2023 and November 2024. A total of 88 samples were collected from dairy farm environments, consisting of 44 fresh fecal samples, 22 manure samples applied as crop fertilizer, and 22 waste effluent samples that were directly discharged into nearby water bodies. Sampling took place across six sub-cities in Addis Ababa: Akaki Kality, Bole, Nifas Silk-Lafto, Kolfe Keranyo, Yeka, and Arada. All samples were collected using a sterile stool cup and transported in a cold chain to the Health Biotechnology Laboratory at Addis Ababa University for microbiological analysis within four hours of collection. The samples were kept at 4°C in a refrigerator until they were processed. Isolation and identification of bacterial isolates from dairy farms One gram of fresh feces and manure and one mL of wastewater effluent samples were suspended in 9 mL of buffered peptone water separately and vortexed to homogenize the samples and settle the large debris. Then, one mL of the supernatant from feces, manure, or wastewater effluent was added to 9 mL of sterile buffered peptone water separately for each sample type and shaken in an aseptic setting. 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) via a sterile inoculation loop and incubated for 24–48 hours at 37°C. After proper incubation, representative colonies were selected based on their colony morphology and hemolytic properties, and then purified through successive subculturing (29). Then, plates with 25–250 colonies were selected for subsequent procedures (30). A subculture was prepared from each unique colony on blood agar. The colonies were characterized on the basis of their hemolysis, surface, color, texture, and other parameters. The most important pathogenic bacteria were identified on the basis of their colony morphology, growth on their respective selective media, and other bacteriological tests (31). After pure culture on blood agar (BA) was obtained, bacterial isolates were classified as Gram-positive and Gram-negative using 3% KOH and Gram staining procedures. Gram-positive bacteria (GPB) were subcultured on the same blood agar plate (BAP) and further identified via biochemical tests, such as oxidation and fermentation (OF), oxidase, catalase, coagulase, bacitracin, and additional tests, such as the optochin test and salt tolerance test, as described previously (32). Catalase-positive (catalase producers) cocci GPB were subcultured onto Mannitol salt agar, followed by the coagulase test to differentiate between coagulase-positive and coagulase-negative Staphylococcus species. Catalase-negative(catalase non-producers) cocci GPB were grown on the same blood agar and identified using hemolytic patterns(i.e., alpha, beta and gamma hemolysis) on blood agar followed by optochin, bacitracin, and salt-tolerant tests for the identification of Streptococci and Enterococci spp. (33,34). Gram-negative bacteria (GNB) were subcultured on MacConkey (MAC) agar and classified as lactose fermenters (LF) or non-fermenters (LNF) based on their lactose fermentation ability. The oxidative and fermentative properties of the isolates were assessed using oxidation and fermentation (OF) test. Following this, oxidase and catalase tests were performed to identify the genera and species of the isolates (33). GNB isolates that did not grow on MAC agar were identified using the Gram-staining technique and additional biochemical tests. After categorizing the GNB isolates as oxidative or fermentative via OF test and as LF or NLF using MAC, further identifications were conducted through standard biochemical tests, including the Urease test, Indole test, methyl red, Voges–Proskauer test, Citrate utilization test, Mannitol test, Malonate test, and growth on lysine iron agar along with other specific tests for the bacteria (32). After identifying the isolates using biochemical tests, they were subcultured onto their respective selective media to confirm their unique characteristics. The fermentative bacteria (Enterobacterales) were subcultured onto Eosin Methylene Blue Agar (EMB) to observe the dark blue-black colonies with a green metallic sheen characteristic of E. coli and brown, dark-centered and mucoid colonies for K.pneumonia. Among these, Salmonella spp. were further subcultured onto Salmonella-Shigella (SS) Agar to observe colonies of colorless colonies with black centers, and P. aeruginosa from the oxidative group was subcultured onto Pseudomonas selective agar to observe blue to greenish colonies. The results from each biochemical test were then compared with Bergey’s Manual of Determinative Bacteriology (35). Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) (36) has been utilized to identify bacteria that are difficult to classify using biochemical tests and for those for which reagents are not readily available on the local market. These bacterial isolates include Bacillus, Acinetobacter, Aeromonas, Neisseria, and Enterobacter species. All isolates were processed for 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 Antibiotic susceptibility testing (AST) was performed via the Kirby–Bauer disk diffusion method on the basis of the Clinical and Laboratory Standards Institute (CLSI) guidelines, 34th edition (37). This procedure was applied to both GPB and GNB, except for Bacillus cereus, Neisseria flavescens , Aeromonas spp., and Burkholderia species, as these guidelines do not provide clear interpretive criteria for their inhibition zone diameters via disk diffusion methods. 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). Vancomycin was only tested for Enterococcus spp., and oxacillin was only tested for Staphylococcus spp., as there are no interpretive criteria for their inhibition zone diameters. 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). Piperacillin and piperacillin‒tazobactam were tested only for Acinetobacter spp. and P. aeruginosa in this study according to the CLSI guidelines. These antibiotic disks were used because they were available on the local market and commonly prescribed in clinical settings. For AST, bacterial colonies were used to prepare suspensions that matched 0.5 McFarland standards (1.5 × 10 − 8 CFU/mL) with physiological saline. 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 (37). Species-specific interpretive criteria were applied for both GPB and GNB, as were group-level criteria for gram-negative Enterobacterales, according to these guidelines. Multidrug-resistant (MDR) bacterial isolates were classified as nonsusceptible (resistant or intermediate) to at least one agent in three or more antimicrobial categories (38). Phenotypic detection of ESBL-producing bacterial isolates Enterobacterales groups that were resistant to at least one of the third-generation cephalosporins were screened for the formation of ESBLs. The bacterial isolates suspected of producing ESBLs presented an inhibition zone of ≤ 27 mm for cefotaxime (30 µg) and/or ≤ 22 mm for ceftazidime (30 µg) and were selected for confirmatory testing according to the CLSI 34th edition (37). Phenotypic confirmatory test for ESBL producers The combination disc-diffusion test (CDT) was used to confirm the suspicious ESBL-producing bacteria. It was performed with ceftazidime (30 µg) and cefotaxime (30 µg) alone and in combination with ceftazidime-clavulanic acid (CAZ/CLA) and cefotaxime-clavulanic acid (CTX/CLA) as per CLSI 2024 (37). The zone of inhibition ≥ 5 mm for the difference between CAZ/CLA and CTX/CLA was confirmed as an ESBL producer rather than CAZ or CTX alone, as per 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 production of carbapenemase by using the modified carbapenem inactivation method (CIM) per the CLSI guideline 34th edition (37). Briefly, a loop of bacterial colony was suspended in 2 mL of tryptone soya broth (Hi Media, India) from an overnight culture on a tryptone soya agar plate, and a meropenem disk (10 µg) was added and fully immersed in the tryptone soya broth. The tubes were subsequently incubated at 37°C for 4 hrs without agitation. The meropenem disks were then removed via a 10 µL inoculation loop and applied to MHA (Oxoid, UK) freshly inoculated with a 0.5 McFarland suspension of a carbapenem-susceptible strain ( E. coli ATCC 25922). The results were interpreted as per the CLSI guideline 34th edition after overnight incubation. Data Quality Assurance Quality control procedures were implemented throughout the laboratory process to ensure the accuracy of the study results. For each new batch of biochemical tests, the K. pneumoniae ATCC 700603 and E. coli ATCC 25922 strains were utilized for bacterial identification. The quality and effectiveness of antibiotics were assessed using standard strains of E. coli ATCC 25922 and ATCC 35218. AST was conducted with E. coli ATCC 25922 (ESBL-negative) and K. pneumoniae ATCC 700603 (ESBL-positive) control strains for confirmatory testing of ESBLs 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 CPE bacterial species. The bacterial strains were obtained from the Ethiopian Institute of Public Health (EPHI). Data analysis The data obtained from this study were coded via Microsoft Excel and Pivotal tables were utilized to calculate the frequency and percentages of bacterial isolates in each sampling sites, sample types, season and sampling months. The Statistical Package for Social Sciences (SPSS) Version 27 software (IBM Corporation, Armonk, USA) were used to calculate the frequency and percentages of antimicrobial resistance profiles of the bacterial isolates. Results Among the total 88 samples collected from the dairy farm environment, 85.2% tested positive for one or more bacterial species. From these positive samples, 137 bacterial isolates were recovered. Among the 137 positive bacterial isolates, 30 (21.9%) were GPB, and 107 (78.1%) were GNB. Among the total bacterial isolates recovered, 62 (45.3%) were ESKAPE pathogens. Among these pathogens, 53 (85.5%) were GNB, whereas 9 (14.5%) were GPB. Among these strains, Enterobacter spp. 28 (52.8%) and S. aureus 9 (100%) were the dominant GNB and GPB, respectively, among the ESKAPE groups. For GPB, the dominant isolate was S. aureus 9 (30%), followed by CoNS and Bacillus cereus 7 (23.3%), with similar frequencies. The least prevalent GPB was S. agalactiae 2 (6.7%). Among GNB, the dominant isolate was Enterobacter spp. 28 (26.2%), followed by E. coli 20 (18.7%), while the least frequently isolated was N. flavescens 2 (1.9%) (Table 1). A total of seventeen (17) different bacterial species were identified from the total positive samples. Among these, the most frequently isolated bacterium was Enterobacter spp. 28 (20.4%), followed by E. coli 20 (14.6%), K. pneumoniae 13 (9.5%), and P. aeruginosa 12 (8.8%) (Table 1). Table 1 Bacterial isolates recovered from dairy farm environmental samples at Addis Ababa, Ethiopia, from June 2023 to November 2024 Gram-Negative isolates (GNB) N (%) ESKAPE pathogen Acinetobacter spp 7(6.5) - Aeromonas spp 10(9.3) - Burkholderia spp 3(2.8) - E.coli 20(18.7) - Enterobacter spp 28(26.2) 28(52.8) K. pneumonia 13(12.1) 13(24.5) M. morgannii 4(3.7) - N. flavescens 2(1.9) - P. aeruginosa 12(11.2) 12(22.6) Salmonella spp 8(7.5) - Gram-Positive Bacteria (GBP) N (%) ESKAPE pathogen B. cereus 7(23.3) - CoNS 7(23.3) - E. fecalis 5(16.7) - S. aureus 9(30) 9(100) S. agalactiae 2(6.7) - CoNS, coagulase-negative Staphylococcus spp. Among these 137 positive bacterial isolates, the highest proportion of bacterial isolates was obtained from Akaki Kality subcity, 43 (31.4%), followed by Nefassilk Lafto subcity dairy farm environments, 24 (17.5%); the lowest proportion of the isolates was found from Bole and Arada subcity dairy farms, 16 (11.7%). (Table 2). Table 2 Distribution of bacterial species from dairy farm environments at Addis Ababa, Ethiopia, from June 2023 to November 2024 Sampling sites (%) Bacterial Isolates (%) AKD ARD BSD KKD NLD YSD Acinetobacter spp(7) 3(7) 0(0) 0(0) 3(17.6) 1(4.2) 0(0) Aeromonas spp(10) 4(9.3) 4(25) 0(0) 0(0) 0(0) 2(9.5) Bacillus cereus (7) 3(7) 0()) 1(6.25) 0(0) 1(4.2) 2(9.5) Burkholderia spp(3) 0(0) 1(6.25) 0(0) 2(11.8) 0(0) 0(0) E.coli (20) 8(18.6) 1(6.25) 3(18.75) 1(5.9) 4(16.7) 3(14.3) Enterobacter spp(28) 8 (28.6) 6(21.4) 4(14.3) 3(10.7) 2(7.1) 5(17.7) E. fecalis (5) 1(2.3) 1(6.25) 0(0) 0(0) 2(8.3) 1(4.8) K. pneumoniae (13) 3(7) 1(6.25) 4(25) 2(11.8) 2(8.3) 1(4.8) M. morgannii (4) 0(0) 0(0) 1(6.25) 1(5.9) 1(4.2) 1(4.8) N.flavescens (2) 2(4.6) 0(0) 0(0) 0(0) 0(0) 0(0) P. aeruginosa (12) 3(7) 1(6.25) 0(0) 2(11.8) 5(20.8) 1(0) Salmonella spp(8) 2(4.6) 1(6.25) 1(6.25) 0(0) 1(4.2) 3(14.3) S. aureus (12) 4(9.3) 0(0) 1(6.25) 1(5.9) 1(4.2) 2(9.5) CoNS (7) 2(28.6 0(0) 1(14.3) 0(0) 4(57.1) 0(0) Strep. agalactiae 0(0) 0(0) 0(0) 2(11.8) 0(0) 0(0) Total (137) 43(31.4) 16(11.7) 16(11.7) 17(12.4) 24(17.5) 21(15.3) Abbreviations: AKD, Akaki Kality Subcity dairy farms; ARD, Arada Subcity dairy farms; BSD, Bole Subcity dairy farms; KKD, Kolfe Keranyo Subcity dairy farms; NLD, Nefassilk Subcity dairy farms; and YSD, Yeka Subcity dairy farms: CoNS, Coagulase Negative Staphylococcus Among the total samples collected, 70 (51.1%) bacterial isolates were isolated from dairy feces, 37 (27%) from manure, and 30 (21.9%) from the total bacterial isolates recovered, as shown in Figure 2. Figure 2 Positive bacterial isolates in each dairy farm environment sample (feces, manure, and wastewater effluent). Enterobacter spp. (24.3%, 17/70) were the most abundant bacteria in the fecal samples, followed by E. coli (15.7%, 11/70). P. aeruginosa and Enterobacter spp. (13.5%, 5/37) were the most frequently isolated bacteria from manure, while E. coli (23.3%, 7/30) was most common in wastewater effluents, as shown in Figure 3. Figure 3 Distribution of each bacterial species in dairy farm environment samples (feces, manure, and wastewater effluent). Antibiogram Profiles of GPB Isolates The highest percentage/frequency of antimicrobial resistance in GPB was observed for penicillin (12 (52.2%)), followed by tetracycline (11 (47.8%)). The lowest resistance rate was found for gentamicin, clindamycin, and cefoxitin (4 [17.4%]). Two (22.2%) of the S. aureus isolates were identified as methicillin-resistant (MRSA) via the use of a cefoxitin disk as a surrogate marker; 4 (80%) of the Enterococcus spp. were resistant to vancomycin. (Table 3). Table 3 Antimicrobial resistance profiles of gram-positive bacterial isolates recovered from dairy farm environment samples at Addis Ababa, Ethiopia, from June 2023 to April 2024 Antibiotics tested (%) Bacterial isolates (%) Pen AMP/OXY ERY TET CIP NIT CLO SXT GEN VAN FOX E. fecalis (5) 2(40) 2(40) 2(40) 2(40) 1(20) 2(40) NT NT NT 4(80) NT CoNS (7) 4(57.1) 1(14.3) 3(42.3) 3(42.3) 1(14.3) 2(28.6) 2(28.6) 2(28.6) 1(14.3) NT 1(14.3) Strep. agalactiae (2) 1(50) 1(50) 1(50) 1(50) 0(0) 0(0) 0(0) 0(0) 1(50) NT 1(50) S. aureus (9) 5(55.6) 3(33.3) 3(33.3) 5(55.6) 3(33.3) 4(44.4) 2(22.2) 6(66.7)) 3(33.3) NT 2(22.2) Total(23) 12(52.2) 7(30.4) 9(39.1) 11(47.8) 5(21.7) 8(34.8) 4(17.4) 8(34.8) 4(17.4) 4(17.4%) 4(17.4) Pen, penicillin; AMP, ampicillin; Oxy, oxacillin; ERY, erythromycin; TET, tetracycline; CIP, ciprofloxacin; NIT, nitrofurantoin; CLO, clindamycin; SXT, sulfamethoxazole-trimethoprim; GEN, gentamycin; VAN, vancomycin; FOX, cefoxitin; NT, not tested Antibiogram of GNB Isolates The antibiotic resistance rates for GNB isolates were highest for ampicillin (68, 73.9%), followed by tetracycline (58, 63%) and sulfamethoxazole-trimethoprim (46, 49.5%). Significant resistance to cefuroxime, 43 (46.7%), cefotetan, 28 (30.4%), and ceftazidime, 27 (29.3%), was also detected. The lowest resistance rates were observed for meropenem (7.6%), amikacin (3.3%), and ertapenem (2.2%). Among the bacterial isolates tested, Enterobacter spp. (100%) presented the highest resistance to ampicillin (100%). Acinetobacter spp. was another bacterial isolate that presented the highest level of resistance to piperacillin, at 6 (85.7%). Moreover, a lack of resistance (0%) against cefotaxime, ceftriaxone, ceftazidime, aztreonam, ertapenem, meropenem, amikacin and ciprofloxacin was detected in Enterobacter spp., and no resistance against amoxicillin/clavulanic acid, cefepime, ceftriaxone, ceftazidime, aztreonam, meropenem, ertapenem, amikacin, gentamycin, ciprofloxacin and sulfamethoxazole/trimethoprim was detected in M. morgannii (Table 4). (Table 4 is located at the end of this main text file.) Table 4 Antimicrobial resistance profiles of gram-negative isolates recovered from dairy farm environments at Addis Ababa, Ethiopia, from June 2023 to April 2024 Bacterial isolates (%) AM/PIP AMC/PTZ FEP CTX CRO CXM CTT CAZ AT ETP MEM GM AN CIP SXT TET Acinetobacter spp(8) 6(85.7) 3(42.9) 0(0) NT NT NT NT 1(14.3) NT NT 1(14.3) 2(28.6) 1(14.3) 3(42.9) 5(71.5) 4(57.1) Enterobacter spp(28) 28(100) 6(21.4) 2(7.1) 1(3.6) 0(0) 14(50) 10(35.7) 1(3.6) 1(3.6) 1(3.6) 1(3.6) 4(14.3) 1(4.3) 4(14.3) 9(32.1) 15(53.6) E.coli (20) 17(85) 8(40) 2(10) 8(40) 6(30) 12(60) 10(50) 4(20) 3(15) 1(5) 1(5) 2(10) 0(0) 5(25) 13(65) 13(65) K.pneumonia (13) NT 3(23.1) 1(7.7) 5(38.5) 1(7.7) 9(69.2) 6(46.2) 1(7.7) 1(7.7) 0(0) 0(0) 2(15.4) 1(7.7) 3(23.1) 6(46.2) 10(76.9) M.morganii (4) 3(75) 0(0) 0(0) 0(0) 0(0) 2(50) 2(50) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 0(0) 3(75) P.aeruginosa (12) 8(66.7) 4(33.3) 3(25) NT NT NT NT 2(16.7) 6(50) NT 4(33.3) 6(50) 0(0) 0(0) 8(66.6) 9(75) Salmonella spp(8) 6(75) NT NT NT 5(62) NT NT NT NT 1(12.5) 1(12.5) NT NT 3(37) 5(62.5) 4(50) Total(92) 68(73.9) 24(26) 8(8.7) 14(15.2) 12(13) 37(40.2) 28(30.4) 9(9.8) 11(12) 2(2.2) 7(7.6) 16(17.4) 3(3.3) 18(19.6) 46(50) 58(63) Abbreviations: AM: ampicillin, PIP: piperacillin. PTZ: Piperacillin-tazobactam AMC: Amoxicillin/clavulanic acid, FEP: Cefepime, CTX: Cefotaxime, CRO: Ceftriaxone, CTT: Cefotetan, CXM: Cefuroxime, CAZ: Ceftazidime, AT: Aztreonam, ETP: Ertapenem, MEM: Meropenem, GM: Gentamycin, AN: Amikacin, CIP: Ciprofloxacin, SXT: Sulphamethoxazole–Trimethoprim, TET: Tetracycline, NT: Not tested N.B. Piperacillin was tested for Acinetobacter spp. and P. aeruginosa only instead of ampicillin in this study. MDR Profiles of Bacterial Isolates The bacterial species with the highest percentages of antibiotic resistance were Enterobacter spp. (100%) for ampicillin and Acinetobacter spp. (85.7%) for piperacillin. Multidrug resistance (MDR) was detected in 53 (46%) bacterial isolates. Among the bacterial isolates processed for the AST, E. coli had the highest percentage of MDR bacteria (12, 60%), followed by P. aeruginosa (7, 58.3%) and K. pneumoniae (7, 53.8%) (Table 5). Table 5 Antimicrobial resistance patterns of bacterial isolates recovered from dairy farm environments in Addis Ababa, Ethiopia, from June 2023 to April 2024 Antimicrobial resistance pattern of isolates (%) Bacterial isolates (%) R0 R1 R2 R3 R4 R5 R6 R7 R8 >R8 MDR Acinetobacter spp(8) 0(0) 1(12.5) 2(25) 1(12.5) 1(12.5) 1(12.5) 0(0) 0(0) 1(12.5) 0(0) 4(50) Enterobacter spp(28) 0(0) 2(7.1) 11(39.3) 4(14.3) 4(14.3) 4(14.3) 0(0) 0(0) 0(0) 0(0) 9(32.1) E.coli (20) 0(0) 1(5) 5(25) 1(5) 3(15) 4(20) 1(5) 1(5) 1(5) 3(15) 12(60) K.pneumoniae (13) 0(0) 0(0) 2(15.4) 0(0) 0(0) 6(46.1) 0(0) 1(7.7) 1(7.7) 3(23) 7(53.8) M.morganii (4) 0(0) 1(25) 1(25) 1(25) 1(25) 0(0) 0(0) 0(0) 0(0) 0(0) 2(50) P.aeruginosa (12) 0(0) 0(0) 3(25) 2(16.7) 1(8.3) 4(33.3) 0(0) 2(16.7) 0(0) 0(0) 7(58.3) Salmonella spp(8) 0(0) 0(0) 5(62.5) 0(0) 1(12.5) 1(12.5) 1(12.5) 0(0) 0(0) 0(0) 3(37.5) E.fecalis (5) 0(0) 0(0) 2(40) 2(40) 1(50) 0(0) 0(0) 0(0) 0(0) 0(0) 2(40) CoNS(7) 0(0) 1(0) 4(50) 0(0) 0(0) 1(25) 0(0) 1(25) 0(0) 0(0) 2(50) Strep. agalactiae (2) 0(0) 1(50) 0(0) 0(0) 0(0) 1(50) 0(0) 0(0) 0(0) 0(0) 1(50) S.aurues (9) 1(11.1) 1(11.1) 1(11.1) 2(22.2) 1(22.2) 0(0) 2(22.2) 0(0) 0(0) 1(11.1) 4(44.4) Total(115) 1(1) 9(7.8) 36(31.3) 16(13.9) 14(12.1) 18(15.6) 5(4.3) 3(2.6) 2(1.7) 5(4.3) 53(46) Abbreviations: R0, susceptible to all drugs tested; R1, resistant to 1 drug; R2, resistant to 2 drugs; R3, resistant to 3 drugs; R4, resistant to 4 drugs; R5, resistant to 5 drugs; R6, resistant to 6 drugs; R7, resistant to 7 drugs; R8, resistant to 8 drugs and >R8, resistant to more than 8 drugs tested; MDR, multidrug resistant Magnitudes of ESBL and carbapenemase-producing (CPE) bacterial isolates Among the GNB isolates (N=92) selected for the AST, 23 (25%) were presumptive ESBL producers. Among these 23 potential ESBL-producing Enterobacterales, 18 (78.3%) were confirmed as ESBL producers. The overall distribution of ESBL-producing bacteria was 19.6% (18/92), with the highest proportion found in E. coli (12%; 11/92) and the lowest in K. pneumoniae (7.6%; 7/92). Among the ESBL-producing isolates, E. coli accounted for 61.1% (11/18), and K. pneumoniae accounted for 38.9% (7/18). The highest number of ESBL-producing isolates was found in dairy feces, with 12 (52.2%), followed by dairy wastewater effluent, with 5 (21.7%). The lowest percentage was in manure, with 1 (4.3%) isolate. No CPE was detected in any samples from the dairy farm environment (Table 6). Table 6 Distribution of ESBL- and CPE-producing isolates from dairy farm environments at selected dairy farms in Addis Ababa, Ethiopia, from June 2023 to June 2024 Sample type (%) Feces Wastewater Manure Bacterial isolates (%) ESBL positive ESBL negative ESBL positive ESBL negative ESBL positive ESBL negative CPE E. coli (11) 7(58.3) 1(8.3) 4(33.3) 0(0) 0(0) 0(0) 0(0) K .pneumoniae (7) 5(45.4) 2(18.2) 1(9) 1(9) 1(9) 1(9) 0(0) Total(18) 12(52.2%) 3(13) 5(21.7) 1(4.3) 1(4.3) 1(4.3) 0(0) ESBL, extended-spectrum beta-lactamases; CPE, carbapenemase-producing Enterobacterales Discussion Waste generated from dairy farm environments contains antibiotic residues, antibiotic-resistant bacteria, and their genes (39). These are the main drivers of the development and spread of AMR in the environment and public health. AMR is a great challenge for public health worldwide because of alarming resistance and the absence of new antimicrobial discoveries to treat infectious diseases (11). The main factors associated with AMR in dairy farm environments are a lack of awareness of AMR in antibiotic users, the prescription of antibiotics without veterinary guidelines, and the overuse of antibiotics for infection treatment, prophylaxis, and growth promotion. In our findings, a total of 137 bacterial isolates were recovered from dairy farm environmental samples, such as fresh feces, manure, and wastewater effluents. Among the bacterial isolates recovered, Enterobacter spp. (28, 20.4%) constituted the highest percentage, followed by E. coli (20, 14.6%). There are few studies on the occurrence of bacterial species and their AMR profiles in dairy farm environments in Ethiopia. However, there are some reports about the distribution and AMR profiles of bacteria from Bahirdar, Ethiopia, in hotspot environments, including dairy farms. Salmonella spp. (37.8%), followed by Citrobacter spp. (9.3%), are the most prevalent bacteria in dairy waste and wastewater (11). This disagrees with our findings. Another study on MDR and ESBL lactose-fermenting Enterobacteriaceae at the human‒dairy interface in Northwest Ethiopia revealed the dominance of E. coli (71.3%), Citrobacter spp. (15.2%), Enterobacter spp. (10.2%), and Klebsiella spp. (6.9%), which is in line with our findings. A study in Cape Province, South Africa, revealed Salmonella and E. coli as the most prevalent bacterial species (40). N. flavescens is an exceptional bacterial species identified from dairy farm environments in our investigation. Although it is typically regarded as a normal flora of the upper respiratory tract of humans and animals, its presence in environmental sources is infrequently reported. The detection of N. flavescens in dairy farm environments may indicate contamination from the fecal matter or respiratory secretions of humans or animals (41). While generally considered harmless, the occurrence of N. flavescens in such settings has significant implications. From a “One Health” perspective, commensal Neisseria species are known reservoirs for genes associated with AMR (42). Of the total isolates recovered, 45.3% were identified as ESKAPE pathogens. This proportion is 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 (43). There are limited reports about ESKAPE under this collective term in Ethiopia, although species-specific reports are available. S. aureus (an ESKAPE pathogen) was reported in 20.8% of Addis Ababa, Ethiopia. Our finding is also higher than other findings carried out in the USA, with 42.2% from bloodstream infections (44). This percentage is lower than that reported in a study conducted in southern Ethiopia, where 65.3% of this group of pathogens were identified in clinical samples (45). These discrepancies may be due to differences in sample sources, study design protocols and antibiotic exposure. ESKAPE pathogens from dairy farm settings may be animal specific, but they possess a broader range and higher AMR rates from human sources in the clinical setting (46). This group of pathogens is related to diseases such as mastitis on dairy farms, possesses resistance profiles different from those of human sources, and can be transmitted directly with colonized animals, contaminated animal manure, and waste effluent (47). Although antibiotics were introduced as miracle drugs in modern medicine, owing to their abuse and easy accessibility in human and veterinary practice, bacteria have developed resistance and have been declared among the top global public health challenges by the WHO (1). It directly causes the deaths of 1.27 million people and contributes to 4.95 million deaths (3). The main cause of AMR is ESKAPE pathogens. They can evade/escape common antimicrobial treatments and resist many drug classes (48). The occurrence of these pathogens in the dairy farm setting is alarming. They are reported mainly from human medicine, and their occurrence has not yet been extensively studied in dairy farm environments in Ethiopia. Therefore, this study provides comprehensive information on their distribution in this setting. In this study, the majority of bacterial isolates demonstrated resistance to ampicillin (73.9%) and tetracyclines (63%) among GNB isolates and penicillin (52.2%) and tetracycline (47.8%) among GPB isolates. These findings align with those reported in Bahirdar, Ethiopia (11), but contrast with results from Cape Province, South Africa (40). Notably, meropenem, ertapenem, and amikacin exhibited the highest efficacy, possibly due to their limited use in dairy farm settings. Conversely, the most frequently used antibiotics in these settings are penstrep, oxytetracycline, and sulfonamides (53). Among the bacterial isolates recovered, E. coli had the highest percentage of MDR bacteria (60%), followed by P. aeruginosa (58.3%) and K. pneumoniae (53.8%). This is consistent with a study in Gondar, Ethiopia (54). In other findings from Ethiopia, 70.7% of E. coli strains were resistant (55). A study from Slovakia reported 64.3% MDR in E. coli isolates recovered from dairy farm samples (56). Similarly, 68% MDR was detected among E. coli isolates in Romania. These findings are inconsistent with our results. A study from France also reported 38% MDR among E. coli isolates. Another study from Indonesia reported that 11.7% of E. coli isolates from dairy farm wastewater and 37.1% of MDR E. coli were also obtained from Jordan cattle farms (57). Similarly, 13.7% of bacterial isolates recovered from South African dairy farms were MDR E. coli (58) . These findings are lower than those of our study. In addition to E. coli , MDR strains of K. pneumoniae have been reported in different studies. A study in Indonesia reported that 12.57% of MDR K. pneumoniae strains were isolated from dairy farm samples (59). These findings are lower than our findings, whereas 53.57% of K. pneumoniae were MDR in the same county (60). This finding is comparable to that of our study. The total proportion of MDR bacterial isolates in this study was 46%, which is lower than the rates reported in Gondar, Ethiopia (54), and Bahirdar, Ethiopia (11). However, this prevalence exceeds the findings from a study conducted in Selangor, Malaysia (61). The variation in the occurrence of AMR/MDR bacterial isolates may be attributed to factors such as sample size, study design, seasonal fluctuations, waste and manure management strategies, antimicrobial usage at dairy farms, and the number of antibiotic agents tested during the AST. A longitudinal study design was used in this study because it provides a more comprehensive understanding of AMR prevalence, antibiotic usage patterns, farm management practices, and seasonal effects over time. Relying on single-time point sampling may not accurately capture the true frequency of AMR bacteria within the dairy farm environment(28). In the present study, the distribution of ESBL-producing bacteria was 19.6%, with the highest proportion of E. coli (12%), which is greater than that reported in a study conducted in Malaysia (2.8%) involving cow manure samples (61). Our findings are lower than those of a study conducted in Germany, where 70.6% of the isolates were ESBL producers, and the occurrence rate of ESBLs was 21.3% in Gondar, Ethiopia (54). However, our results were greater than those of a study conducted in Malaysia, where 6.5% of ESBL producers were recovered from dairy farm environments (62). There were no records about the prevalence of carbapenemase-producing bacteria in this study. This may be due to the restricted use of carbapenems in the study area, and carbapenem drugs are not used on dairy farms (63). The presence of ESBL-producing bacteria in dairy farm environments represents a significant risk, as they can disseminate resistance genes through plasmids among microbial communities, facilitating their spread to both commensal and pathogenic bacteria. This environmental reservoir complicates infection control and treatment, particularly in resource-limited settings where access to advanced antibiotics such as cephamycins and carbapenems remains limited (64). Moreover, dairy farms serve as hotspots for AMR dissemination via direct contact, animal interactions, and contaminated food and water, highlighting the critical need for vigilant antimicrobial stewardship and monitoring strategies to mitigate public health risks (65). The dairy farm environment is conducive to the spread of resistance genes through plasmids among microbial communities. This makes it more likely that resistance spreads to both commensals and pathogens, making infection management strategies more difficult (66). The rampant, often uncontrolled, use of antibiotics in veterinary practices, from treating illness to promoting growth, coupled with inadequate waste management on dairy farms, likely fuels the alarming rise of MDR bacterial strains. Horizontal transfer of resistance genes between pathogenic and nonpathogenic bacteria, facilitated by environmental contamination, exacerbates this crisis. A proactive One Health approach, emphasizing routine antimicrobial resistance (AMR) surveillance, improved farm hygiene practices, and judicious antimicrobial stewardship, is critical for mitigating the spread of these resistant infections to both humans and the wider ecosystem. Limitations of the study This study has many limitations. First, the sampling sites were limited to dairy farms in Addis Ababa, Ethiopia, which may not accurately represent dairy farms in other regions of the country. Second, the study relied solely on phenotypic methods for antimicrobial susceptibility testing (AST). The minimum inhibitory concentration (MIC) for better evaluation of bacterial susceptibility could not be determined and it didn’t incorporate molecular techniques to identify resistance genes, such as those related to extended-spectrum β-lactamases (ESBLs) or their mechanisms, because of resource limitations. Third, the sample size was relatively small in relation to the number of dairy farms present in the country, indicating a need for further study. Lastly, since the study was cross-sectional, it offers only a snapshot of the occurrence and resistance patterns at the time of sampling, without demonstrating seasonal or temporal changes. Future research with wider geographic coverage, larger sample sizes, and whole-genome sequencing and Metagenomic studies is needed to gain a more complete understanding of the occurrence and antimicrobial resistance profiles of bacterial species in the dairy farm environment. Conclusion This study shows that dairy farm environments serve as reservoirs for antibiotic-resistant bacteria (ARB), which may help in the emergence and spread of resistance within communities. It emphasizes the need for collaborative efforts in managing antibiotic use and calls for further research into the specific mechanisms and drivers of resistance development in these hot spots. Additionally, a temporal analysis of antimicrobial resistance in dairy farms is essential to address seasonal variations in antibiotic use among cattle in response to infection incidences. Raising awareness and educating the public about antibiotic use, adhering to prescription guidelines, and consulting veterinary professionals are crucial steps. This also includes implementing proper manure and waste management practices in these hotspot areas. Furthermore, conducting antimicrobial susceptibility testing (AST) on bacterial isolates from dairy farm settings in veterinary or National Public Health Referral Laboratories is important for gaining a detailed understanding of the antibiotic-resistant bacterial species or genes circulating in Ethiopia. Abbreviations ESKAPE pathogen: Enterococcus faecium , Staphylococcus aureus , Klebsiella pneumonia , Acinetobacter baumannii , Pseudomonas aeruginosa , and Enterobacter species. Declarations Ethics approval and consent to participate This study was approved by Addis Ababa University, Institute of Biotechnology Ethical Review Committee (IoB-IRB) (Minute No IoB/L-7/2016/2024). A support letter was obtained from the Institute of Biotechnology. Consent for publication All authors consent to publication. Availability of data and material The data generated and analyzed during this study are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Funding Only the laboratory work was financially supported by Addis Ababa University. Author contributions Mr. Baye Maru Derso: Conception, sample collection, main laboratory work, execution, acquisition of data, writing original draft, analysis, and interpretation. 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1","display":"","copyAsset":false,"role":"figure","size":127529,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area (Addis Ababa, Ethiopia)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7577060/v1/c3c85f2ce31da7f526da3d4f.jpeg"},{"id":94483472,"identity":"e9e5d808-b394-470a-9c7d-bd6989bc2d98","added_by":"auto","created_at":"2025-10-27 16:26:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37268,"visible":true,"origin":"","legend":"\u003cp\u003ePositive bacterial isolates in each dairy farm environment sample (feces, manure, and wastewater effluent).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7577060/v1/783551d0c66bf1a23633412a.png"},{"id":94483661,"identity":"ab973945-c7c8-4182-abab-914cca61e779","added_by":"auto","created_at":"2025-10-27 16:29:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":53080,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of each bacterial species in dairy farm environment samples (feces, manure, and wastewater effluent).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7577060/v1/7d81fe432b654ed0cc07c364.png"},{"id":102235216,"identity":"41db0810-240e-4a63-8833-70295296c19c","added_by":"auto","created_at":"2026-02-09 16:15:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1408387,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7577060/v1/1f0c28ff-813d-4f72-9574-5d4f6fe2513b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Occurrence and Antimicrobial Resistance Profiles of Bacteria from Dairy Farm Environments in Addis Ababa, Ethiopia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAntimicrobial resistance (AMR) stands out as a critical challenge facing global public health in the 21st century (1). This threatens the efficient treatment capacity of drugs against infectious diseases by jeopardizing decades of medical achievements. A report from the OIE states that this burden will significantly increase future human mortality rates (2). The United States Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) have identified AMR as one of the top ten global public health threats. Antimicrobial-resistant bacterial infections were estimated to have caused 4.95\u0026nbsp;million deaths in 2019, and by 2050, resistant infections could account for 10\u0026nbsp;million deaths annually (3).\u003c/p\u003e\u003cp\u003eAntibiotics are widely used in both human and veterinary medicine to treat infectious diseases. They are also essential for promoting growth and preventing illness. On dairy farms, antimicrobial agents are administered to manage common diseases such as lameness, mastitis, and respiratory diseases in cattle, as well as to optimize the nutritional component in the feed efficiently (4). However, irrational use of these antimicrobial agents leads to the emergence of multidrug-resistant (MDR) bacteria, which are excreted and released into the environment as harmful microbes (5).\u003c/p\u003e\u003cp\u003eThe dairy farm environment is a significant hotspot for the development and spread of antimicrobial-resistant bacteria (ARB) and genes, largely due to the routine use of antibiotics for both clinical and non-clinical purposes. These activities serve as selection pressures for AMR pathogens, thereby promoting the emergence and spread of such superbugs and/or resistance genes (6). According to studies, ARB from dairy farm environments frequently exhibit resistance to three or more antibiotic classes, such as β-lactams, sulfonamides, aminoglycosides, fluoroquinolones, and tetracyclines (7,8).\u003c/p\u003e\u003cp\u003eARB and their genes, have been found in various environmental matrices, including municipal sewage (9,10), medical wastewater (11), beef waste and wastewater, dairy farm waste and wastewater (12,13), and soil samples from an unspoiled environment (14).\u003c/p\u003e\u003cp\u003eStudies have shown that dairy manure, feces, and wastewater often contain a variety of resistance genes, such as extended-spectrum beta-lactamases (ESBLs) (15,16), AmpC (17,18), and carbapenemase-producing Enterobacterales (CPEs) (19). The findings of another study also showed that the dairy farm environment is a highly selective environment that increases the prevalence of resistant bacteria released into the environment, including \u003cem\u003eE. coli\u003c/em\u003e, Klebsiella spp., Pseudomonas spp., Enterococcus spp., and Aeromonas spp. (20,21). Owing to its high nutrient content, dairy manure is frequently used in agriculture as an organic fertilizer. However, manure samples contain ARB and ARB genes, as the use of antibiotic agents in dairy cows is irrational, and when these agents are applied to crops, they pose a significant human health risk, as they contain ARB and antibiotic residues (AR) and are transported to plant tissues, where they cause food-borne diseases (22).\u003c/p\u003e\u003cp\u003eIn April 2014, the World Health Organization (WHO) published its inaugural global report on antimicrobial resistance, highlighting the levels of resistance both within community settings and among bacteria responsible for nosocomial infections (23). Additionally, the WHO released a prioritized list of bacteria urgently requiring new research and therapeutic development in 2017, which was subsequently updated in 2024 to reflect evolving resistance patterns (24). Bacteria classified as having critical priority include carbapenem-resistant \u003cem\u003eA. baumannii\u003c/em\u003e, \u003cem\u003eP. aeruginosa\u003c/em\u003e, and ESBL-producing Enterobacterales. The priority pathogens on the list include \u003cem\u003eE. faecium\u003c/em\u003e, \u003cem\u003eS. aureus\u003c/em\u003e, Campylobacter spp., and Enterobacter spp. Consequently, WHO data underscore that AMR at the human, animal, and environmental interface represents a significant global reservoir for the emergence and dissemination of pathogenic microorganisms.\u003c/p\u003e\u003cp\u003eVarious studies that have been conducted in Ethiopia involving samples from dairy cows, slaughterhouses, dairy products, and dairy farm workers (25,26). However, research on the occurrence and AMR profiles of bacterial species, including ESBLs and CPEs in the dairy farm environments remains limited. Drug resistance is a growing concern that worsens each day. Consequently, there is an urgent need for through investigation into the persistence of ARB in dairy farm environmental samples (16). Understanding AMR profiles in dairy farm environments is essential for addressing the environmental aspect of AMR and controlling transmission pathways from farms to humans, which can occur through edible crops and direct contact. Research has shown that as ESBL-\u003cem\u003eE. coli\u003c/em\u003e strains isolated from dairy cows share genetic similarities with human isolates (27). This information is vital for guiding antibiotic stewardship and shaping manure and waste management policies (18).\u003c/p\u003e\u003cp\u003eThe findings of this study will provide valuable insights into the dairy farm environment as a potential hotspot for the development and spread of ARB and contribute to evidence-based antibiotic stewardship and proper manure and waste disposal strategies to mitigate the rise of AMR.\u003c/p\u003e\u003cp\u003eThis study aimed to investigate the occurrence of bacterial species, including ESKAPE pathogens, and their antimicrobial-resistant profiles. Additionally, it aimed to generate information on the occurrence of ESBL- and carbapenemase-producing bacterial species in environmental samples from dairy farms in Addis Ababa, Ethiopia.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Setting\u003c/h2\u003e\u003cp\u003eThis study was conducted in Addis Ababa, Ethiopia, a city with approximately 6\u0026nbsp;million residents, situated at about 9\u0026deg;1\u0026prime;48\u0026Prime; N latitude and 38\u0026deg;44\u0026prime;24\u0026Prime; E longitude. The city experiences a subtropical highland climate characterized by moderate temperatures and distinct wet and dry seasons, at an average elevation of 2355 m above sea level (Alene et al., 2025). As Ethiopia's political, economic, and cultural center, Addis Ababa\u0026rsquo;s diverse and growing population is driving an increasing demand for livestock products such as meat and milk. The study was carried out across six of the city\u0026rsquo;s 11 sub-cities: Akaki Kality, Bole, Yeka, Arada, Nefassilk, and Kolfe Keranyo, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. (All figures are located at the end of this main text file.).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Map of the study area (Addis Ababa, Ethiopia)\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample collection and preparation\u003c/h3\u003e\n\u003cp\u003eA cross-sectional study was conducted between June 2023 and November 2024. A total of 88 samples were collected from dairy farm environments, consisting of 44 fresh fecal samples, 22 manure samples applied as crop fertilizer, and 22 waste effluent samples that were directly discharged into nearby water bodies. Sampling took place across six sub-cities in Addis Ababa: Akaki Kality, Bole, Nifas Silk-Lafto, Kolfe Keranyo, Yeka, and Arada.\u003c/p\u003e\u003cp\u003eAll samples were collected using a sterile stool cup and transported in a cold chain to the Health Biotechnology Laboratory at Addis Ababa University for microbiological analysis within four hours of collection. The samples were kept at 4\u0026deg;C in a refrigerator until they were processed.\u003c/p\u003e\n\u003ch3\u003eIsolation and identification of bacterial isolates from dairy farms\u003c/h3\u003e\n\u003cp\u003eOne gram of fresh feces and manure and one mL of wastewater effluent samples were suspended in 9 mL of buffered peptone water separately and vortexed to homogenize the samples and settle the large debris. Then, one mL of the supernatant from feces, manure, or wastewater effluent was added to 9 mL of sterile buffered peptone water separately for each sample type and shaken in an aseptic setting. Serial dilutions ranging from 10\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e 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.\u003c/p\u003e\u003cp\u003eFrom the 10\u003csup\u003e\u0026ndash;3,\u003c/sup\u003e 10\u003csup\u003e\u0026ndash;4,\u003c/sup\u003e and 10\u003csup\u003e\u0026ndash;5\u003c/sup\u003e dilutions, 0.1 mL of each aliquot was cultured on blood agar (blood agar base, HiMedia, India, with 5% sheep blood) via a sterile inoculation loop and incubated for 24\u0026ndash;48 hours at 37\u0026deg;C. After proper incubation, representative colonies were selected based on their colony morphology and hemolytic properties, and then purified through successive subculturing (29). Then, plates with 25\u0026ndash;250 colonies were selected for subsequent procedures (30). A subculture was prepared from each unique colony on blood agar. The colonies were characterized on the basis of their hemolysis, surface, color, texture, and other parameters. The most important pathogenic bacteria were identified on the basis of their colony morphology, growth on their respective selective media, and other bacteriological tests (31).\u003c/p\u003e\u003cp\u003eAfter pure culture on blood agar (BA) was obtained, bacterial isolates were classified as Gram-positive and Gram-negative using 3% KOH and Gram staining procedures. Gram-positive bacteria (GPB) were subcultured on the same blood agar plate (BAP) and further identified via biochemical tests, such as oxidation and fermentation (OF), oxidase, catalase, coagulase, bacitracin, and additional tests, such as the optochin test and salt tolerance test, as described previously (32). Catalase-positive (catalase producers) cocci GPB were subcultured onto Mannitol salt agar, followed by the coagulase test to differentiate between coagulase-positive and coagulase-negative Staphylococcus species. Catalase-negative(catalase non-producers) cocci GPB were grown on the same blood agar and identified using hemolytic patterns(i.e., alpha, beta and gamma hemolysis) on blood agar followed by optochin, bacitracin, and salt-tolerant tests for the identification of Streptococci and Enterococci spp. (33,34).\u003c/p\u003e\u003cp\u003eGram-negative bacteria (GNB) were subcultured on MacConkey (MAC) agar and classified as lactose fermenters (LF) or non-fermenters (LNF) based on their lactose fermentation ability. The oxidative and fermentative properties of the isolates were assessed using oxidation and fermentation (OF) test. Following this, oxidase and catalase tests were performed to identify the genera and species of the isolates (33). GNB isolates that did not grow on MAC agar were identified using the Gram-staining technique and additional biochemical tests. After categorizing the GNB isolates as oxidative or fermentative via OF test and as LF or NLF using MAC, further identifications were conducted through standard biochemical tests, including the Urease test, Indole test, methyl red, Voges\u0026ndash;Proskauer test, Citrate utilization test, Mannitol test, Malonate test, and growth on lysine iron agar along with other specific tests for the bacteria (32).\u003c/p\u003e\u003cp\u003eAfter identifying the isolates using biochemical tests, they were subcultured onto their respective selective media to confirm their unique characteristics. The fermentative bacteria (Enterobacterales) were subcultured onto Eosin Methylene Blue Agar (EMB) to observe the dark blue-black colonies with a green metallic sheen characteristic of \u003cem\u003eE. coli\u003c/em\u003e and brown, dark-centered and mucoid colonies for \u003cem\u003eK.pneumonia.\u003c/em\u003e Among these, Salmonella spp. were further subcultured onto Salmonella-Shigella (SS) Agar to observe colonies of colorless colonies with black centers, and \u003cem\u003eP. aeruginosa\u003c/em\u003e from the oxidative group was subcultured onto Pseudomonas selective agar to observe blue to greenish colonies. The results from each biochemical test were then compared with Bergey\u0026rsquo;s Manual of Determinative Bacteriology (35).\u003c/p\u003e\u003cp\u003eMatrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) (36) has been utilized to identify bacteria that are difficult to classify using biochemical tests and for those for which reagents are not readily available on the local market. These bacterial isolates include Bacillus, Acinetobacter, Aeromonas, Neisseria, and Enterobacter species. All isolates were processed for 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\u0026deg;C for future experiments.\u003c/p\u003e\n\u003ch3\u003ePhenotypic antibiotic susceptibility testing\u003c/h3\u003e\n\u003cp\u003eAntibiotic susceptibility testing (AST) was performed via the Kirby\u0026ndash;Bauer disk diffusion method on the basis of the Clinical and Laboratory Standards Institute (CLSI) guidelines, 34th edition (37). This procedure was applied to both GPB and GNB, except for \u003cem\u003eBacillus cereus, Neisseria flavescens\u003c/em\u003e, Aeromonas spp., and Burkholderia species, as these guidelines do not provide clear interpretive criteria for their inhibition zone diameters via disk diffusion methods. GPB were tested against gentamicin (10 \u0026micro;g), clindamycin (2 \u0026micro;g), vancomycin (30 \u0026micro;g), cefoxitin (30 \u0026micro;g), penicillin (10 \u0026micro;g), nitrofurantoin (30 \u0026micro;g), ciprofloxacin (5 \u0026micro;g), erythromycin (15 \u0026micro;g), oxacillin (10 \u0026micro;g) and sulfamethoxazole-trimethoprim (1.25/23.75 \u0026micro;g). Vancomycin was only tested for Enterococcus spp., and oxacillin was only tested for Staphylococcus spp., as there are no interpretive criteria for their inhibition zone diameters. The GNB isolates were also tested against ampicillin (10 \u0026micro;g), cefotetan (30 \u0026micro;g), cefuroxime (30 \u0026micro;g), cefotaxime (30 \u0026micro;g), ceftriaxone (30 \u0026micro;g), ceftazidime (30 \u0026micro;g), cefepime (30 \u0026micro;g), ciprofloxacin (5 \u0026micro;g), sulfamethoxazole trimethoprim (25 \u0026micro;g), gentamycin (10 \u0026micro;g), amikacin (10 \u0026micro;g), meropenem (10 \u0026micro;g), ertapenem (10 \u0026micro;g), piperacillin (100 \u0026micro;g), amoxicillin/clavulanic acid (20/10 \u0026micro;g), and piperacillin-tazobactam (100/10). Piperacillin and piperacillin‒tazobactam were tested only for Acinetobacter spp. and \u003cem\u003eP. aeruginosa\u003c/em\u003e in this study according to the CLSI guidelines. These antibiotic disks were used because they were available on the local market and commonly prescribed in clinical settings.\u003c/p\u003e\u003cp\u003eFor AST, bacterial colonies were used to prepare suspensions that matched 0.5 McFarland standards (1.5 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e CFU/mL) with physiological saline. The bacteria were then spread on M\u0026uuml;ller‒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\u0026deg;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 (37). Species-specific interpretive criteria were applied for both GPB and GNB, as were group-level criteria for gram-negative Enterobacterales, according to these guidelines.\u003c/p\u003e\u003cp\u003eMultidrug-resistant (MDR) bacterial isolates were classified as nonsusceptible (resistant or intermediate) to at least one agent in three or more antimicrobial categories (38).\u003c/p\u003e\n\u003ch3\u003ePhenotypic detection of ESBL-producing bacterial isolates\u003c/h3\u003e\n\u003cp\u003eEnterobacterales groups that were resistant to at least one of the third-generation cephalosporins were screened for the formation of ESBLs. The bacterial isolates suspected of producing ESBLs presented an inhibition zone of \u0026le;\u0026thinsp;27 mm for cefotaxime (30 \u0026micro;g) and/or \u0026le;\u0026thinsp;22 mm for ceftazidime (30 \u0026micro;g) and were selected for confirmatory testing according to the CLSI 34th edition (37).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePhenotypic confirmatory test for ESBL producers\u003c/h2\u003e\u003cp\u003eThe combination disc-diffusion test (CDT) was used to confirm the suspicious ESBL-producing bacteria. It was performed with ceftazidime (30 \u0026micro;g) and cefotaxime (30 \u0026micro;g) alone and in combination with ceftazidime-clavulanic acid (CAZ/CLA) and cefotaxime-clavulanic acid (CTX/CLA) as per CLSI 2024 (37). The zone of inhibition\u0026thinsp;\u0026ge;\u0026thinsp;5 mm for the difference between CAZ/CLA and CTX/CLA was confirmed as an ESBL producer rather than CAZ or CTX alone, as per the 34th edition of CLSI guidelines.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePhenotypic detection of carbapenemase-producing bacterial isolates\u003c/h3\u003e\n\u003cp\u003eBacterial isolates that were nonsusceptible to either meropenem or ertapenem were screened for production of carbapenemase by using the modified carbapenem inactivation method (CIM) per the CLSI guideline 34th edition (37). Briefly, a loop of bacterial colony was suspended in 2 mL of tryptone soya broth (Hi Media, India) from an overnight culture on a tryptone soya agar plate, and a meropenem disk (10 \u0026micro;g) was added and fully immersed in the tryptone soya broth. The tubes were subsequently incubated at 37\u0026deg;C for 4 hrs without agitation. The meropenem disks were then removed via a 10 \u0026micro;L inoculation loop and applied to MHA (Oxoid, UK) freshly inoculated with a 0.5 McFarland suspension of a carbapenem-susceptible strain (\u003cem\u003eE. coli\u003c/em\u003e ATCC 25922). The results were interpreted as per the CLSI guideline 34th edition after overnight incubation.\u003c/p\u003e\n\u003ch3\u003eData Quality Assurance\u003c/h3\u003e\n\u003cp\u003eQuality control procedures were implemented throughout the laboratory process to ensure the accuracy of the study results. For each new batch of biochemical tests, the \u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 700603 and \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 strains were utilized for bacterial identification. The quality and effectiveness of antibiotics were assessed using standard strains of \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 and ATCC 35218. AST was conducted with \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 (ESBL-negative) and \u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 700603 (ESBL-positive) control strains for confirmatory testing of ESBLs producing isolates. In addition, the control strains \u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC BAA-1705 (positive) and \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 (negative) were employed for confirmatory testing of CPE bacterial species. The bacterial strains were obtained from the Ethiopian Institute of Public Health (EPHI).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThe data obtained from this study were coded via Microsoft Excel and Pivotal tables were utilized to calculate the frequency and percentages of bacterial isolates in each sampling sites, sample types, season and sampling months. The Statistical Package for Social Sciences (SPSS) Version 27 software (IBM Corporation, Armonk, USA) were used to calculate the frequency and percentages of antimicrobial resistance profiles of the bacterial isolates.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAmong the total 88 samples collected from the dairy farm environment, 85.2% tested positive for one or more bacterial species. From these positive samples, 137 bacterial isolates were recovered.\u003c/p\u003e\n\u003cp\u003eAmong the 137 positive bacterial isolates, 30 (21.9%) were GPB, and 107 (78.1%) were GNB. Among the total bacterial isolates recovered, 62 (45.3%) were ESKAPE pathogens. Among these pathogens, 53 (85.5%) were GNB, whereas 9 (14.5%) were GPB. Among these strains, Enterobacter spp. 28 (52.8%) and \u003cem\u003eS. aureus\u0026nbsp;\u003c/em\u003e9 (100%) were the dominant GNB and GPB, respectively, among the ESKAPE groups. For GPB, the dominant isolate was \u003cem\u003eS. aureus\u0026nbsp;\u003c/em\u003e9 (30%), followed by CoNS and\u003cem\u003e\u0026nbsp;Bacillus cereus\u0026nbsp;\u003c/em\u003e7 (23.3%),\u003cem\u003e\u0026nbsp;\u003c/em\u003ewith similar frequencies. The least prevalent GPB was \u003cem\u003eS. agalactiae\u003c/em\u003e 2 (6.7%). Among GNB, the dominant isolate was Enterobacter spp. 28 (26.2%), followed by \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u0026nbsp;\u003c/em\u003e20\u003cem\u003e\u0026nbsp;\u003c/em\u003e(18.7%), while the least frequently isolated was \u003cem\u003eN. flavescens\u0026nbsp;\u003c/em\u003e2\u0026nbsp;(1.9%) (Table 1).\u003c/p\u003e\n\u003cp\u003eA total of seventeen (17) different bacterial species were identified from the total positive samples. Among these, the most frequently isolated bacterium was Enterobacter spp. 28 (20.4%), followed by \u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003e20 (14.6%), \u003cem\u003eK. pneumoniae\u003c/em\u003e 13 (9.5%),\u003cem\u003e\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;P. aeruginosa\u0026nbsp;\u003c/em\u003e12 (8.8%)\u003cem\u003e\u0026nbsp;\u003c/em\u003e(Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1 Bacterial isolates recovered from dairy farm environmental samples at Addis Ababa, Ethiopia, from June 2023 to November 2024\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"456\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eGram-Negative isolates (GNB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eESKAPE pathogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eAcinetobacter spp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e7(6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eAeromonas spp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e10(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eBurkholderia spp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3(2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eE.coli\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e20(18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eEnterobacter spp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e28(26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e28(52.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eK. pneumonia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e13(12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e13(24.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eM. morgannii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4(3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eN. flavescens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eP. aeruginosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e12(11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e12(22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eSalmonella spp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e8(7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eGram-Positive Bacteria (GBP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003eESKAPE pathogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eB. cereus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e7(23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003eCoNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e7(23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eE. fecalis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e5(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e9(30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e9(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 212px;\"\u003e\n \u003cp\u003e\u003cem\u003eS. agalactiae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 151px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCoNS, coagulase-negative Staphylococcus spp.\u003c/p\u003e\n\u003cp\u003eAmong these 137 positive bacterial isolates, the highest proportion of bacterial isolates was obtained from Akaki Kality subcity, 43 (31.4%), followed by Nefassilk Lafto subcity dairy farm environments, 24 (17.5%); the lowest proportion of the isolates was found from Bole and Arada subcity dairy farms, 16 (11.7%). (Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2 Distribution of bacterial species from dairy farm environments at Addis Ababa, Ethiopia, from June 2023 to November 2024\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"500\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 389px;\"\u003e\n \u003cp\u003eSampling sites (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eBacterial Isolates (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eAKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eARD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eBSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eKKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eNLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eYSD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAcinetobacter spp(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAeromonas spp(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eBacillus cereus\u003c/em\u003e(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0())\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eBurkholderia spp(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eE.coli\u003c/em\u003e(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e8(18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(18.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eEnterobacter spp(28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e8 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e6(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e5(17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eE. fecalis\u003c/em\u003e(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eM. morgannii\u003c/em\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eN.flavescens\u003c/em\u003e(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eP. aeruginosa\u003c/em\u003e(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e5(20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eSalmonella spp(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e3(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u003c/em\u003e(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eCoNS\u003c/em\u003e(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e4(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cem\u003eStrep. agalactiae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e2(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eTotal (137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e43(31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e16(11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e16(11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e17(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e24(17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e21(15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: AKD, Akaki Kality Subcity dairy farms; ARD, Arada Subcity dairy farms; BSD, Bole Subcity dairy farms; KKD, Kolfe Keranyo Subcity dairy farms; NLD, Nefassilk Subcity dairy farms; and YSD, Yeka Subcity dairy farms: CoNS, Coagulase Negative Staphylococcus\u003c/p\u003e\n\u003cp\u003eAmong the total samples collected, 70 (51.1%) bacterial isolates were isolated from dairy feces, 37 (27%) from manure, and 30 (21.9%) from the total bacterial isolates recovered, as shown in Figure 2.\u003c/p\u003e\n\u003cp\u003eFigure 2 Positive bacterial isolates in each dairy farm environment sample (feces, manure, and wastewater effluent).\u003c/p\u003e\n\u003cp\u003eEnterobacter spp. (24.3%, 17/70) were the most abundant bacteria in the fecal samples, followed by \u003cem\u003eE. coli\u003c/em\u003e (15.7%, 11/70). \u003cem\u003eP. aeruginosa\u003c/em\u003e and Enterobacter spp. (13.5%, 5/37) were the most frequently isolated bacteria from manure, while \u003cem\u003eE. coli\u003c/em\u003e (23.3%, 7/30) was most common in wastewater effluents, as shown in Figure 3.\u003c/p\u003e\n\u003cp\u003eFigure 3 Distribution of each bacterial species in dairy farm environment samples (feces, manure, and wastewater effluent).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibiogram Profiles of GPB Isolates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe highest percentage/frequency of antimicrobial resistance in GPB was observed for penicillin (12 (52.2%)), followed by tetracycline (11 (47.8%)). The lowest resistance rate was found for gentamicin, clindamycin, and cefoxitin (4 [17.4%]). Two (22.2%) of the \u003cem\u003eS. aureus\u003c/em\u003e isolates were identified as methicillin-resistant (MRSA) via the use of a cefoxitin disk as a surrogate marker; 4 (80%) of the Enterococcus spp. were resistant to vancomycin. (Table 3).\u003c/p\u003e\n\u003cp\u003eTable 3 Antimicrobial resistance profiles of gram-positive bacterial isolates recovered from dairy farm environment samples at Addis Ababa, Ethiopia, from June 2023 to April 2024\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"780\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"11\" valign=\"bottom\" style=\"width: 674px;\"\u003e\n \u003cp\u003eAntibiotics tested (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003eBacterial isolates (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003ePen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003eAMP/OXY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eERY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003eTET\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCLO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003eSXT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eGEN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003eVAN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eFOX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cem\u003eE. fecalis\u0026nbsp;\u003c/em\u003e(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e4(80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003eCoNS (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e4(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e3(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2(28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2(28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e2(28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cem\u003eStrep. agalactiae\u0026nbsp;\u003c/em\u003e(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cem\u003eS. aureus\u0026nbsp;\u003c/em\u003e(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e5(55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e5(55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e2(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e6(66.7))\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 105px;\"\u003e\n \u003cp\u003eTotal(23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e12(52.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7(30.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e9(39.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 61px;\"\u003e\n \u003cp\u003e11(47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e5(21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e8(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e4(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 59px;\"\u003e\n \u003cp\u003e8(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003e4(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e4(17.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e4(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePen, penicillin; AMP,\u0026nbsp;ampicillin; Oxy,\u0026nbsp;oxacillin; ERY,\u0026nbsp;erythromycin; TET,\u0026nbsp;tetracycline; CIP,\u0026nbsp;ciprofloxacin; NIT,\u0026nbsp;nitrofurantoin; CLO,\u0026nbsp;clindamycin; SXT,\u0026nbsp;sulfamethoxazole-trimethoprim; GEN, gentamycin; VAN, vancomycin; FOX, cefoxitin; NT, not\u0026nbsp;tested\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibiogram of GNB Isolates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe antibiotic resistance rates for GNB isolates were highest for ampicillin (68, 73.9%), followed by tetracycline (58, 63%) and sulfamethoxazole-trimethoprim (46, 49.5%). Significant resistance to cefuroxime, 43 (46.7%), cefotetan, 28 (30.4%), and ceftazidime, 27 (29.3%), was also detected. The lowest resistance\u0026nbsp;rates were\u0026nbsp;observed for meropenem (7.6%), amikacin (3.3%), and ertapenem (2.2%).\u003c/p\u003e\n\u003cp\u003eAmong the bacterial isolates tested, Enterobacter spp.\u0026nbsp;(100%)\u0026nbsp;presented\u0026nbsp;the highest resistance\u0026nbsp;to ampicillin (100%). Acinetobacter spp. was another bacterial isolate that presented the highest level of resistance to piperacillin, at 6 (85.7%). Moreover, a lack of resistance (0%) against cefotaxime, ceftriaxone, ceftazidime, aztreonam, ertapenem, meropenem, amikacin and ciprofloxacin was detected in Enterobacter spp., and no resistance\u003cem\u003e\u0026nbsp;\u003c/em\u003eagainst amoxicillin/clavulanic acid, cefepime, ceftriaxone, ceftazidime, aztreonam, meropenem, ertapenem, amikacin, gentamycin, ciprofloxacin and sulfamethoxazole/trimethoprim was detected in \u003cem\u003eM. morgannii\u003c/em\u003e (Table 4). (Table 4 is located at the end of this main text file.)\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 4 Antimicrobial resistance profiles of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003egram-negative isolates recovered from\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003edairy farm\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eenvironments\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;at Addis Ababa, Ethiopia, from June 2023 to April 2024\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"1046\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003eBacterial isolates (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eAM/PIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003eAMC/PTZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eFEP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eCTX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eCRO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eCXM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eCTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eCAZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eETP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eMEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eGM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eAN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eCIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eSXT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eTET\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003eAcinetobacter spp(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e6(85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e3(42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2(28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3(42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e5(71.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e4(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003eEnterobacter spp(28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e28(100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e6(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e2(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e1(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e14(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e10(35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e1(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e4(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e4(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e9(32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e15(53.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cem\u003eE.coli\u003c/em\u003e(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e17(85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e8(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e2(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e8(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e6(30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e12(60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e10(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e4(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e3(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e5(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e13(65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e13(65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cem\u003eK.pneumonia\u003c/em\u003e(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e3(23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e1(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e5(38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e1(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e9(69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e6(46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e1(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3(23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e6(46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e10(76.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cem\u003eM.morganii\u003c/em\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e2(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cem\u003eP.aeruginosa\u003c/em\u003e(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e8(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e4(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e3(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e2(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e6(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e4(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e6(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e8(66.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e9(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003eSalmonella spp(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e6(75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e5(62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003eNT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e3(37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e5(62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e4(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003eTotal(92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e68(73.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e24(26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e8(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e14(15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e12(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e37(40.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e28(30.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e9(9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 52px;\"\u003e\n \u003cp\u003e11(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e2(2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e7(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e16(17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e3(3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e18(19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e46(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003e58(63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations:\u0026nbsp;AM: ampicillin, PIP: piperacillin. PTZ: Piperacillin-tazobactam AMC: Amoxicillin/clavulanic acid, FEP: Cefepime, CTX: Cefotaxime, CRO: Ceftriaxone, CTT: Cefotetan, CXM: Cefuroxime, CAZ: Ceftazidime, AT: Aztreonam, ETP: Ertapenem, MEM: Meropenem, GM: Gentamycin, AN: Amikacin, CIP: Ciprofloxacin, SXT: Sulphamethoxazole\u0026ndash;Trimethoprim, TET: Tetracycline, NT: Not tested\u003c/p\u003e\n\u003cp\u003eN.B. Piperacillin was tested for Acinetobacter spp. and \u003cem\u003eP. aeruginosa\u003c/em\u003e only instead of ampicillin in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMDR Profiles of Bacterial Isolates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The bacterial species with the highest percentages of antibiotic resistance were Enterobacter spp.\u003cem\u003e\u0026nbsp;\u003c/em\u003e(100%) for ampicillin and Acinetobacter spp.\u0026nbsp;(85.7%)\u0026nbsp;for\u0026nbsp;piperacillin. Multidrug resistance (MDR) was\u0026nbsp;detected\u0026nbsp;in 53 (46%) bacterial isolates.\u003c/p\u003e\n\u003cp\u003eAmong the bacterial isolates processed for the AST, \u003cem\u003eE. coli\u003c/em\u003e had the highest percentage of MDR bacteria (12, 60%), followed by \u003cem\u003eP. aeruginosa\u003c/em\u003e (7, 58.3%) and \u003cem\u003eK. pneumoniae\u003c/em\u003e (7, 53.8%) (Table 5).\u003c/p\u003e\n\u003cp\u003eTable 5 Antimicrobial resistance patterns\u0026nbsp;of bacterial isolates recovered from dairy farm\u0026nbsp;environments in\u0026nbsp;Addis Ababa, Ethiopia, from June 2023 to April 2024\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"795\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 370px;\"\u003e\n \u003cp\u003eAntimicrobial resistance pattern of isolates (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003eBacterial isolates (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eR0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eR3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eR4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eR5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eR6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eR7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eR8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026gt;R8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eMDR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003eAcinetobacter spp(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003eEnterobacter spp(28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e11(39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e9(32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eE.coli\u003c/em\u003e(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e3(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e12(60)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eK.pneumoniae\u003c/em\u003e(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e6(46.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3(23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e7(53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eM.morganii\u003c/em\u003e(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eP.aeruginosa\u003c/em\u003e(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e3(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e7(58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003eSalmonella spp(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5(62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e3(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eE.fecalis\u003c/em\u003e(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003eCoNS(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eStrep. agalactiae\u003c/em\u003e(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eS.aurues\u003c/em\u003e(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eTotal(115)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9(7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e36(31.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e16(13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e14(12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e18(15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e3(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2(1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e53(46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: R0, susceptible to all drugs tested; R1, resistant to 1 drug; R2, resistant to 2 drugs; R3, resistant to 3 drugs; R4, resistant to 4 drugs; R5, resistant to 5 drugs; R6, resistant to 6 drugs; R7, resistant to 7 drugs; R8, resistant to 8 drugs and \u0026gt;R8, resistant to more than 8 drugs tested; MDR, multidrug resistant\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMagnitudes of ESBL and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecarbapenemase-producing (CPE) bacterial isolates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the GNB isolates (N=92) selected for the AST, 23 (25%) were presumptive ESBL producers. Among these 23 potential ESBL-producing Enterobacterales, 18 (78.3%) were confirmed as ESBL producers. The overall distribution of ESBL-producing bacteria was 19.6% (18/92), with the highest proportion found in \u003cem\u003eE. coli\u003c/em\u003e (12%; 11/92) and the lowest in \u003cem\u003eK. pneumoniae\u003c/em\u003e (7.6%; 7/92). Among the ESBL-producing isolates, \u003cem\u003eE. coli\u003c/em\u003e accounted for 61.1% (11/18), and \u003cem\u003eK. pneumoniae\u003c/em\u003e accounted for 38.9% (7/18). The highest number of ESBL-producing isolates was found in dairy feces, with 12 (52.2%), followed by dairy wastewater effluent, with 5 (21.7%). The lowest percentage was in manure, with 1 (4.3%) isolate. No CPE was detected in any samples from the dairy farm environment (Table 6).\u003c/p\u003e\n\u003cp\u003eTable 6 Distribution of ESBL- and CPE-producing isolates from dairy farm environments at selected dairy farms in Addis Ababa, Ethiopia, from June 2023 to June 2024\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"708\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 249px;\"\u003e\n \u003cp\u003eSample type (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eFeces\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003eWastewater\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003eManure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eBacterial isolates (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003eESBL positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003eESBL negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003eESBL positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003eESBL negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003eESBL positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003eESBL negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003eCPE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003e(11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e7(58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003e4(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cem\u003eK .pneumoniae\u003c/em\u003e (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e5(45.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003e1(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eTotal(18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e12(52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3(13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 81px;\"\u003e\n \u003cp\u003e5(21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e1(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eESBL, extended-spectrum beta-lactamases; CPE, carbapenemase-producing Enterobacterales\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWaste generated from dairy farm environments contains antibiotic residues, antibiotic-resistant bacteria, and their genes\u0026nbsp;(39). These are the main drivers of the development and spread of AMR in the environment and public health. AMR is a great challenge for public health\u0026nbsp;worldwide\u0026nbsp;because of alarming resistance and the absence of new antimicrobial discoveries to treat infectious diseases\u0026nbsp;(11). The main\u0026nbsp;factors associated with\u0026nbsp;AMR in dairy farm\u0026nbsp;environments are\u0026nbsp;a lack of awareness\u0026nbsp;of\u0026nbsp;AMR in antibiotic users,\u0026nbsp;the\u0026nbsp;prescription of antibiotics without veterinary guidelines, and\u0026nbsp;the\u0026nbsp;overuse of antibiotics for infection treatment, prophylaxis, and growth promotion.\u003c/p\u003e\n\u003cp\u003eIn our findings, a total of 137 bacterial isolates were recovered from dairy farm environmental samples, such as fresh feces, manure, and wastewater effluents. Among the bacterial isolates recovered, Enterobacter spp. (28, 20.4%) constituted the highest percentage, followed by \u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003e(20, 14.6%). There are few studies on the occurrence of bacterial species and their AMR profiles in dairy farm environments in Ethiopia. However, there are some reports about the distribution and AMR profiles of bacteria from Bahirdar, Ethiopia, in hotspot environments, including dairy farms. Salmonella spp. (37.8%), followed by Citrobacter spp. (9.3%), are the most prevalent bacteria in dairy waste and wastewater (11). This disagrees with our findings. Another study on MDR and ESBL lactose-fermenting Enterobacteriaceae at the human‒dairy interface in Northwest Ethiopia revealed the dominance of \u003cem\u003eE. coli\u003c/em\u003e (71.3%), Citrobacter spp. (15.2%), Enterobacter spp. (10.2%), and Klebsiella spp. (6.9%), which is in line with our findings. A study in Cape Province, South Africa, revealed Salmonella and \u003cem\u003eE. coli\u0026nbsp;\u003c/em\u003eas the most prevalent bacterial species\u0026nbsp;(40).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eN. flavescens\u003c/em\u003e is an exceptional bacterial species identified from dairy farm environments in our investigation. Although it is typically regarded as a normal flora of the upper respiratory tract of humans and animals, its presence in environmental sources is infrequently reported. The detection of \u003cem\u003eN. flavescens\u003c/em\u003e in dairy farm environments may indicate contamination from the fecal matter or respiratory secretions of humans or animals (41). While generally considered harmless, the occurrence of \u003cem\u003eN. flavescens\u003c/em\u003e in such settings has significant implications. From a \u0026ldquo;One Health\u0026rdquo; perspective, commensal Neisseria species are known reservoirs for genes associated with AMR (42).\u003c/p\u003e\n\u003cp\u003eOf the total isolates recovered, 45.3% were identified as ESKAPE pathogens. This proportion is higher than the pooled prevalence of 41.7%, reported in a meta\u0026ndash;analysis conducted in Africa, which emphasized ESKAPE pathogens recovered in milk and meat samples (43). There are limited reports about ESKAPE under this collective term in Ethiopia, although species-specific reports are available. \u003cem\u003eS. aureus\u003c/em\u003e (an ESKAPE pathogen) was reported in 20.8% of Addis Ababa, Ethiopia. Our finding is also higher than other findings carried out in the USA, with 42.2% from bloodstream infections (44). This percentage is lower than that reported in a study conducted in southern Ethiopia, where 65.3% of this group of pathogens were identified in clinical samples (45). These discrepancies may be due to differences in sample sources, study design protocols and antibiotic exposure. ESKAPE pathogens from dairy farm settings may be animal specific, but they possess a broader range and higher AMR rates from human sources in the clinical setting (46). This group of pathogens is related to diseases such as mastitis on dairy farms, possesses resistance profiles different from those of human sources, and can be transmitted directly with colonized animals, contaminated animal manure, and waste effluent (47).\u003c/p\u003e\n\u003cp\u003eAlthough\u0026nbsp;antibiotics were introduced as miracle drugs in modern medicine,\u0026nbsp;owing\u0026nbsp;to\u0026nbsp;their\u0026nbsp;abuse and\u0026nbsp;easy\u0026nbsp;accessibility in human and veterinary practice, bacteria\u0026nbsp;have\u0026nbsp;developed resistance and\u0026nbsp;have been declared among\u0026nbsp;the top global public health challenges by\u0026nbsp;the\u0026nbsp;WHO\u0026nbsp;(1). It\u0026nbsp;directly causes the\u0026nbsp;deaths of 1.27 million people and\u0026nbsp;contributes to\u0026nbsp;4.95 million deaths\u0026nbsp;(3). The main\u0026nbsp;cause\u0026nbsp;of AMR is ESKAPE pathogens. They can evade/escape common antimicrobial\u0026nbsp;treatments\u0026nbsp;and resist many drug\u0026nbsp;classes\u0026nbsp;(48).\u003c/p\u003e\n\u003cp\u003eThe occurrence of these pathogens in the dairy farm setting\u0026nbsp;is\u0026nbsp;alarming. They are reported mainly from human medicine,\u0026nbsp;and their occurrence\u0026nbsp;has\u0026nbsp;not yet\u0026nbsp;been\u0026nbsp;extensively studied in dairy farm environments in Ethiopia. Therefore, this study provides comprehensive information on their distribution in this setting.\u003c/p\u003e\n\u003cp\u003eIn this study, the majority of bacterial isolates demonstrated resistance to ampicillin (73.9%) and tetracyclines (63%) among GNB isolates and penicillin (52.2%) and tetracycline (47.8%) among GPB isolates. These findings align with those reported in Bahirdar, Ethiopia (11), but contrast with results from Cape Province, South Africa (40). Notably, meropenem, ertapenem, and amikacin exhibited the highest efficacy, possibly due to their limited use in dairy farm settings. Conversely, the most frequently used antibiotics in these settings are penstrep, oxytetracycline, and sulfonamides (53).\u003c/p\u003e\n\u003cp\u003eAmong the bacterial isolates recovered, \u003cem\u003eE. coli\u003c/em\u003e had the highest percentage of MDR bacteria (60%), followed by \u003cem\u003eP. aeruginosa\u003c/em\u003e (58.3%) and \u003cem\u003eK. pneumoniae\u003c/em\u003e (53.8%). This is consistent with a study in Gondar, Ethiopia (54). In other findings from Ethiopia, 70.7% of \u003cem\u003eE. coli\u003c/em\u003e strains were resistant (55). A study from Slovakia reported 64.3% MDR in \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u003c/em\u003e isolates recovered from dairy farm samples (56). Similarly, 68% MDR was detected among \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u003c/em\u003e isolates in Romania. These findings are inconsistent with our results.\u003c/p\u003e\n\u003cp\u003eA study from France also reported 38% MDR among \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u003c/em\u003e isolates. Another study from Indonesia reported that 11.7% of \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u003c/em\u003e isolates from dairy farm wastewater and 37.1% of MDR \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u003c/em\u003e were also obtained from Jordan cattle farms (57). Similarly, 13.7% of bacterial isolates recovered from South African dairy farms were MDR \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u0026nbsp;\u003c/em\u003e(58)\u003cem\u003e.\u0026nbsp;\u003c/em\u003eThese findings are lower than those of our study. In addition to \u003cem\u003eE.\u003c/em\u003e\u003cem\u003e\u0026nbsp;coli\u003c/em\u003e, MDR strains of \u003cem\u003eK. pneumoniae\u003c/em\u003e have been reported in different studies. A study in Indonesia reported that 12.57% of MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e strains were isolated from dairy farm samples (59). These findings are lower than our findings, whereas 53.57% of \u003cem\u003eK.\u003c/em\u003e\u003cem\u003e\u0026nbsp;pneumoniae\u003c/em\u003e were MDR in the same county (60). This finding is comparable to that of our study.\u003c/p\u003e\n\u003cp\u003eThe total proportion of MDR bacterial isolates in this study was 46%, which is lower than the rates reported in Gondar, Ethiopia\u0026nbsp;(54),\u0026nbsp;and Bahirdar, Ethiopia (11). However, this prevalence exceeds the findings from a study conducted in Selangor, Malaysia\u0026nbsp;(61).\u003c/p\u003e\n\u003cp\u003eThe variation in the occurrence of AMR/MDR bacterial isolates may be attributed to factors such as sample size, study design, seasonal fluctuations, waste and manure management strategies, antimicrobial usage\u0026nbsp;at dairy farms, and the number of antibiotic agents tested during the AST. A longitudinal study design was used in this study because it provides a more comprehensive understanding of AMR prevalence, antibiotic usage patterns, farm management practices, and seasonal effects over time. Relying on single-time point sampling may not accurately capture the true frequency of AMR bacteria within the dairy farm environment(28).\u003c/p\u003e\n\u003cp\u003eIn the present study, the distribution of ESBL-producing bacteria was 19.6%, with the highest proportion of \u003cem\u003eE. coli\u003c/em\u003e (12%), which is greater than that reported in a study conducted in Malaysia (2.8%) involving cow manure samples (61). Our findings are lower than those of a study conducted in Germany, where 70.6% of the isolates were ESBL producers, and the occurrence rate of ESBLs was 21.3% in Gondar, Ethiopia (54). However, our results were greater than those of a study conducted in Malaysia, where 6.5% of ESBL producers were recovered from dairy farm environments (62). There were no records about the prevalence of carbapenemase-producing bacteria in this study. This may be due to the restricted use of carbapenems in the study area, and carbapenem drugs are not used on dairy farms (63).\u003c/p\u003e\n\u003cp\u003eThe presence of ESBL-producing bacteria in dairy farm environments represents a significant risk, as they can disseminate resistance genes through plasmids among microbial communities, facilitating\u0026nbsp;their spread to both commensal and pathogenic bacteria. This environmental reservoir complicates infection control and treatment, particularly in resource-limited settings where access to advanced antibiotics such as cephamycins and carbapenems remains limited (64). Moreover, dairy farms serve as hotspots for AMR dissemination via direct contact, animal interactions, and contaminated food and water, highlighting the critical need for vigilant antimicrobial stewardship and monitoring strategies to mitigate public health risks\u0026nbsp;(65). The dairy farm environment is conducive to the spread of resistance genes through plasmids among microbial communities.\u0026nbsp;This makes it more likely that resistance spreads to both commensals and pathogens, making infection management strategies more difficult (66).\u003c/p\u003e\n\u003cp\u003eThe rampant, often uncontrolled, use of antibiotics in veterinary practices, from treating illness to promoting growth, coupled with inadequate waste management on dairy farms, likely fuels the alarming rise of MDR bacterial strains. Horizontal transfer of resistance genes between pathogenic and nonpathogenic bacteria, facilitated by environmental contamination, exacerbates this crisis. A proactive One Health approach, emphasizing routine antimicrobial resistance (AMR) surveillance, improved farm hygiene practices, and judicious antimicrobial stewardship, is critical for mitigating the spread of these resistant infections to both humans and the wider ecosystem.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has many limitations. First, the sampling sites were limited to dairy farms in Addis Ababa, Ethiopia, which may not accurately represent dairy farms in other regions of the country. Second, the study relied solely on phenotypic methods for antimicrobial susceptibility testing (AST).\u0026nbsp;The\u0026nbsp;minimum inhibitory concentration (MIC) for better evaluation of bacterial susceptibility\u0026nbsp;could not be determined and it\u0026nbsp;didn\u0026rsquo;t incorporate molecular techniques to identify resistance genes, such as those related to extended-spectrum \u0026beta;-lactamases (ESBLs) or their mechanisms, because of resource limitations. Third, the sample size was relatively small in relation to the number of dairy farms present in the country, indicating a need for further study. Lastly, since the study was cross-sectional, it offers only a snapshot of the occurrence and resistance patterns at the time of sampling, without demonstrating seasonal or temporal changes.\u003c/p\u003e\n\u003cp\u003eFuture research with wider geographic coverage, larger sample sizes, and whole-genome sequencing and Metagenomic studies is needed to gain a more complete understanding of the occurrence and antimicrobial resistance profiles of bacterial species in the dairy farm environment.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study shows that dairy farm environments serve as reservoirs for antibiotic-resistant bacteria (ARB), which may help in the emergence and spread of resistance within communities. It emphasizes the need for collaborative efforts in managing antibiotic use and calls for further research into the specific mechanisms and drivers of resistance development in these hot spots.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditionally, a temporal analysis of antimicrobial resistance in dairy farms is essential to address seasonal variations in antibiotic use among cattle in response to infection incidences. Raising awareness and educating the public about antibiotic use, adhering to prescription guidelines, and consulting veterinary professionals are crucial steps. This also includes implementing proper manure and waste management practices in these hotspot areas. Furthermore, conducting antimicrobial susceptibility testing (AST) on bacterial isolates from dairy farm settings in veterinary or National Public Health Referral Laboratories is important for gaining a detailed understanding of the antibiotic-resistant bacterial species or genes circulating in Ethiopia.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eESKAPE\u0026nbsp;\u003c/strong\u003epathogen: \u003cem\u003eEnterococcus faecium\u003c/em\u003e, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003eKlebsiella pneumonia\u003c/em\u003e, \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, and Enterobacter species.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by Addis Ababa University, Institute of Biotechnology Ethical Review Committee (IoB-IRB) (Minute No IoB/L-7/2016/2024). A support letter was obtained from the Institute of Biotechnology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data generated and analyzed during this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOnly the laboratory work was financially supported by Addis Ababa University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMr. Baye Maru Derso: Conception, sample collection, main laboratory work, execution, acquisition of data, writing original draft, analysis, and interpretation.\u003c/p\u003e\n\u003cp\u003eDr. Bayable Atinafu Kassa: Supervision, conception, investigation, writing, review, and editing\u003c/p\u003e\n\u003cp\u003eDr. Tesfaye Admassu Abate: Supervision, conception, investigation, writing, review, and editing\u003c/p\u003e\n\u003cp\u003eDr. Alemayehu Godana Birhanu: Supervision, conception, investigation, writing, review, and editing\u003c/p\u003e\n\u003cp\u003eProfessor Tesfaye Sisay Tessema: Main supervision, conception, investigation, resources, writing, review, and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Debre Berhan University for sponsoring the PhD study and Addis Ababa University for their teaching, coaching, and mentorship. We also appreciate dairy farm owners for their willingness during the sample collection process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. Global Antimicrobial Resistance and Use Surveillance System (GLASS) [Internet]. World Health Organization. 2022 [cited 2025 May 13]. Available from: https://books.google.com/books?hl=en\u0026amp;lr=\u0026amp;id=dHsOEQAAQBAJ\u0026amp;oi=fnd\u0026amp;pg=PR4\u0026amp;dq=World+Health+Organization.+Global+antimicrobial+resistance+and+use+surveillance+system+(GLASS)+report:+2021%3B+2021.\u0026amp;ots=EZVeqnKn29\u0026amp;sig=ZuQD9SKYUKP4iwgyjr7DqQGwfLY\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Neill J. 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Available from: https://link.springer.com/article/10.1186/s12917-018-1737-0\u003c/li\u003e\n\u003cli\u003eBeyene AM, Gizachew M, Yousef AE, Haileyesus H, Abdelhamid AG, Berju A, et al. Multidrug-resistance and extended-spectrum beta-lactamase-producing lactose-fermenting enterobacteriaceae in the human-dairy interface in northwest Ethiopia. PLoS One [Internet]. 2024 May 1 [cited 2025 May 19];19(5):e0303872. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0303872\u003c/li\u003e\n\u003cli\u003eTweldemedhin M, Muthupandian S, Gebremeskel TK, Mehari K, Abay GK, Teklu TG, et al. Multidrug resistance from a one health perspective in Ethiopia: A systematic review and meta-analysis of literature (2015\u0026ndash;2020) [Internet]. Vol. 14, One Health. 2022 [cited 2025 May 19]. 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Available from: https://www.sciencedirect.com/science/article/pii/S1438422113000167\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Antimicrobial resistance, Infection control, MDR, Environment","lastPublishedDoi":"10.21203/rs.3.rs-7577060/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7577060/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eWastes generated from dairy environments are critical hotspots where pathogenic and opportunistic pathogens interact with high concentrations of antibiotic residues and normal flora, potentially contributing to the occurrence of superbugs. Therefore, this study aimed to isolate bacteria from dairy environmental feces, manure, and waste effluent, determine their antimicrobial resistance patterns, and examine the distribution of extended-spectrum beta-lactamase and carbapenemase-producing bacterial isolates in Addis Ababa, Ethiopia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional study was conducted in Addis Ababa, Ethiopia, from June 2023 to November 2024. A total of 88 samples, including feces, manure, and wastewater effluent, were collected from the dairy farm environment. The samples were transported and processed under sterile conditions. Following this, bacterial isolation, identification, and antimicrobial susceptibility testing were performed in accordance with standard microbiological protocols.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOut of the total samples collected, 137 bacterial isolates were recovered from the dairy farm environment, with the highest proportion, 76(50.7%), found in fecal samples. Enterobacter spp. (28, 20.4%) and \u003cem\u003eE. coli\u003c/em\u003e (20, 13.3%) were the most frequently isolated species among the bacterial isolates. \u003cem\u003eE. coli\u003c/em\u003e showed the highest percentage of multidrug resistance, 12 (60%), among the tested isolates. Overall, 45.3% of the bacterial isolates were ESKAPE pathogens. Of these, 53 (85.5%) were gram-negative bacteria, while 9 (14.5%) were gram-positive bacteria. Gram-positive bacteria had the highest resistance rates against penicillin (12, 52.2%) and tetracycline (11, 47.8%), whereas Gram-negative bacteria showed the highest resistance against ampicillin (68, 73.9%). Multidrug resistance was present in 46% of the bacterial isolates.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eWastes generated from dairy farm environments contain multidrug-resistant bacterial isolates, which may contaminate nearby environments, crops, and water bodies and affect public health. Therefore, there must be proper antibiotic usage in dairy farm settings and adequate management of dairy manure and wastewater effluent before they are discharged into the environment.\u003c/p\u003e","manuscriptTitle":"Occurrence and Antimicrobial Resistance Profiles of Bacteria from Dairy Farm Environments in Addis Ababa, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-27 15:52:02","doi":"10.21203/rs.3.rs-7577060/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-21T12:51:07+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"12447931839903495899781434074507239678","date":"2025-10-21T07:42:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217160488196472474494018689584530773339","date":"2025-10-20T07:37:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-19T02:43:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-18T16:55:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-18T13:39:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224672491374795827486473701352572615569","date":"2025-10-17T13:47:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"317185873581399843282103952080036643901","date":"2025-10-15T16:40:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"30356168472638381223220302352733853779","date":"2025-10-15T15:06:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"181746432871145180431819160240375806711","date":"2025-10-15T14:14:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"290286097087076322190579474303175314583","date":"2025-10-15T13:46:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54136526041353400453481957821676720179","date":"2025-10-14T14:10:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224302620529476503158134662406596212092","date":"2025-10-13T13:37:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289332400513590030709381832274399681030","date":"2025-10-13T13:13:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-13T13:07:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-01T07:24:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-25T06:43:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-24T10:39:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2025-09-24T10:36:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e8f77102-8a22-40cc-bb64-8a3091612886","owner":[],"postedDate":"October 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T16:11:02+00:00","versionOfRecord":{"articleIdentity":"rs-7577060","link":"https://doi.org/10.1186/s12866-026-04766-6","journal":{"identity":"bmc-microbiology","isVorOnly":false,"title":"BMC Microbiology"},"publishedOn":"2026-02-06 15:59:43","publishedOnDateReadable":"February 6th, 2026"},"versionCreatedAt":"2025-10-27 15:52:02","video":"","vorDoi":"10.1186/s12866-026-04766-6","vorDoiUrl":"https://doi.org/10.1186/s12866-026-04766-6","workflowStages":[]},"version":"v1","identity":"rs-7577060","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7577060","identity":"rs-7577060","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}