Multidrug Antibiotic Resistance Index and Antimicrobial Resistance Patterns of Escherichia coli in Intensive Pig Farms in Kenya

Multidrug Antibiotic Resistance Index and Antimicrobial Resistance Patterns of Escherichia coli in Intensive Pig Farms in Kenya | 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 Multidrug Antibiotic Resistance Index and Antimicrobial Resistance Patterns of Escherichia coli in Intensive Pig Farms in Kenya Christine Inguyesi, Moses Olum, Peter Ndirangu, Nathan Langat, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7428840/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Nov, 2025 Read the published version in One Health Outlook → Version 1 posted 17 You are reading this latest preprint version Abstract Antibiotic resistance is a major public health threat globally, rendering the treatment of human and animal infections difficult, longer and expensive. This study was carried out to determine the antibiotic resistance profiles of Escherichia coli isolated from pig farming environments in selected pig farms around Kenya. Waste water and the associated sludge together with ground surface boot sock samples were collected from preselected intensive pig farms. The samples were cultured, E. coli isolates identified using standard microbiological procedures and confirmed by Matrix Assisted Laser Desorption/Ionization Time-of Flight Mass Spectroscopy (MALDI-TOF MS). Antibiotic susceptibility testing was performed using the Kirby–Bauer disc diffusion method against Ampicillin, Amoxicillin-clavulanic acid, Gentamicin, Trimethoprim-Sulfamethoxazole, Chloramphenicol, Enrofloxacin and Cefotaxime. The highest resistance was recorded against Amoxicillin-clavulanic acid at 30.4% and the lowest was recorded for Cefotaxime at 7.1%. Multidrug resistance was observed for 25.9% of the isolates. The isolates had varied Multidrug Antibiotic Resistance (MAR) indices, but the average index was 0.33. The results suggest that there is high antibiotic exposure in the intensive pig farms that increase the selection pressure leading to development and dissemination of antibiotic-resistant E. coli among pig populations, to humans and potentially into the environment further compounding the public health threat. AMR Antibiotics E. coli Environment Intensive Pig farming Figures Figure 1 Figure 2 Figure 3 BACKGROUND The rising demand for livestock products in Kenya and worldwide, driven by population growth and urbanization, has led to the widespread adoption of intensive livestock production methods to efficiently meet this demand. However, in large-scale pig production systems, diseases can significantly decrease productivity and increase mortality rates, largely due to poor hygiene, low welfare standards, and production stress commonly seen in intensive operations ( 1 ). To address health and productivity issues in pigs, antibiotics are frequently used, sometimes in sub-therapeutic doses, as feed additives or treatments to protect livestock and investments. However, the indiscriminate use of antibiotics on farms, often without proper antimicrobial stewardship, has been identified as a major contributor to the emergence of antibiotic-resistant bacteria in pigs and their environments, due to selective pressure ( 2 ). This resistance threatens the effective treatment of bacterial infections in both humans and animals, leading to increased morbidity, mortality, and rising healthcare and veterinary costs. Livestock and their farming environments are considered reservoirs for antimicrobial-resistant bacteria, which can potentially be transmitted to humans. As a result, livestock farming is widely recognized as a significant risk factor for antibiotic resistance in humans ( 3 ). The selection process for bacterial resistance does not end with the cessation of antibiotic treatment or feeding in animals. Instead, it continues as waste from livestock farms—containing antibiotic residues, resistant bacteria, and resistance genes—is released into the environment through farmland application, wastewater collection points, or water bodies. Research indicates that the repeated use of pig manure and wastewater from pig farms increases the selection of resistant bacterial populations in the soil due to presence of sub-optimal concentration of antibiotics, with effects reaching the atmosphere, surface and groundwater, and even contaminating irrigated crops and nearby community water sources. This results in the constant introduction and reintroduction of potentially pathogenic microorganisms from animal sources into the environment ( 4 ). The environment thus serves as both a reservoir and a pathway for the emergence and spread of antibiotic resistance, significantly increasing the risk of transmission through the food chain, particularly in Low and Middle Income Countries (LMICs). While manure is the main route through which antibiotic residues, resistance genes, and resistant bacteria from animals enter the environment, gut bacteria in food animals also play a crucial role as environmental reservoirs for antibiotic resistance ( 5 ). There are limited measures in place to control the spread of resistant bacteria from livestock manure, across humans, animals, and the environment, unlike the more stringent policies for human waste management. Horizontal gene transfer within the environment can play a key role in the exchange and acquisition of antibiotic resistance genes, significantly contributing to the evolution of microbial communities. Containing the spread of antimicrobial-resistant (AMR) bacteria is crucial for protecting the broader environment from related health hazards ( 6 ). Escherichia coli ( E. coli ) is a normal part of the intestinal flora in both animals and humans. However, in immunosuppressed individuals, it can cause disease including urinary tract infections and life-threatening bloodstream infections ( 7 ). In animals, E. coli infections can lead to significant economic losses due to increased mortality and morbidity. The World Health Organization (WHO) has categorized E. coli as a priority pathogen due to it developing multidrug resistance ( 8 ). E. coli can act as a reservoir for resistant genes, facilitating their transmission, which poses a risk to both animal and human health ( 9 ). Studies have shown a direct relationship between antimicrobial use and antimicrobial resistance in E. coli isolates from pigs, poultry and cattle. For instance, the emergence of resistance to Colistin, a critically important antibiotic, has been largely linked to its use in food producing animals ( 10 ). The high resistance to this drug was observed in China during regular surveillance of resistance to antimicrobials associated with commensal E. coli from food-producing animals. The dissemination of Colistin resistance from the veterinary environment to humans has been confirmed, making it a major public health concern ( 11 ). This study evaluated dynamics of antimicrobial resistance in intensive pig farming in Kenya with a focus on E. coli . METHODS Study design and sample size determination A cross-sectional study was carried out in 12 counties of Kenya as shown in Fig. 1 . These are the counties where intensive pig farming is prevalent ( 12 ). The Sampling frame was provided by farmer’s choice and farms with at least 15 sows, and were supplying their finisher pigs to large pork retail entities in Kenya were randomly selected for inclusion in the study. The sample size was determined using the formulae according to ( 13 ). where Z is 1.96 at 95% Confidence interval, p is the expected AMR prevalence taken to be 50%, q is 1minus p and e is the margin of error, which was taken to be 11%. Given the limited studies on antimicrobial resistance spillover from intensive pig farming in Kenya, this study aims to provide foundational insights within this context allowing for an initial assessment of AMR patterns in environmental samples, in order to generate valuable data to inform more precise and extensive research in the future. Farmers were fully informed on the essence of the study to improve food safety and their role in data provision to improve antimicrobial stewardship. Those that were willing to participate in the study first signed a consent form before sampling commenced. Sampling was conducted between February and April 2022 and farms were identified using alphabetical codes. A total of 80 samples were collected in triplicates from 16 intensive pig farms. Five samples were collected from each farm. Samples included upstream water and sediment samples, downstream water and sediment samples, and two bootsock samples that were pooled into one. Sample collection Water and soil samples collection These were collected aseptically upstream and downstream in triplicates from the piggeries. Fifty milliliters of water and a scoop of sediment was collected into sterile centrifuge tubes at two locations along the main effluent exiting the piggery. The samples at the point closest to the shelter were designated upstream water and sediment samples while the corresponding downstream samples were collected at the furthest possible location. Each sample was collected in triplicates. Following collection, the tubes were securely capped, wiped externally with 70% ethanol and appropriately labeled. Subsequently, the samples were stored in a well-insulated cool box with icepacks. Boot socks sample collection Two boot sock samples were collected from the windward direction of the piggeries and pooled. The boot socks were soaked beforehand in normal saline while being consistently hand palpated. Freshly gloved hands were used to put on sterile plastic shoe covers over the gumboots, followed by wearing the boot socks over the shoe covers. The individual conducting the sampling proceeded alongside the pig shelter, following the typical direction of the prevailing wind. Using gloved sterile hands, the boot socks were removed and placed into pre-dispensed Tryptic Soy Broth contained within a zip-lock sampling bag. After sealing the bag, it was gently palpated until adequately soaked in the broth, then appropriately labeled and positioned upright on ice within the cool box. All samples were promptly transported to the laboratory, where culturing began within 24 hours of collection Laboratory methods Culturing of the samples This was carried out at the KALRO - Veterinary Science Research Institute (VSRI). The water samples were vortexed for 30 seconds and were then diluted in Normal saline at a ratio of 1:10. Approximately 5g of sediment was diluted in 10ml of Normal Saline. The boot sock samples were palpated for a minute after which 1ml was taken into a sterile tube. For each sample, a loopful was streaked on MacConkey Agar (Himedia, Mumbai, India). Culturing was performed in duplicates and the cultures incubated overnight at 37 0 C. After 18-24hours, colony morphology was observed followed by Catalase, Oxidase and Indole tests and subsequently Gram staining and microscopic observation. This was carried out for the preliminary identification of bacteria showing pink colonies surrounded by a red region of precipitated bile salts on MacConkey agar and appearing as gram negative rods under the microscope. Matrix assisted laser desorption/ionization time-of flight mass spectroscopy (MALDI-TOF MS) was used to confirm the identity of the isolates which were then preserved as 10% glycerol stocks at -20 0 C for further analysis ( 14 ). Antibiotic Susceptibility Testing (AST) Antibiotic susceptibility testing was performed using the Kirby–Bauer disk diffusion method as recommended by the European Committee on Antimicrobial Susceptibility Testing ( 15 ), on Mueller Hinton Agar (Himedia, Mumbai, India) ( 16 ). Seven antibiotics were tested (Basingstoke, Hampshire, United Kingdom) (Table 1 ). E. coli ATCC® 25922 was used for quality control during the antibiotic sensitivity testing. The diameters of the inhibition zones were measured and interpreted according to the EUCAST, 2024 breakpoints. Table 1 Criteria for interpretation of the diameter of the zones of inhibition of E. coli. Antibiotic Class Antibiotic Potency (µg) Disc abbreviation Interpretation (Zone in mm) Susceptible (S) ≥ Intermediate (I) Resistant <(R) Penicillins Ampicillin 10 AMP 14 - 14 Amoxicillin-clavulanic acid 20 − 10 AMC 19 - 19 Aminoglycosides Gentamicin 10 GEN 17 - 17 Sulfonamides Trimethoprim- Sulfamethoxazole 1.25–23.75 SXT 14 11–13 11 Chloramphenicol Chloramphenicol 30 C 17 - 17 Fluoroquinolones Enrofloxacin 5 ENR 25 22–24 22 Cephalosporins Cefotaxime 5 CTX 20 17–19 17 DATA ANALYSIS All the data was recorded using Microsoft Excel. The zones of inhibition obtained after conducting antibiotic sensitivity testing was interpreted according to EUCAST ( 16 ). Multiple antibiotic resistance (MAR) index was calculated as follows: A/B; where ‘A’ was taken as the number of antibiotics an isolate was resistant to, and ‘B’ was taken as the total number of antibiotics tested. Multidrug resistance (MDR) patterns were determined from the isolates exhibiting resistance to at least one antibiotic agent in different antibiotic classes ( 17 ). The data was presented by the aid of Microsoft Excel and Graphpad Prism software. RESULTS A total of 112 E. coli isolates were identified from the five sample types: 10.7% ( n = 12) were isolated from bootsock samples, 38% (n = 46) were isolated from water samples where 19.6% ( n = 46) were from upstream water samples, 21.4% (n = 46) from downstream water samples, 48.3% of the isolates were isolated from sediment samples where 31.3% (n = 54) were from upstream sediment samples and 17% ( n = 54) from downstream sediment samples. These isolates were tested for their susceptibility to seven antibiotics (Table 2 ). Table 2 Percentages of E. coli isolates resistant to different antibiotic classes classified by sample type. Antibiotic Overall resistance% (n = 112) Bootsocks samples % (n = 12) Water samples % (n = 46) Sediment samples % (n = 54) AMP 26.8 50 28.3 20.4 CN 12.5 8.3 10.9 14.8 AMC 30.4 41.7 28.3 29.6 SXT 25.9 66.7 17.4 24.1 C 11.6 25 10.9 9.3 ENR 11.6 8.3 15.2 11.1 CTX 7.1 8.3 8.7 5.6 The isolates obtained from boot sock samples had the highest resistance against SXT at 66.7%. Isolates derived from water samples were most resistant to the penicillins at 28.3% each while 29.6% of the sediment isolates were resistant to AMC (Table 2 ). The E. coli strains were found to be sensitive to the Cephalosporin, CTX, with a resistance of only 4.5% and intermediate resistance of 2.7% (Fig. 2 ). Resistance to ENR and C was found to be 8.9% and 11.6% respectfully. The highest resistance rates were observed for the Penicillins tested, AMC at 30.4% followed by AMP recorded to be 26.8%. Table 3 Antibiograms of E. coli isolates Pattern Number Antibiogram Number of Antibiotics Percentage of The Isolates (n) 1 No resistance 0 46.4 (52) 2 AMC 1 8( 9 ) 3 CN 1 5.4( 6 ) 4 SXT 1 4.5( 5 ) 5 C 1 3.6( 4 ) 6 AMP 1 0.9( 1 ) 7 ENR 1 0.9( 1 ) 8 AMP-AMC 2 4.5( 5 ) 9 SXT-ENR 2 0.9( 1 ) 10 AMC-CTX 2 1.8( 2 ) 11 AMP-SXT 2 1.8( 2 ) 12 CN-SXT 2 0.9( 1 ) 13 AMP-ENR 2 0.9( 1 ) 14 CN-ENR 2 0.9( 1 ) 15 AMP-CTX 2 0.9( 1 ) 16 AMP-CN-ENR 3 0.9( 1 ) 17 AMP-AMC-SXT 3 4.5( 5 ) 18 AMP-SXT-C 3 0.9( 1 ) 19 AMP-AMC-SXT-ENR 4 1.8( 2 ) 20 AMP-AMC-SXT-C 4 2.7( 3 ) 21 AMP-AMC-SXT-CTX 4 0.9( 1 ) 22 AMP-CN-AMC-SXT-ENR 5 0.9( 1 ) 23 AMP-AMC-SXT-C-ENR 5 1.8( 2 ) 24 AMP-CN-AMC-SXT-C-CTX 6 0.9( 1 ) 25 AMP-CN-AMC-SXT-C-ENR-CTX 7 1.8( 2 ) In this study, 46.4% of the isolates were susceptible to all the antimicrobials tested, while 1.8% were resistant to all the antibiotics tested. Twenty-four patterns of resistance to the tested antibiotics (antibiograms) were recorded (Table 3 ). The most dominant resistance was against AMP, as registered in 15 out of 24 patterns overally. Interestingly, only 0.9% of the isolates were resistant to AMP alone. The isolates exhibited a total of 18 patterns that were designated as multidrug-resistant (MDR) since they exhibited resistance to more than one antibiotic agent in different antibiotic classes ( 17 ). Among the isolates, 25.9% of the E. coli isolates were shown to be MDR. AMP-AMC and AMP-AMC-SXT were the most common patterns of resistance at 4.5% each. Rates of intermediate resistance were low and hence were classified as resistant ( 18 ). The highest calculated MAR was 1 exhibited by 1.8% of the isolates. The isolates had varied MAR indices but the average index was 0.33 as (Fig. 3 ). DISCUSSION The present study sought to identify antibiotic resistance in and around intensive pig farms in Kenya by isolating E. coli and characterizing their antibiotic resistance profiles. Many similar studies conducted in other countries have reported varied percentages of resistance in E. coli against the antibiotics tested attributable to the antibiotics in use and the regulations in the country. The resistance recorded in the current study against Ampicillin and Amoxicillin clavulanic acid and chloramphenicol was 57.1% and 11.6%. This is lower than the resistance observed in a study conducted in Thailand on medium sized pig farms (500–5000 swine population) and large scale pig farms (more than 5000), which reported 98.6% resistance to ampicillin and amoxicillin and 75% resistance to Chloramphenicol on medium sized pig farms. A resistance of 96.3% was recorded against Ampicillin and amoxicillin from pig farming environments on large scale pig farms. This may be due to the much higher number of pig populations in the sampled farms as compared to the farms in our study. Resistance against ampicillin as detected in waste water in the present study was 28.3%, which was also lower than that detected in the waste water from the medium-sized farms which had resistance rates of 91.7% against Ampicillin and the antibiotic resistance in the sludge (sediments) had an even higher resistance of up to 100% against ampicillin and amoxicillin as compared to the current study that recorded an overall combined resistance against ampicillin and amoxicillin clavulanic acid at 50% in the sediment samples ( 19 ). Another study also observed high resistance rates to Ampicillin and Amoxicillin- clavulanic acid in pig farming environments ( 20 ). Multidrug resistance was observed to be 25.9% in the present study as compared to a South African study which recorded a high percentage of resistance in pig farm isolates and the highest prevalence of MDR was found on the pig farm at 74.6%. Similar to our study, the most common MDR pattern included AMP-SXT-CHL, found in 4.7% of the isolates similar to what is reported in the current study at 4.5% ( 21 ). In the study, similar to the current one, E. coli showed the highest resistance to Chloramphenicol, Trimethoprim-sulfamethoxazole and ampicillin. This is because these antibiotics have been used for a long time in food producing animals. In their 2019 Annual Report on Antimicrobial Agents Intended for Use in Animals, WOAH documented that the largest amount of antibiotics used for animal production were tetracyclines, macrolides and ampicillin ( 22 ). A surveillance conducted in China also investigated the trends in antibiotic resistance in E. coli in pig farming reported a high resistance rate to ampicillin and sulfamethoxazole recorded at, 81.44% and 88.36% respectively as related to the current study where resistance rates were observed to be 26.8% and 25.9% for ampicillin and Trimethoprim-sulfamethoxazole respectively. This could be due to the fact that in China, the use of antibiotics for growth promotion and treatment is largely unregulated ( 23 , 24 ). Although the use of chloramphenicol in animal-producing animals was banned in Kenya, E. coli isolates resistant to chloramphenicol were recovered from pig farms at a rate of 11.6%. Another study recorded a much higher percentage of resistance to chloramphenicol ( 25 , 6 ). This is possibly attributed to horizontal gene transfer of chloramphenicol resistance genes and co-selection of resistance due to the use of other antibiotics ( 26 ). For instance, reports have it that the resistance to tetracycline, sulfamethoxazole and kanamycin, which are accepted for animal use is often transferred together with chloramphenicol resistance ( 27 ). Cephalosporins and fluoroquinolones exhibited a relatively low resistance rate in comparison to other antibiotics in this study. However, they still need monitoring due to their clinical importance since the World Health Organization classified both as critically important antibiotics (CIAs) for human medicine ( 28 ). The increasing occurrence of MDR E. coli poses a public health challenge since E. coli occupies multiple niches, in animals, the environment and humans and, can acquire or transmit antimicrobial resistance genes both vertically and horizontally. The prevalent MDR pattern reported in the current study included resistance to antibiotics commonly used for treating diseases in human and veterinary medicine indicating that there is a possibility of the resistance genes being transmitted to other pigs, the environment and consequently to humans. The multiple antibiotic resistance (MAR) index is commonly applied in the determination of health risk associated with the dissemination of resistance in any given location ( 21 ). A MAR index higher than 0.2 suggests that the bacteria under study were exposed to high antibiotic use environments ( 21 ). The current study recorded a mean MAR index of 0.33 in the pig farming environments confirming the high antibiotic used in pig rearing in Kenya and the high selective pressure created in these environments. The E. coli isolates in the current study were highly sensitive to cephalosporins and fluoroquinolones, with resistance rates of 7.1% and 8.9%. Such results were also reported at about 4% resistance to fluoroquinolones in one study ( 6 ). This serves to caution farmers that increased use of drugs in these classes should be regulated to minimize the risk of development of resistance to them. CONCLUSIONS To the best of our knowledge, this study is among the first in Kenya to investigate antibiotic resistance in E. coli in intensive pig farming environments. The widespread use of antibiotics in food producing animals, particularly in pig rearing, is intricately linked to the development and dissemination of the antibiotic resistance crisis. The high antibiotic use in swine farming in Kenya and worldwide promotes the proliferation of resistant bacteria in pigs that spill over into the pig rearing environments, posing a significant public health threat. One notable route through which humans can be affected by these resistant bacteria is through environmental contamination, greatly exacerbating the global public health challenge. E. coli has been documented to have a greater capacity to accumulate antibiotic resistant genes, especially through horizontal gene transfer. E. coli might colonize the human intestine and act as reservoirs or opportunistic pathogens at any time later in life. Our findings present that E. coli around intensive pig farms are relatively resistant towards critically important antibiotics leading to serious concerns to public health. To meet the increasing demand for pork, the number, size and population of pigs in pig farms will have to increase tremendously. This implies that even greater amounts of antibiotics will be applied to support the increase in swine production, increasing the threat even further. Enhanced monitoring and surveillance in pig farms is essential to gain a more comprehensive understanding of the situation. This data will offer extensive insights to deepen the understanding of antibiotic resistance in pig farming, potentially informing the formulation and improvement of governmental policies aimed at mitigating AMR within the Kenyan pig industry. Abbreviations AMR Antimicrobial resistance MALDITOF MS-Matrix Assisted Laser Desorption/Ionization Time-of Flight Mass Spectroscopy Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials All data generated or analysed during this study are included in this published article Competing interests The authors declare that they have no competing interests Funding This work was funded by the World Animal Protection. Authors’ contribution Christine Inguyesi a *, Moses Olum a , Peter Ndirangu a , Nathan Langat a , Ascah Jesang a , Ednah Masila a , Esther Wachuka a , Ruth Onywera a , Dishon Muloi b , Linet Ochieng b , Victor Yamo c , Kelvin Momanyi c , Patrick Muinde c , Monicah Maichomo a CI participated in the sampling and laboratory analysis, data analysis and interpretation and manuscript writing. MO participated in project conceptualization, sampling, data analysis and interpretation, manuscript writing, PN participated in data analysis and interpretation and manuscript writing, AJ participated in sampling, and manuscript writing, EM participated in sampling, laboratory analysis, data analysis and manuscript writing. EW participated in laboratory analysis and manuscript writing. RO participated in data analysis and manuscript writing. DM and LO participated in laboratory analysis. VY, KM and PM participated in project conceptualization and sampling. MM participated in sampling and manuscript writing. All authors read and approved the final manuscript Acknowledgements The authors would like to acknowledge the contribution of the staff in the Bacteriology Division of the Veterinary Science Research Institute. References Katushabe P, Byamukama B, Byaruhanga J. Burden of Multidrug-Resistant Escherichia coli in Pigs Slaughtered in Uganda and Its Implication on Veterinary Public Health. Open Journal of Veterinary Medicine. 2022;12(12):187–200. Robinson TP, Bu DP, Carrique-Mas J, Fèvre EM, Gilbert M, Grace D, et al. Antibiotic resistance: mitigation opportunities in livestock sector development. Animal. 2017;11(1):1–3. Muloi D, Kiiru J, Ward MJ, Hassell JM, Bettridge JM, Robinson TP, et al. Epidemiology of antimicrobial-resistant Escherichia coli carriage in sympatric humans and livestock in a rapidly urbanizing city. International Journal of Antimicrobial Agents. 2019 Nov;54(5):531–7. Baquero F, Martínez JL, Cantón R. 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Inguyesi","email":"data:image/png;base64,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","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Christine","middleName":"","lastName":"Inguyesi","suffix":""},{"id":509299457,"identity":"6df0b03c-a209-4a42-89e7-81e5311356b2","order_by":1,"name":"Moses Olum","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Moses","middleName":"","lastName":"Olum","suffix":""},{"id":509299458,"identity":"9e6edaa2-ea2b-4d20-aca8-cc5cc8a48464","order_by":2,"name":"Peter Ndirangu","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Ndirangu","suffix":""},{"id":509299459,"identity":"0d2d3015-bcaa-45af-b21c-907f3b0a1583","order_by":3,"name":"Nathan Langat","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Nathan","middleName":"","lastName":"Langat","suffix":""},{"id":509299460,"identity":"3a4f76ee-15ca-43eb-ba48-de4f09ada1bb","order_by":4,"name":"Ascah Jesang","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Ascah","middleName":"","lastName":"Jesang","suffix":""},{"id":509299462,"identity":"0752977e-8d38-4599-80e3-1f786d69e834","order_by":5,"name":"Ednah Masila","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Ednah","middleName":"","lastName":"Masila","suffix":""},{"id":509299463,"identity":"211c709a-8a69-42a8-aa7a-02140e9c138a","order_by":6,"name":"Esther Wachuka","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Esther","middleName":"","lastName":"Wachuka","suffix":""},{"id":509299464,"identity":"2f821f1b-fd34-45f3-8dc7-6d65a236367f","order_by":7,"name":"Ruth Onywera","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Ruth","middleName":"","lastName":"Onywera","suffix":""},{"id":509299465,"identity":"9da38492-0e5b-4c03-9f85-53093f1334fd","order_by":8,"name":"Dishon Muloi","email":"","orcid":"","institution":"International Livestock Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Dishon","middleName":"","lastName":"Muloi","suffix":""},{"id":509299466,"identity":"53948861-ece2-4103-ad34-ee2724210780","order_by":9,"name":"Linet Ochieng","email":"","orcid":"","institution":"International Livestock Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Linet","middleName":"","lastName":"Ochieng","suffix":""},{"id":509299467,"identity":"bfa56fc2-2b24-4635-a56e-f1562ea6cc8f","order_by":10,"name":"Victor Yamo","email":"","orcid":"","institution":"World Animal Protection","correspondingAuthor":false,"prefix":"","firstName":"Victor","middleName":"","lastName":"Yamo","suffix":""},{"id":509299468,"identity":"783152f0-58bc-4b16-882c-d0da90364359","order_by":11,"name":"Kelvin Momanyi","email":"","orcid":"","institution":"World Animal Protection","correspondingAuthor":false,"prefix":"","firstName":"Kelvin","middleName":"","lastName":"Momanyi","suffix":""},{"id":509299469,"identity":"f4818387-8e1a-4471-b976-27efe1dcab39","order_by":12,"name":"Patrick Muinde","email":"","orcid":"","institution":"World Animal Protection","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Muinde","suffix":""},{"id":509299470,"identity":"76275a88-e1fa-4502-ae8e-eae5d930b278","order_by":13,"name":"Monicah Maichomo","email":"","orcid":"","institution":"Kenya Agricultural and Livestock Research Organization, Veterinary Science Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Monicah","middleName":"","lastName":"Maichomo","suffix":""}],"badges":[],"createdAt":"2025-08-21 19:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7428840/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7428840/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s42522-025-00177-1","type":"published","date":"2025-11-10T15:57:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90500077,"identity":"4ee0a77f-21f2-4515-85c2-30b4a329dcca","added_by":"auto","created_at":"2025-09-03 11:35:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":42690,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA map of Kenya showing the Study sites\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7428840/v1/1d6c0159e7debba122eb6f90.png"},{"id":90500075,"identity":"d7ed8c1c-1a51-402a-986e-3292c964cec1","added_by":"auto","created_at":"2025-09-03 11:35:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5286,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAntimicrobial resistance of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eE. coli\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolates (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003en=112\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAMP- Ampicillin\u003c/p\u003e\n\u003cp\u003eCN- Gentamicin\u003c/p\u003e\n\u003cp\u003eAMC- Amoxicillin Clavulanic acid\u003c/p\u003e\n\u003cp\u003eSXT- Trimethoprim Sulfamethoxazole\u003c/p\u003e\n\u003cp\u003eC- Chloramphenicol\u003c/p\u003e\n\u003cp\u003eENR*- Enrofloxacin\u003c/p\u003e\n\u003cp\u003eCTX- Cefotaxime\u003c/p\u003e\n\u003cp\u003e*Interpreted using Ciprofloxacin breakpoints\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7428840/v1/9c0915209efcea0e77077cee.png"},{"id":90500076,"identity":"8d1a7bca-11d8-4117-965c-37e15310f8f4","added_by":"auto","created_at":"2025-09-03 11:35:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4258,"visible":true,"origin":"","legend":"\u003cp\u003eA bar graph showing the MAR indices of the \u003cem\u003eE. coli\u003c/em\u003e isolates (\u003cem\u003en=112\u003c/em\u003e)\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7428840/v1/0d9062ab3fc8a987c585cf7c.png"},{"id":96105939,"identity":"95eb8094-86b8-4c6f-bef0-11df085b1ff3","added_by":"auto","created_at":"2025-11-17 16:12:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":980682,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7428840/v1/343380d7-3eef-4b44-80f4-2ed016a29e58.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multidrug Antibiotic Resistance Index and Antimicrobial Resistance Patterns of Escherichia coli in Intensive Pig Farms in Kenya","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eThe rising demand for livestock products in Kenya and worldwide, driven by population growth and urbanization, has led to the widespread adoption of intensive livestock production methods to efficiently meet this demand. However, in large-scale pig production systems, diseases can significantly decrease productivity and increase mortality rates, largely due to poor hygiene, low welfare standards, and production stress commonly seen in intensive operations (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo address health and productivity issues in pigs, antibiotics are frequently used, sometimes in sub-therapeutic doses, as feed additives or treatments to protect livestock and investments. However, the indiscriminate use of antibiotics on farms, often without proper antimicrobial stewardship, has been identified as a major contributor to the emergence of antibiotic-resistant bacteria in pigs and their environments, due to selective pressure (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This resistance threatens the effective treatment of bacterial infections in both humans and animals, leading to increased morbidity, mortality, and rising healthcare and veterinary costs. Livestock and their farming environments are considered reservoirs for antimicrobial-resistant bacteria, which can potentially be transmitted to humans. As a result, livestock farming is widely recognized as a significant risk factor for antibiotic resistance in humans (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe selection process for bacterial resistance does not end with the cessation of antibiotic treatment or feeding in animals. Instead, it continues as waste from livestock farms\u0026mdash;containing antibiotic residues, resistant bacteria, and resistance genes\u0026mdash;is released into the environment through farmland application, wastewater collection points, or water bodies. Research indicates that the repeated use of pig manure and wastewater from pig farms increases the selection of resistant bacterial populations in the soil due to presence of sub-optimal concentration of antibiotics, with effects reaching the atmosphere, surface and groundwater, and even contaminating irrigated crops and nearby community water sources. This results in the constant introduction and reintroduction of potentially pathogenic microorganisms from animal sources into the environment (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe environment thus serves as both a reservoir and a pathway for the emergence and spread of antibiotic resistance, significantly increasing the risk of transmission through the food chain, particularly in Low and Middle Income Countries (LMICs). While manure is the main route through which antibiotic residues, resistance genes, and resistant bacteria from animals enter the environment, gut bacteria in food animals also play a crucial role as environmental reservoirs for antibiotic resistance (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). There are limited measures in place to control the spread of resistant bacteria from livestock manure, across humans, animals, and the environment, unlike the more stringent policies for human waste management. Horizontal gene transfer within the environment can play a key role in the exchange and acquisition of antibiotic resistance genes, significantly contributing to the evolution of microbial communities. Containing the spread of antimicrobial-resistant (AMR) bacteria is crucial for protecting the broader environment from related health hazards (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eE. coli\u003c/em\u003e) is a normal part of the intestinal flora in both animals and humans. However, in immunosuppressed individuals, it can cause disease including urinary tract infections and life-threatening bloodstream infections (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In animals, \u003cem\u003eE. coli\u003c/em\u003e infections can lead to significant economic losses due to increased mortality and morbidity. The World Health Organization (WHO) has categorized \u003cem\u003eE. coli\u003c/em\u003e as a priority pathogen due to it developing multidrug resistance (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). \u003cem\u003eE. coli\u003c/em\u003e can act as a reservoir for resistant genes, facilitating their transmission, which poses a risk to both animal and human health (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStudies have shown a direct relationship between antimicrobial use and antimicrobial resistance in \u003cem\u003eE. coli\u003c/em\u003e isolates from pigs, poultry and cattle. For instance, the emergence of resistance to Colistin, a critically important antibiotic, has been largely linked to its use in food producing animals (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The high resistance to this drug was observed in China during regular surveillance of resistance to antimicrobials associated with commensal \u003cem\u003eE. coli\u003c/em\u003e from food-producing animals. The dissemination of Colistin resistance from the veterinary environment to humans has been confirmed, making it a major public health concern (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study evaluated dynamics of antimicrobial resistance in intensive pig farming in Kenya with a focus on \u003cem\u003eE. coli\u003c/em\u003e.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and sample size determination\u003c/h2\u003e\u003cp\u003eA cross-sectional study was carried out in 12 counties of Kenya as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. These are the counties where intensive pig farming is prevalent (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e The Sampling frame was provided by farmer\u0026rsquo;s choice and farms with at least 15 sows, and were supplying their finisher pigs to large pork retail entities in Kenya were randomly selected for inclusion in the study. The sample size was determined using the formulae according to (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cimg 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HT09PV/Tk4cPH8bOnTuRkZGBrKws8V30PfF4vI9TSBo5HA4LrQxO4urqavT29iInJwdFRUVCtxMOHTqEzZs3IxaLwWazIS0tDaNGjYLH4+lj4WkzrNFoRGpqKgDgs88+w1tvvYVwOAyDwQC73d6nFMG1kHlQiSxPl+CNC/NEcJaQtA1ALIESSKMRdF2Hz+cT1xgo5PYktk2XQl/y3zRV99epjGvbRCJdCRRFEXvsEr+LrF0oFMLbb7+NDz/8EN3d3RgzZgzuv/9+PPbYY3C5XACPFhBhWlpacODAARw8eBCNjY1ieVdRFLFrBDxSQQ4ZOV00eORZoampCV999RV8Ph/S09Mxfvx4kSEHAO3t7aivrxeLLwsXLsSaNWuQnZ2N3t5e+Hw+WK1W1NbWYv/+/X3u2xdffIGPPvoIVVVVUFUVOTk5KCwsFJ+brzG7zvjrX//614lvXg0YYyLuSdMbEYRIQbqNSMWkaU4+nrQcJP1oTPDOvw00cMCnYHqP/qW/5RvJpNxbcso0aXuSwus+ML7bYiDtIQKRbiWSUTt6e3tRUVGBl19+GV9++SU0TUNGRgYKCwuRkpKCc+fO4fz586itrUVtbS0+//xzfPLJJ9i3bx9Onz6NtLQ03H///YLwBh6Tlr9b/q30OX2mKAoqKiqwZcsW1NfXIzc3F8XFxXC5XGhqasKBAwewd+9e7Nu3D93d3Vi+fDkeffRRzJs3D2azGYFAAG1tbaisrMSlS5dEvkd3dzcqKirw/vvv48iRI+ju7gYAlJSUYNGiRZgyZcqglBkYtCVqXdfh9/thsVjgcDjE+/F4HKFQSHjOoVAIjDGY+A7hxB8Qi8Xg9/thMpngcDhgNpsRi8UQj8eFRbkSML5l3mAwCK2mSymDNDgSjyetqus6onxnsbw5U9aepqtINA+FQlBVtU/sNhqN4ujRo9i6dSvefPNNeL1e2Gw25OXlITMzE06nU8wEmqYhEomgsbERra2tMJvNKC4uxtKlS/HUU08NOCYb5clDVqsV69evxy9/+UsEg0EUFxfj7rvvxsSJE3H48GHs3bsXiqIgEolgypQp2LRpE8aNGye0t9lsxsmTJ/HYY4/h5MmTcLlcSE1NRSwWQzAYhMJnJIPBgNbWVjzyyCP4+c9/jqKioj5ZeleLQSMyuIMRCoUQi8WQlpYmbnKMl4EiiwTJIuhcr1Eqn9VqRSwWE5LD4XBAVVVEo1E4nc4+VuWbIFtTIqxsceW2kT6jcBR4iErhcVgDd4zi8XifwTdQEoOH1aK8HgX9fqPRiPr6epw4cULEb1NTUwXJTCYT7HY7AoEAfD4fNGkjajweR1FREaZNm4bx48eL9n8bGJ9BFUURkmTDhg345S9/CbPZDLfbjfT0dGRkZMBgMMDhcKC0tBRFRUWYMGECioqKRFRC4Va9q6sL+/btw44dO3DkyBFhiHJycrBs2TLs3bsX77zzDtxuN37+859j9erV0DQNDoejj/G7GgwqkRmvSxaNRuFyuS7bqWQVZQ87HA7DZDIJ75nI63K5xKgfiEVGAnH7GwBEBJIy1JlEbovFIn6DqqqIx+NwOp1ikAxU7tCgpUFDg8NutyMYDMLn8yEWi8HhcMBqtSIQCCAcDoMxhtTUVHEMEYum9MzMTIwYMSLx674RTKpGZDQa0dvbi+effx4bNmxAWloaSkpKxGJGZmYmCgoKMHnyZEyYMEEYJE3TxKykcNlFiyJHjhyB2WyG0+lEZmYmCgsL8dJLL+G1115DdnY2nn76afzkJz9BT08PrHyL1TUhMfniaqHrOguHwywWizFN05jX62Ver5eFQiGmaRpTVZUFg0Gm6zpTVZX5fD7W29vbJ1GFEmkYYywSifSb7DJQxGIxFolE+r2OnKhDiEQizOfzsXA4zOLxuHifEnDoGL/f3+81Lwe5fwjhcJj5fD4Wj8eZpmkivTMSibBgMMgYTwbyer2infL5uq6z3t5eFolExHsDAbU/GAyynTt3smXLljGLxcKys7PZ7373O8b4b6X+o76MRCKiz6hNdC25T6i//H4/27hxI7vtttuY0WhkBQUF7NVXXxXHaZo2oL7sD183U1cJha9cmUwmBAIBHD16FNu2bcP//u//4oUXXsALL7yAd999F6qqCku3bds2bN68GUeOHBFWkTxiM89DuNYJg6Y9RdK4GndAyZLIVtXKV8ZsNlsfDW0ymYSWs1qtcLvd/Vr5bwKTnMwYd2IdDoeQXWTdzHyPHABYLBZYeK03hetyQpxvYB1oOwh0nqIoaGxsFE6a3+8Xx5Dco/ZRGyN865PcphhP6o9EItA0TfSXw+HA3r17UV1dDSMvBZaRkSG+g/Fo0LXc60GLWoB3iK7r6O3tRVdXF06dOoXPP/8cn332GVRVxZgxY2AymVBbW4vdu3fjiy++QHV1Ndrb2zFlyhS43W7oPPeVbhDJAybtnBgoiMzkLNG1I5EIamtrceLECZw4cQJNTU1obGxEY2Mjmpub8Ze//AWnTp3CxYsXceHCBZw/fx7V1dViVco8wJARySlFUaCqKox8Yyc5cnQt+pdurokvntD79DvoHHp/oP2jaRpOnz6Nbdu2Yffu3aipqUEwGEQsFsPEiRNRVlYmjAlFWuieyKST7xG1iRzS8+fPY+fOnfjDH/4An88Ho9EIi8WCrKwsjB07VgxkJERaBoxEE32tCAaDrKuriwWDQfbWW2+x733vewwAe/LJJ1llZSV7+umn2ZQpU5jT6WTz589nN910E7vpppvYoUOHvpYjy7jcCIfDQpYMBJqmibxcxvN6Q6GQuM6lS5fYxo0b2YIFC9ioUaNYfn4+mzRpErv11lvZbbfdxiZMmMBGjRrFSkpK2JQpU1h+fj4bMWIE++lPf8pOnTolcn8HCk3TWCAQELnIPp+PBQIBFovFhJzRNI11d3cLiSGfq6pqn10mkUiEBQKBAU3PJEt+8YtfMPCdGrR7BACbP38+e+edd5jf72eRSIR1dHT0kVq6rov+DAQCLBQK9ZE9PT09bN26dWzatGkMADMajczj8bDU1FSmKAorLi5mTz/9NGtubhbnXAsGNoSvADabDW63GyaTCW63GyNGjICJh7O6u7tRXl6O22+/Hb///e+xdOlSpKeno7e3V0gKgsazwZSEdMeBgKywPG3JFiwSieDSpUs4e/YsWltb0dDQgHPnzqGmpganTp1CXV0dWltb0djYiJqaGjQ0NKCrqwvd3d0ionClIKtGckCOkJCUIIlB1s3lcsHG83iDwSAikYiw0DT7gcuPq+2f3NxczJo1C/Pnz8eiRYuwZMkSPPDAA5g+fbqIElmtVrhcLgQCAbFWEIlEoPMkJRvPESF5CL6BNhwO46abbsLcuXOxdOlSLFq0CHPnzkVZWRnGjh0Ll8sFOy8Oc63SYlCjFjRtU4du3boVmzZtwunTp1FaWorp06ejoaEBP/rRjzBr1iy88cYbePHFF9HW1oatW7di1qxZYprRecx3oJGBRFC0weFwiCmZJEFbWxs+/fRTVFZW4uLFi3C73QD/brOU/mi1WhEMBhEMBmGxWHDXXXdh4cKFGDt2bB/N+k1gCbkWpB+JtInSQf7tjEeDaFqm6Z2IfLVTciwWw4kTJ3Dq1Cnhtxj5QlBKSgpGjx6NcePGwWw2Q9d1sePaarVCVVWhmcHvfZxXzdd1He3t7fjyyy9Fn4H7GfF4HO3t7bBarcjLy0NZWZmo/3ylfdkfBo3ITFrZo85+44038Nvf/haZmZmIRqPIz8/Hf/7nfyIjIwPNzc1Ys2YNPvjgA2RmZmLnzp0oLS1FNBr9mvaUrelAofJlcIfD0ceKERno5lDYL87TK8nBAicWWXJdCqFdjRWU48jg30e/l34nkTQuVaZn/axGMh5CI4JfLWiQEZFoqZnCkXKfgPeH7AjLIGMGvthi5DnQ0YTFKTq2p6cHNpvtmsNvgyYtFB61UHhxPQDo7u5GXV0dGhsbUVJSgieeeEJ4q36/H8ePH4eiKJg6darIsSVrFOOLJHQDadoiyUGgz2RZQpZXPobxKAXdAMatoNvtFiSGVJNYJqhs8ehmXE1Mm24mTdn0ikmLMoqUC2GVcojpfSIJvWfhkaJrAV2Hrp+amtpngYKcUhrMlyMxpI2zCl9oIRlk5ZtiE4+lCBH4qmdUyrW5HIgDNLAxmBaZoOs6VFVFOBzGs88+iw0bNqCwsBBr1qzBE088AXB9dfDgQTz44IOwWq1YtWqVWF4lDUlEpB8f4+WfyFJB2t1A59BNpukakvYia6Jxb5+u6/f7cfbsWdTV1QESwZ1OpwglmXiCjcJzRW6++WZMmjQJAwFZPbJQcb507/f74ff7hT9A30PnfNvtkY8dLPR3TaWfwovfBvmcy51P79MAIsNC/SCfT+2ie0iDBH8NIoMTtbKyEv/93/+NTz75BCtWrMA//dM/Ye7cuVBVFfX19fj000/xzDPPoKioCD/72c+wZMkSke6XiMSG6zzEZ+FV29GP/GD9TLsqL/+k8P1wsVgMVVVVeP311/HHP/4RdrsdPp8PwWAQaWlpIsciEonA7/fDaDTi5ptvxk9/+lP86Ec/klo4MOhcb166dAlNTU1oa2uD3+8X8VeacciJ+ivcohsKsVgMKSkpmD17NrKysoQOJyIrfICToUq81xhsIpOm8/l8+P3vf4+XX34ZFy5cwIYNG7B06VIhH/bs2YNNmzbh/fffx+OPP45///d/R2ZmJsDJZuVr/5Q5ZbVaUVBQ0GdLDFk3A99vpnEnjoiNhO1DBi4PqGNId3Z3d6O2thbNzc0w83oQUZ65RZLFxmuiadwhKSwsRGFh4demym8Ck6SFkeceB4PBPhEbeRDiGpy47xoYj687nU44HA4R0WFSfJpmMjqe7ilhUIms8fyDS5cu4b/+67+wefNmWCwWbN++XWxdNxgMeP/997Fx40acP38ea9euxerVq9Ha2gqTyST2m9XU1ODgwYOoqKiA2WzGxIkTMWnSJBQXFyMvL0+EpciZg7QTwcy9b3CHQ15NTJQfdNxAQDqOdOOVgPEZgtr3TdblbxURvhmA9Dokn4msMjjP6N5Rvw2aswcpD9nn8+HChQswGo0YP368qAgZ5Dt1I7wiI+0J6+3txZ49e9DQ0ACLxYK6ujq89tpreOaZZ0RC9gsvvIA1a9bgzTffxLlz5xDjy6HBYBAOhwNutxtWqxV+vx+hUEi0iYgiT03gs0ckEoHKN20yxvrEScGtfog/x4N0ORKWjQcCs1TilaD0k9dMfsAg2pjvBGw8+V/uH3lWIlKTRZYxqEvU4J5ndXU1Xn31VTidTixbtkxUUDdwvbdlyxbs2LEDmZmZMBgMaGtrg6qqYo/Yr371K1RUVKCwsBA/+9nPcOedd8Jms6G6ulo8U2Pq1Klwu90wco+aQI6ZPB3RiwhC0zhZbpIc9Dd1GFlP+Zo0CDHAqZ8IK1sakj56Pxl61Fd/Cy9wg0P9AMkJJOJS3yX+K/pL/DVICAQC6OjoQDgcRmFhIe6++24RyiENSk8kqq2tRVNTE2KxGMaNG4eMjAx0dnZi3759UBQFP/jBD/Dwww/jiSeewEMPPYSysjL09vaisrJS7DQgPR2XUj0tFguYlIhCTmJ/pKPOVLhuJgIRqEPpdTmLcCX4pu+XQW3t7/jhDDIgiS9IfZdoEAiDTuRIJAKz2YwZM2Zgzpw5mDZtmthgCE7m/Px8jB49Gi0tLcjKysLDDz+M73//+3A4HLh06RKsVitmzpyJhQsXwsijDjNmzMCqVaswY8YMBINBtLa29pEBcb7/TbakUf5QRU1K5idZoPPIgexoxXk2F+lpcD0cCoWEfnPy59hdjbSQYeCxYmqPrNXlwWWQ4s3D9UW/k/oz0RJfST8PurQw8BJMRUVFmD59utjVS2SwWq0YOXIkpk6dijlz5mD27NnIycmBw+FAa2srysvLsX37dsyePRsrV64UDqSVpxNWVlbiyy+/RGFhIcaMGYOUlBQxTRs4UWO8OjrJAgPPX1B55XXqQBN/2KJBGt2aFP4y8AiDbKmvtGMTwXjUoj8ZISPR4suzwXB/JRJcJjq9WMJsSei/N68BLpcL48ePx7x58zBhwgSwhBQ/xhgmTpyIlStX4h//8R9RVlYmzq2vr0dlZaV4bACBrGxaWhqsfENjdXU1GhsbxTFESnk6Im0sj3RqB2lr+XPqNDqOLEXiNeh3XA36O4+umXjd/o69HkicGQYb9Dtlwvb3+iYMaqsoLEJfGufb+41GI1wuFzwej9CyjDtOZr4/DADq6upw9OjRPtcki5kYRqutrUVjY6OwsOSQUSyb1u5lC2i32+HxeESwXZc2mBKJzVKRPyJ1jCf70MCQr3ulUPgyrVVadobk9MX4MjWkmcDIIy3X+5VIosTPr/VFvxPfMKgJlyP2oBKZGkagaZm+1CDFeBVee4HxKReSo0jnyjBwssZ5sZHU1FSkp6fDxve+RXmKJJ1HUoPa09+PV7iDl/hdMugY+Xco/TgbVwu6lixzEtt5paCZpD8CfBNoQJMvASn+Dl7v4r333sPzzz+PvXv39jmOcdlIg/BaIRN1IP0wOHeDI/GLlX4STPqbyhM7hj6ToUjWEQCys7PFSiH6WeCQr3k5UPsS250IGhAykb/tnCsFEZms0rVc92qJzBKK59DsE4lEcPToUXz44Yf4+OOP8c4772DTpk3Ytm0bmpqaRGydjIs8Sw20DTKupn8HlchXA4uUL+F0OsVu4EQi6rzqUDQahcPhQE5OjpAkZp6NZuE5FVdzM4cTBkwCaZoHJ6bRaEQ4HMZvfvMbbNq0CV1dXTAajdi6dSt+8pOfYPfu3ejo6IDCJRPjq6yMSwOSmUOFQY9aXCl0Xe/zzGTwFcH29nacPXsWeXl5mDJlighPRSIRfPTRRygvL4fJZMI//MM/oKSkRJAXUmSArplo1Yc7iDjyzHE5MB5npxmBZjuNP4ekpaUFZ8+exbhx4zBv3jzMmzcPc+bMgcViwcWLF9HZ2YmsrCwUFRUJPU+zCvlBshz7a+O63mnqTJqSJkyYgHnz5iE3Nxd1dXXYs2ePKCbt9/vxySefoK6uDjk5OZg4caIodk3OI12TJMPfOr7NIlL/x3karCKFtzo7OxEKhbBixQosWbIEs2fPxty5c/Hwww9j+vTpqKysxIkTJwBJosmGY6gITLhuRDYYDOIZycFgEKFQCDk5OZg3bx4mTZqEixcvYteuXWhqakIwGERjYyMqKyvh8/mQm5srapxF+HOUo9EoFO5A0mJGEl+HLLssFgs0noVHfWfl27pcLhfy8/Nh4LvNvV4vwH2TkpIShEIh9PT0iOuSw814Ue+Bbjy4Vgxq9ttAQQ4aWVW73Q5VVbFjxw5s2bIFVVVVyM/PR2ZmJlwuFzRNw/jx43Hbbbdh1qxZYvEjJj1zWbby17r69l0DzWyXkxaJs5bCd/OQ34EEQsq62chXWKuqqlBeXo6zZ8/i3nvvxfLlywEe5aB7SOGzoZQW143IjHvKcueSJfV6vdi9ezd27dqF1tZWKIqCgoIC3HfffbjllluQnp7eJ7xGU6NRej4Gu8o9dd9lJBJZ/lvuZ/qXog4GHhal6IMsM1RV7eNIf/bZZ6iqqkJpaSmKi4sxatQoMK6vqc9Jrgxl/183IhMCgQAikQjS0tKEriWS04s6I86TggwGA7xeLywWi6jFRqSmnzNUHXgjoT8iy2DSUnAsFkNHRwecTqfYmUMhOLPZjO7ubvh8PmRkZMDhcAjLvH//fvz5z3/GsmXL+jwrm5w99BMKHQpcdyKTp0wLGyrfZm6TNoT2h0AgABPfoAl+k+QOlB2PvxV8260kIoOTjVZKLTyJiqAoCsK8mr3T6RRRJfDFkZ6eHhQUFMAuPXaMBo8qVVAaSlxXIut8aRiSNqOwDa0AUgeTdCDCgnc4vXQpdilbh78lfNutvJylRkIduSjfkkUEZv2U6KX35TCbrusIhUIw8z13Q4nrZraoE4iAXq8XmqYhJSVF5EnIo5s6kKw2yQiy6ArPk5A7NYm+uBzR5dlMvi/gTpzP5+tT2JAQCATQ2dmJCK+ApEg53UON62qRyWEDL1xCkQdwa61zzzfxHMaT5ekGkHNCoJ/0TRZoOEMmpmxVa2pqsGPHDtTX10PXdaSkpODOO+/ErFmzYLVaYefPOIlGo7BYLOju7sa7776LzMxMzJgxQ1RrivBdMlGeEDZy5EhRD5u+VxnEfJQrwXUlchKDCyIQEZmkWXt7O06fPo0vvvgCW7ZsEY/IaG5uxrJly/Dkk0+KaBAhGo3i+PHj+NWvfoXRo0dj/vz5UHhphGg0CpvNhtGjR2Ps2LEYMWIEnE4nzGYzNJ5akCRyElcFJulYeYby+/1Yt24dPvzwQ1y8eBETJkzAfffdh8zMTKxevRpWqxWPPPII1qxZ06fqfUNDA/bv34+3334bPp8PHo8HKq8L4nQ6MXnyZNx7772488474fF4xKBJLEE2VEgSeZhAJjL5E2fPnsXOnTuxf/9+fPXVV/B4PPjNb36DxYsXo7W1FUuXLsXZs2cxe/ZsvPfee8jOzhakDQQCuHDhAk6ePIk4f+SEpmlQeYGbESNGoKCgAHl5eULmRaNRxPgjK+QcmCEBS2LYQK6t3NbWxl588UU2bdo0lpuby0pLS9natWtFDeVdu3axiRMnMgBs2rRpok5xW1tbnzrIoVBI/H05UK3kcDjMVFVl0Wh0QLWaBwNDJ2KS+KuDLLHP58Mrr7wi8oabmpowc+ZMrF27FgaDAdu3b8dzzz2HhoYG5OTk4PbbbxdSQH6CKeMRDMooDAaDfTb8avyZgWSlaQWQwnBDGTlKEnmYgEgHTriDBw/i8OHDUFUV3//+9zF37lxomoZXXnkFL730Eo4fPw63241FixbhwQcfFOFMi8WCKN99TrkTRl7ii0JrGt+aJYfpmLTYQnHkoYwaJYk8TECkifDnotTX10Pl5RFycnLQ3d2N7du3Y+PGjTh27Bjy8vKwcOFCrFy5ErNmzYKZP5jTwHecU3yerLzOk7AMPLeFwqAGaXMuRUsUHtMfSiInnb1hhuPHj+Pdd9/F66+/jvb2dpj4PseMjAx4PB60t7dj5syZePDBB7Fw4UJkZ2dD4QtIirRKSmSlCIgiFX6k9/uL35MModXVoSJzksjDDLt378bvfvc77N69G5FIBGPGjEFBQQFKS0tRUFAAXdcxbtw43HrrrcjKygJ4zJi0bSKhKfdFzmkhytDxkHbkJOPISQwKtm3bhv/5n/9BRUUFYrEYbrnlFqxatQpLly7F2LFjxXGMMfzlL3+B2WxGZmYm3G7316wtkx7zK6cJgJOYrDa4LqbPh8oKyxi6IZPEkMDAqy0ZeYKVz+dDVlbW14qoHzt2DPfddx/Wr1+PON8qZpDKNZBDZ7PZoGkafPwZ2InfY7PZREH0OM9DJv08lEgSeZiBdCmRrqurC1u2bMHrr7+Ojz/+GMeOHcOrr76KtWvX4syZM+js7ERXV5eQCJr0IEpKwLLwne79SQWyvmTF+9POQ4Hrtos6ib8OvF4v2tvbUV9fj97eXqiqKqIYzc3NaGhowNatW3Ho0CHceuutuOeeezBp0iSkpaVBUZQ+zhppXqP0MJzLgTTx9SAxkhp5+EDTNHR3d8PpdOLixYt45plnsHv3blF+1+FwwGQyIRQKwePx4Pbbb8fTTz+N0tJSsesmwgufu1wuIU0oJJeYhXijIUnkYQJd1xEOh0VORGVlJcrLy1FeXo6jR4+ip6cHLpcLy5cvx4wZM1BSUoLbb79dRCOivGSWwguuKDwuHOEPFPo2i3y9kSTyMAPdTkVR0NLSggMHDuCjjz5CXV0d8vLysHbtWpSWlorjdamIoonXa5Y/o90iSSInMWSg8FmcFz038QKN4XAYOt+k4OQPq6TbTv/Kixe6VAnzemnegSJJ5GEGsq5RXquiP21LMWCKSshE1fjOdUM/S89yHPlGw9fjKUl8p6HwfGTKZtM0DZFIRDwDW5YekKy4vEqXeAyR+0a2eUmLPIxAzhrFe2lvHTmAtMBB0oI28mr8gekW6bnWTCpRSy+y4DcikkQeJmA8YcfIi6uT9SXikUSI8fJiFl73jVIxSU/LJCc5cT3jw1eKpLQYhiANrPAcCbLU9LfGV/2M/CFD9KgJIjE5ezQQbmQCE5IWeRhBJqGRP09F4ytzsrWlWx7nBb3JiSMdLDt1Cs+h0HkprRuV1EkiDzMQUQ08QZ6ITLpZPk7nORX0GTl7icfKg+NGRZLISQwLJDVyEsMCSSInMSyQJHISwwJJIicxLPD/ACFFkpc1j9iTAAAAAElFTkSuQmCC\" style=\"width: 122px; height: 72.6517px;\" width=\"122\" height=\"72.6517\"\u003e\u003c/p\u003e\u003cp\u003ewhere Z is 1.96 at 95% Confidence interval, \u003cem\u003ep\u003c/em\u003e is the expected AMR prevalence taken to be 50%, \u003cem\u003eq\u003c/em\u003e is 1minus \u003cem\u003ep\u003c/em\u003e and \u003cem\u003ee\u003c/em\u003e is the margin of error, which was taken to be 11%. Given the limited studies on antimicrobial resistance spillover from intensive pig farming in Kenya, this study aims to provide foundational insights within this context allowing for an initial assessment of AMR patterns in environmental samples, in order to generate valuable data to inform more precise and extensive research in the future.\u003c/p\u003e\u003cp\u003eFarmers were fully informed on the essence of the study to improve food safety and their role in data provision to improve antimicrobial stewardship. Those that were willing to participate in the study first signed a consent form before sampling commenced. Sampling was conducted between February and April 2022 and farms were identified using alphabetical codes. A total of 80 samples were collected in triplicates from 16 intensive pig farms. Five samples were collected from each farm. Samples included upstream water and sediment samples, downstream water and sediment samples, and two bootsock samples that were pooled into one.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample collection\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eWater and soil samples collection\u003c/h2\u003e\u003cp\u003eThese were collected aseptically upstream and downstream in triplicates from the piggeries. Fifty milliliters of water and a scoop of sediment was collected into sterile centrifuge tubes at two locations along the main effluent exiting the piggery. The samples at the point closest to the shelter were designated upstream water and sediment samples while the corresponding downstream samples were collected at the furthest possible location. Each sample was collected in triplicates. Following collection, the tubes were securely capped, wiped externally with 70% ethanol and appropriately labeled. Subsequently, the samples were stored in a well-insulated cool box with icepacks.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eBoot socks sample collection\u003c/h3\u003e\n\u003cp\u003eTwo boot sock samples were collected from the windward direction of the piggeries and pooled. The boot socks were soaked beforehand in normal saline while being consistently hand palpated. Freshly gloved hands were used to put on sterile plastic shoe covers over the gumboots, followed by wearing the boot socks over the shoe covers. The individual conducting the sampling proceeded alongside the pig shelter, following the typical direction of the prevailing wind. Using gloved sterile hands, the boot socks were removed and placed into pre-dispensed Tryptic Soy Broth contained within a zip-lock sampling bag. After sealing the bag, it was gently palpated until adequately soaked in the broth, then appropriately labeled and positioned upright on ice within the cool box. All samples were promptly transported to the laboratory, where culturing began within 24 hours of collection\u003c/p\u003e\n\u003ch3\u003eLaboratory methods\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCulturing of the samples\u003c/h2\u003e\u003cp\u003eThis was carried out at the KALRO - Veterinary Science Research Institute (VSRI). The water samples were vortexed for 30 seconds and were then diluted in Normal saline at a ratio of 1:10. Approximately 5g of sediment was diluted in 10ml of Normal Saline. The boot sock samples were palpated for a minute after which 1ml was taken into a sterile tube. For each sample, a loopful was streaked on MacConkey Agar (Himedia, Mumbai, India). Culturing was performed in duplicates and the cultures incubated overnight at 37\u003csup\u003e0\u003c/sup\u003eC. After 18-24hours, colony morphology was observed followed by Catalase, Oxidase and Indole tests and subsequently Gram staining and microscopic observation. This was carried out for the preliminary identification of bacteria showing pink colonies surrounded by a red region of precipitated bile salts on MacConkey agar and appearing as gram negative rods under the microscope. Matrix assisted laser desorption/ionization time-of flight mass spectroscopy (MALDI-TOF MS) was used to confirm the identity of the isolates which were then preserved as 10% glycerol stocks at -20\u003csup\u003e0\u003c/sup\u003e C for further analysis (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAntibiotic Susceptibility Testing (AST)\u003c/h3\u003e\n\u003cp\u003eAntibiotic susceptibility testing was performed using the Kirby\u0026ndash;Bauer disk diffusion method as recommended by the European Committee on Antimicrobial Susceptibility Testing (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), on Mueller Hinton Agar (Himedia, Mumbai, India) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Seven antibiotics were tested (Basingstoke, Hampshire, United Kingdom) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). \u003cem\u003eE. coli\u003c/em\u003e ATCC\u0026reg; 25922 was used for quality control during the antibiotic sensitivity testing. The diameters of the inhibition zones were measured and interpreted according to the EUCAST, 2024 breakpoints.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCriteria for interpretation of the diameter of the zones of inhibition of \u003cem\u003eE. coli.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAntibiotic Class\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAntibiotic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePotency (\u0026micro;g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDisc abbreviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eInterpretation (Zone in mm)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSusceptible (S) \u0026ge;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIntermediate (I)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eResistant \u0026lt;(R)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePenicillins\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAmpicillin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAMP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAmoxicillin-clavulanic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u0026thinsp;\u0026minus;\u0026thinsp;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAminoglycosides\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGentamicin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGEN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSulfonamides\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrimethoprim- Sulfamethoxazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.25\u0026ndash;23.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSXT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11\u0026ndash;13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChloramphenicol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChloramphenicol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFluoroquinolones\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEnrofloxacin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCephalosporins\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCefotaxime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCTX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17\u0026ndash;19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eDATA ANALYSIS\u003c/h2\u003e\u003cp\u003eAll the data was recorded using Microsoft Excel. The zones of inhibition obtained after conducting antibiotic sensitivity testing was interpreted according to EUCAST (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Multiple antibiotic resistance (MAR) index was calculated as follows: A/B; where \u0026lsquo;A\u0026rsquo; was taken as the number of antibiotics an isolate was resistant to, and \u0026lsquo;B\u0026rsquo; was taken as the total number of antibiotics tested. Multidrug resistance (MDR) patterns were determined from the isolates exhibiting resistance to at least one antibiotic agent in different antibiotic classes (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The data was presented by the aid of Microsoft Excel and Graphpad Prism software.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 112 \u003cem\u003eE. coli\u003c/em\u003e isolates were identified from the five sample types: 10.7% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12) were isolated from bootsock samples, 38% (n\u0026thinsp;=\u0026thinsp;46) were isolated from water samples where 19.6% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;46) were from upstream water samples, 21.4% (n\u0026thinsp;=\u0026thinsp;46) from downstream water samples, 48.3% of the isolates were isolated from sediment samples where 31.3% (n\u0026thinsp;=\u0026thinsp;54) were from upstream sediment samples and 17% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;54) from downstream sediment samples. These isolates were tested for their susceptibility to seven antibiotics (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePercentages of \u003cem\u003eE. coli\u003c/em\u003e isolates resistant to different antibiotic classes classified by sample type.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntibiotic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall resistance% (n\u0026thinsp;=\u0026thinsp;112)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBootsocks samples % (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWater samples % (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSediment samples % (n\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAMP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e14.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e30.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSXT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e25.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e24.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCTX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe isolates obtained from boot sock samples had the highest resistance against SXT at 66.7%. Isolates derived from water samples were most resistant to the penicillins at 28.3% each while 29.6% of the sediment isolates were resistant to AMC (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eE. coli\u003c/em\u003e strains were found to be sensitive to the Cephalosporin, CTX, with a resistance of only 4.5% and intermediate resistance of 2.7% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Resistance to ENR and C was found to be 8.9% and 11.6% respectfully. The highest resistance rates were observed for the Penicillins tested, AMC at 30.4% followed by AMP recorded to be 26.8%.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAntibiograms of \u003cem\u003eE. coli\u003c/em\u003e isolates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePattern Number\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAntibiogram\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of Antibiotics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentage of The Isolates (n)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo resistance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.4 (52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.4(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSXT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.5(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.6(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-AMC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.5(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSXT-ENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMC-CTX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.8(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-SXT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.8(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCN-SXT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-ENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCN-ENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-CTX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-CN-ENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-AMC-SXT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.5(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-SXT-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-AMC-SXT-ENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.8(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-AMC-SXT-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.7(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-AMC-SXT-CTX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-CN-AMC-SXT-ENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-AMC-SXT-C-ENR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.8(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-CN-AMC-SXT-C-CTX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.9(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMP-CN-AMC-SXT-C-ENR-CTX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.8(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn this study, 46.4% of the isolates were susceptible to all the antimicrobials tested, while 1.8% were resistant to all the antibiotics tested. Twenty-four patterns of resistance to the tested antibiotics (antibiograms) were recorded (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The most dominant resistance was against AMP, as registered in 15 out of 24 patterns overally. Interestingly, only 0.9% of the isolates were resistant to AMP alone. The isolates exhibited a total of 18 patterns that were designated as multidrug-resistant (MDR) since they exhibited resistance to more than one antibiotic agent in different antibiotic classes (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Among the isolates, 25.9% of the \u003cem\u003eE. coli\u003c/em\u003e isolates were shown to be MDR. AMP-AMC and AMP-AMC-SXT were the most common patterns of resistance at 4.5% each. Rates of intermediate resistance were low and hence were classified as resistant (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe highest calculated MAR was 1 exhibited by 1.8% of the isolates. The isolates had varied MAR indices but the average index was 0.33 as (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe present study sought to identify antibiotic resistance in and around intensive pig farms in Kenya by isolating \u003cem\u003eE. coli\u003c/em\u003e and characterizing their antibiotic resistance profiles. Many similar studies conducted in other countries have reported varied percentages of resistance in \u003cem\u003eE. coli\u003c/em\u003e against the antibiotics tested attributable to the antibiotics in use and the regulations in the country. The resistance recorded in the current study against Ampicillin and Amoxicillin clavulanic acid and chloramphenicol was 57.1% and 11.6%. This is lower than the resistance observed in a study conducted in Thailand on medium sized pig farms (500\u0026ndash;5000 swine population) and large scale pig farms (more than 5000), which reported 98.6% resistance to ampicillin and amoxicillin and 75% resistance to Chloramphenicol on medium sized pig farms. A resistance of 96.3% was recorded against Ampicillin and amoxicillin from pig farming environments on large scale pig farms. This may be due to the much higher number of pig populations in the sampled farms as compared to the farms in our study. Resistance against ampicillin as detected in waste water in the present study was 28.3%, which was also lower than that detected in the waste water from the medium-sized farms which had resistance rates of 91.7% against Ampicillin and the antibiotic resistance in the sludge (sediments) had an even higher resistance of up to 100% against ampicillin and amoxicillin as compared to the current study that recorded an overall combined resistance against ampicillin and amoxicillin clavulanic acid at 50% in the sediment samples (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Another study also observed high resistance rates to Ampicillin and Amoxicillin- clavulanic acid in pig farming environments (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMultidrug resistance was observed to be 25.9% in the present study as compared to a South African study which recorded a high percentage of resistance in pig farm isolates and the highest prevalence of MDR was found on the pig farm at 74.6%. Similar to our study, the most common MDR pattern included AMP-SXT-CHL, found in 4.7% of the isolates similar to what is reported in the current study at 4.5% (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In the study, similar to the current one, \u003cem\u003eE. coli\u003c/em\u003e showed the highest resistance to Chloramphenicol, Trimethoprim-sulfamethoxazole and ampicillin. This is because these antibiotics have been used for a long time in food producing animals. In their 2019 Annual Report on Antimicrobial Agents Intended for Use in Animals, WOAH documented that the largest amount of antibiotics used for animal production were tetracyclines, macrolides and ampicillin (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA surveillance conducted in China also investigated the trends in antibiotic resistance in \u003cem\u003eE. coli\u003c/em\u003e in pig farming reported a high resistance rate to ampicillin and sulfamethoxazole recorded at, 81.44% and 88.36% respectively as related to the current study where resistance rates were observed to be 26.8% and 25.9% for ampicillin and Trimethoprim-sulfamethoxazole respectively. This could be due to the fact that in China, the use of antibiotics for growth promotion and treatment is largely unregulated (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough the use of chloramphenicol in animal-producing animals was banned in Kenya, \u003cem\u003eE. coli\u003c/em\u003e isolates resistant to chloramphenicol were recovered from pig farms at a rate of 11.6%. Another study recorded a much higher percentage of resistance to chloramphenicol (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This is possibly attributed to horizontal gene transfer of chloramphenicol resistance genes and co-selection of resistance due to the use of other antibiotics (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). For instance, reports have it that the resistance to tetracycline, sulfamethoxazole and kanamycin, which are accepted for animal use is often transferred together with chloramphenicol resistance (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCephalosporins and fluoroquinolones exhibited a relatively low resistance rate in comparison to other antibiotics in this study. However, they still need monitoring due to their clinical importance since the World Health Organization classified both as critically important antibiotics (CIAs) for human medicine (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The increasing occurrence of MDR \u003cem\u003eE. coli\u003c/em\u003e poses a public health challenge since \u003cem\u003eE. coli\u003c/em\u003e occupies multiple niches, in animals, the environment and humans and, can acquire or transmit antimicrobial resistance genes both vertically and horizontally. The prevalent MDR pattern reported in the current study included resistance to antibiotics commonly used for treating diseases in human and veterinary medicine indicating that there is a possibility of the resistance genes being transmitted to other pigs, the environment and consequently to humans.\u003c/p\u003e\u003cp\u003eThe multiple antibiotic resistance (MAR) index is commonly applied in the determination of health risk associated with the dissemination of resistance in any given location (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). A MAR index higher than 0.2 suggests that the bacteria under study were exposed to high antibiotic use environments (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The current study recorded a mean MAR index of 0.33 in the pig farming environments confirming the high antibiotic used in pig rearing in Kenya and the high selective pressure created in these environments.\u003c/p\u003e\u003cp\u003eThe \u003cem\u003eE. coli\u003c/em\u003e isolates in the current study were highly sensitive to cephalosporins and fluoroquinolones, with resistance rates of 7.1% and 8.9%. Such results were also reported at about 4% resistance to fluoroquinolones in one study (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This serves to caution farmers that increased use of drugs in these classes should be regulated to minimize the risk of development of resistance to them.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eTo the best of our knowledge, this study is among the first in Kenya to investigate antibiotic resistance in \u003cem\u003eE. coli\u003c/em\u003e in intensive pig farming environments. The widespread use of antibiotics in food producing animals, particularly in pig rearing, is intricately linked to the development and dissemination of the antibiotic resistance crisis. The high antibiotic use in swine farming in Kenya and worldwide promotes the proliferation of resistant bacteria in pigs that spill over into the pig rearing environments, posing a significant public health threat. One notable route through which humans can be affected by these resistant bacteria is through environmental contamination, greatly exacerbating the global public health challenge. \u003cem\u003eE. coli\u003c/em\u003e has been documented to have a greater capacity to accumulate antibiotic resistant genes, especially through horizontal gene transfer. \u003cem\u003eE. coli\u003c/em\u003e might colonize the human intestine and act as reservoirs or opportunistic pathogens at any time later in life. Our findings present that \u003cem\u003eE. coli\u003c/em\u003e around intensive pig farms are relatively resistant towards critically important antibiotics leading to serious concerns to public health.\u003c/p\u003e\u003cp\u003eTo meet the increasing demand for pork, the number, size and population of pigs in pig farms will have to increase tremendously. This implies that even greater amounts of antibiotics will be applied to support the increase in swine production, increasing the threat even further. Enhanced monitoring and surveillance in pig farms is essential to gain a more comprehensive understanding of the situation. This data will offer extensive insights to deepen the understanding of antibiotic resistance in pig farming, potentially informing the formulation and improvement of governmental policies aimed at mitigating AMR within the Kenyan pig industry.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAMR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAntimicrobial resistance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMALDITOF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMS-Matrix Assisted Laser Desorption/Ionization Time-of Flight Mass Spectroscopy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the World Animal Protection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChristine Inguyesi\u003csup\u003ea\u003c/sup\u003e*, Moses Olum\u003csup\u003ea\u003c/sup\u003e,\u003csup\u003e\u0026nbsp;\u003c/sup\u003ePeter Ndirangu\u003csup\u003ea\u003c/sup\u003e, Nathan Langat\u003csup\u003ea\u003c/sup\u003e,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAscah Jesang\u003csup\u003ea\u003c/sup\u003e, Ednah Masila\u003csup\u003ea\u003c/sup\u003e, Esther Wachuka\u003csup\u003ea\u003c/sup\u003e, Ruth Onywera\u003csup\u003ea\u003c/sup\u003e,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDishon Muloi\u003csup\u003eb\u003c/sup\u003e, Linet Ochieng\u003csup\u003eb\u003c/sup\u003e, Victor\u003csup\u003e\u0026nbsp;\u003c/sup\u003eYamo\u003csup\u003ec\u003c/sup\u003e, Kelvin Momanyi\u003csup\u003ec\u003c/sup\u003e, Patrick Muinde\u003csup\u003ec\u003c/sup\u003e, Monicah Maichomo\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eCI participated in the sampling and laboratory analysis, data analysis and interpretation and manuscript writing. MO participated in project conceptualization, sampling, data analysis and interpretation, manuscript writing, PN participated in data analysis and interpretation and manuscript writing, AJ participated in sampling, and manuscript writing, EM participated in sampling, laboratory analysis, data analysis and manuscript writing. EW participated in laboratory analysis and manuscript writing. RO participated in data analysis and manuscript writing. DM and LO participated in laboratory analysis. VY, KM and PM participated in project conceptualization and sampling. MM participated in sampling and manuscript writing. \u0026nbsp;All authors read and approved the final manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the contribution of the staff in the Bacteriology Division of the Veterinary Science Research Institute.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKatushabe P, Byamukama B, Byaruhanga J. Burden of Multidrug-Resistant Escherichia coli in Pigs Slaughtered in Uganda and Its Implication on Veterinary Public Health. Open Journal of Veterinary Medicine. 2022;12(12):187\u0026ndash;200. \u003c/li\u003e\n\u003cli\u003eRobinson TP, Bu DP, Carrique-Mas J, F\u0026egrave;vre EM, Gilbert M, Grace D, et al. Antibiotic resistance: mitigation opportunities in livestock sector development. 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Microorganisms. 2022 Jul 23;10(8):1485.\u003c/li\u003e\n\u003cli\u003eAbdalla SE, Abia ALK, Amoako DG, Perrett K, Bester LA, Essack SY. From Farm-to-Fork: E. Coli from an Intensive Pig Production System in South Africa Shows High Resistance to Critically Important Antibiotics for Human and Animal Use. Antibiotics. 2021 Feb 10;10(2):178.\u003c/li\u003e\n\u003cli\u003eG\u0026oacute;chez D, Raicek M, Pinto Ferreira J, Jeannin M, Moulin G, Erlacher-Vindel E. OIE Annual Report on Antimicrobial Agents Intended for Use in Animals: Methods Used. Frontiers in Veterinary Science. 2019 Sep 25;6.\u003c/li\u003e\n\u003cli\u003eZhang P, Shen Z, Zhang C, Song L, Wang B, Shang J, et al. Surveillance of antimicrobial resistance among Escherichia coli from chicken and swine, China, 2008\u0026ndash;2015. Veterinary Microbiology. 2017 May;203:49\u0026ndash;55.\u003c/li\u003e\n\u003cli\u003eZhu YG, Johnson TA, Su JQ, Qiao M, Guo GX, Stedtfeld RD, et al. Diverse and abundant antibiotic resistance genes in Chinese swine farms. Proceedings of the National Academy of Sciences. 2013 Feb 26;110(9):3435\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eDirector of Veterinary Services (Kenya). Prohibition of chloramphenicol, nitrofurans (Cap. 364). L.N. 25/2010; Animal Diseases Act. Notice under section 8. Nairobi: Kenya Gazette; 2010.\u003c/li\u003e\n\u003cli\u003eLay KK, Koowattananukul C, Chansong N, Chuanchuen R. Antimicrobial Resistance, Virulence, and Phylogenetic Characteristics of \u003cem\u003eEscherichia coli\u003c/em\u003e Isolates from Clinically Healthy Swine. Foodborne Pathogens and Disease. 2012 Nov;9(11):992\u0026ndash;1001.\u003c/li\u003e\n\u003cli\u003eBischoff KM, White DG, Hume ME, Poole TL, Nisbet DJ. The chloramphenicol resistance gene \u003cem\u003ecmlA\u003c/em\u003e is disseminated on transferable plasmids that confer multiple-drug resistance in swine \u003cem\u003eEscherichia coli\u003c/em\u003e. FEMS Microbiology Letters. 2005 Feb;243(1):285\u0026ndash;91.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. \u003cem\u003eWHO List of Critically Important Antimicrobials for Human Medicine (WHO CIA List)\u003c/em\u003e World Health Organization; Geneva, Swizerland: 2019.\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":"one-health-outlook","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oneh","sideBox":"Learn more about [One Health Outlook](https://onehealthoutlook.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/oneh/default.aspx","title":"One Health Outlook","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"AMR, Antibiotics, E. coli, Environment, Intensive, Pig farming","lastPublishedDoi":"10.21203/rs.3.rs-7428840/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7428840/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAntibiotic resistance is a major public health threat globally, rendering the treatment of human and animal infections difficult, longer and expensive. This study was carried out to determine the antibiotic resistance profiles of \u003cem\u003eEscherichia coli\u003c/em\u003e isolated from pig farming environments in selected pig farms around Kenya. Waste water and the associated sludge together with ground surface boot sock samples were collected from preselected intensive pig farms. The samples were cultured, \u003cem\u003eE. coli\u003c/em\u003e isolates identified using standard microbiological procedures and confirmed by Matrix Assisted Laser Desorption/Ionization Time-of Flight Mass Spectroscopy (MALDI-TOF MS). Antibiotic susceptibility testing was performed using the Kirby\u0026ndash;Bauer disc diffusion method against Ampicillin, Amoxicillin-clavulanic acid, Gentamicin, Trimethoprim-Sulfamethoxazole, Chloramphenicol, Enrofloxacin and Cefotaxime. The highest resistance was recorded against Amoxicillin-clavulanic acid at 30.4% and the lowest was recorded for Cefotaxime at 7.1%. Multidrug resistance was observed for 25.9% of the isolates. The isolates had varied Multidrug Antibiotic Resistance (MAR) indices, but the average index was 0.33. The results suggest that there is high antibiotic exposure in the intensive pig farms that increase the selection pressure leading to development and dissemination of antibiotic-resistant \u003cem\u003eE. coli\u003c/em\u003e among pig populations, to humans and potentially into the environment further compounding the public health threat.\u003c/p\u003e","manuscriptTitle":"Multidrug Antibiotic Resistance Index and Antimicrobial Resistance Patterns of Escherichia coli in Intensive Pig Farms in Kenya","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 11:35:28","doi":"10.21203/rs.3.rs-7428840/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-06T07:00:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-05T16:23:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-04T13:51:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-02T20:09:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303996909420129605373754604058704629910","date":"2025-09-01T18:07:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-01T05:28:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"262430413335667396380777494767154441093","date":"2025-08-31T06:04:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259031606818449478276430091682941858374","date":"2025-08-29T12:07:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318880696705973110762048747667555561059","date":"2025-08-29T09:38:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157857869082827917142586603761806913504","date":"2025-08-29T04:38:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247027113517664896196798487603182268134","date":"2025-08-28T14:33:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263455639470721549993605613044653038083","date":"2025-08-28T08:33:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"239713846378482126864978606472486806159","date":"2025-08-27T15:08:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-27T09:34:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-27T09:28:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-26T05:58:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"One Health Outlook","date":"2025-08-21T18:54:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"one-health-outlook","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"oneh","sideBox":"Learn more about [One Health Outlook](https://onehealthoutlook.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/oneh/default.aspx","title":"One Health Outlook","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f613903e-f8a0-4ff9-9abc-231ea413d2c4","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:11:10+00:00","versionOfRecord":{"articleIdentity":"rs-7428840","link":"https://doi.org/10.1186/s42522-025-00177-1","journal":{"identity":"one-health-outlook","isVorOnly":false,"title":"One Health Outlook"},"publishedOn":"2025-11-10 15:57:33","publishedOnDateReadable":"November 10th, 2025"},"versionCreatedAt":"2025-09-03 11:35:28","video":"","vorDoi":"10.1186/s42522-025-00177-1","vorDoiUrl":"https://doi.org/10.1186/s42522-025-00177-1","workflowStages":[]},"version":"v1","identity":"rs-7428840","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7428840","identity":"rs-7428840","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}