Detection and Antimicrobial Resistance Profile of Salmonella Isolated From Raw Cow Milk and Its Products in Bishoftu Town, Central Ethiopia: Implication for Public Health

Detection and Antimicrobial Resistance Profile of Salmonella Isolated From Raw Cow Milk and Its Products in Bishoftu Town, Central Ethiopia: Implication for Public Health | 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 Detection and Antimicrobial Resistance Profile of Salmonella Isolated From Raw Cow Milk and Its Products in Bishoftu Town, Central Ethiopia: Implication for Public Health Lema Temesgen, Takele Beyene Tufa, Fufa Abunna This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5353585/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Mar, 2025 Read the published version in One Health Outlook → Version 1 posted 5 You are reading this latest preprint version Abstract Background Salmonella is a significant foodborne pathogen, with milk and milk products commonly implicated in its transmission. However, limited information is available regarding the direct link between antimicrobial use (AMU), dairy hygiene practices, and antimicrobial resistance (AMR) in Salmonella strains isolated from dairy products in Bishoftu town. Methods Cross-sectional research was done from October 2023 to April 2024 to assess dairy farmers' antimicrobial usage (AMU) and hygiene practices and the occurrence of antimicrobial resistance (AMR) profiles of Salmonella isolated from raw cow milk and its products. Two hundred samples were collected from dairy farms, milk vendors, and restaurants and analyzed using standard microbiological methods. Using the OmniLog system, Salmonella enterica was successfully identified. Then, the antimicrobial susceptibility was evaluated using the Kirby-Bauer disc diffusion technique. Data were analyzed using STATA version 14.2. Results Overall, 2% (n = 4) of the samples tested positive for S. enterica . Of the 4 isolates, 3 were identified in dairy farm samples, whereas 1 were isolated from milk vendors. However, no Salmonella was identified in cheese or yogurt samples obtained from the restaurants. Regarding the AMR profile, S. enterica isolates were resistant to amoxicillin (75%), streptomycin (75%), and tetracycline (50%). Resistant to two or more antimicrobials were identified in 75% of the isolates. Conclusion This study indicated contamination of cow milk and its products with S. enterica . Therefore, appropriate control measures, including awareness creation among personnel and improving hygienic practices at the milk value chains is recommended to mitigate cross-contamination. AMU and AMR KAP assessment Milk vendors and S. enterica Figures Figure 1 Introduction Foodborne illnesses seriously threaten global public health, safety, and the economy. Every year, an estimated 600 million infections and 420,000 fatalities occur because of food-borne diseases (Havelaar et al., 2015 ). Salmonella species , prominent among foodborne pathogens, ranks as the third largest cause of mortality from diarrheal diseases globally (Ferrari et al., 2019 ). It is responsible for an estimated 115 million human infections and 370,000 fatalities every year (Qin et al., 2022 ). The World Health Organization (WHO) estimates that around one in ten individuals become sick from foodborne Salmonella infections each year, resulting in the loss of millions of healthy life years (Lee and Yoon, 2021 ; WHO, 2022). This problem is widespread, affecting countries globally, but developing countries face challenges due to inadequate food safety regulations, poor food handling practices, and limited financial resources (Abunna et al., 2017 ; Ali et al ., 2022; Bedassa et al., 2023 ). Salmonella species are gram-negative, rod-shaped bacteria from the Enterobacteriaceae family (WHO, 2022) and consist of two species, Salmonella bongori and Salmonella enterica , according to the White-Kauffmann system. This categorization is based on the surface structures (lipopolysaccharides, flagella, and capsular polysaccharides). The species Salmonella enterica has six subspecies: enterica, salamae, arizonae, diarizonae, houtenae, and indica, with around 2600 serovars (Vinueza, 2017; Ferrari et al., 2019 ). Among these, the subspecies Salmonella enterica is responsible for about 1500 serovars, of which 99% might cause infections in animals and humans (Ballal et al., 2016 ). Salmonella enterica is classified into two classes based on clinical features of human infections: Typhoidal Salmonella is specific to humans and causes typhoid fever, but Nontyphoidal Salmonella (NTS) has a wide range of hosts and causes several illnesses other than typhoid fever (Fanta, 2021). NTS serotypes are the leading cause of bacterial diarrhea and invasive infections, posing a significant risk to young children, the elderly, and those with weakened immune systems in developing countries (Andoh et al., 2017 ). Salmonella , a ubiquitous bacterium, poses significant public health concerns due to its ability to infect various animals and contaminate the environment. It is commonly found in the digestive systems of both domestic and wild animals (Ehuwa et al., 2021 ) and shed in their feces, facilitating its widespread presence in animal waste, sewage, and contaminated materials (Pal et al ., 2015; Abrar et al ., 2020). As a result, milk and dairy products are susceptible to contamination by infected animals or cross-contamination with fecal-containing pathogens during processing (Teklemariam et al ., 2023). When humans consume contaminated food, they can develop salmonellosis, a diarrheal illness that can range from mild to severe, including abdominal cramps, fever, nausea, and vomiting. In extreme circumstances, Salmonellosis can cause dehydration and even death (Pal et al ., 2015). Milk is considered a highly nutritious food, but it can also be a vehicle for microbial hazards, particularly in developing countries where the hygiene and sanitation practices of dairy farms are inadequate (Kashima et al ., 2013). The bacteria that are associated with raw milk include Escherichia coli O157:H7, Salmonella enterica, Listeria monocytogenes, Campylobacter spp ., and Staphylococcus aureus (Verra et al ., 2015). These can induce severe gastroenteritis in humans (WHO, 2015). Infections with Salmonella species are particularly significant because they cause bacteremia in adults and children in developing countries (Andoh et al., 2017 ). Antimicrobial resistance (AMR) has emerged as a significant worldwide public health problem, posing substantial challenges to effectively treating bacterial infections (Sobur et al., 2019 ). Salmonella , a common foodborne pathogen, is among the bacteria that have developed resistance to various antibiotics. The inappropriate use of antibiotics in livestock particularly, dairy farms has contributed to the rise of antimicrobial-resistant (AMR) Salmonella which can increase human health risks (Endrias Zewdu and Cornelius 2009 ; Abunna et al., 2017 ). Some MDR Salmonella infections in humans have been connected to exposure to dairy farms or contaminated dairy products (Abrar et al., 2020). Salmonellosis , a costly disease affecting dairy producers, can lead to limited treatment options, prolonged illnesses, decreased milk yield, increased healthcare costs, and potentially fatal outcomes. Farmers must be aware of Salmonella's presence in seemingly healthy cows, as it poses significant food safety concerns (Abunna et al., 2017 ; Bedhasa et al ., 2022). In nations with low and middle incomes, such as Ethiopia, there is a growing demand for animal protein, leading to the routine use of antibiotics for growth-promoting, therapeutic, and preventative reasons in livestock production (Van Boeckel et al., 2015 ). Improper antibiotic use in livestock, particularly on dairy farms, along with inadequate waste management practices, can result in the release of resistant pathogens into the environment. This practice poses a significant risk as it can contribute to the emergence of antibiotic-resistant pathogens. This may lead to the development of antibiotic-resistant commensal organisms in livestock, posing a threat to public health (Pandey et al. ,2024). Besides improper antibiotic use, the habit of consuming raw milk or unsafe food, cross-contamination, improper food storage, poor personal hygiene practices, inadequate cooling and reheating of food items, and a prolonged time lapse between preparing and consuming food items have been reported as contributing factors to an outbreak of salmonellosis in human (Vanga and Raghavan, 2018 ). This suggests that milk and dairy products could be a source of Salmonella in Ethiopia in general and may be particularly significant in the central part of Ethiopia, where consumption of milk and milk products is high. Therefore, it is important to isolate pathogenic organisms, identify relevant risk factors, and regularly assess their AMR profiles. In Ethiopia, despite multiple studies identifying Salmonella in milk and dairy products, including evidence of its prevalence among raw milk consumers (Tesfaw et al., 2013 ; Ejo et al., 2016 ; Beyene et al., 2016 ; Abunna et al., 2017 ), there remains a critical gap in understanding the direct relationship between antimicrobial use (AMU), dairy hygiene practices, and the development of antimicrobial resistance (AMR) in Salmonella isolated from dairy products in the current study area. These gaps need for systematic surveillance and comprehensive investigation along the entire farm-to-fork continuum, encompassing routine examination of raw milk and milk product samples from restaurants, milk vendors, and dairy farms. Addressing these gaps is crucial to safeguarding consumer health, mitigating foodborne illnesses, and minimizing both direct and indirect economic losses associated with contaminated dairy products in Ethiopia. Hence, the objectives of this study were to isolate Salmonella from milk and milk products, to evaluate the AMR profile of Salmonella isolated from milk and other dairy products and to assess dairy farmers' AMU and hygienic practices in Bishoftu dairy farms. Material and Methods Description of the Study Area This study was conducted at dairy farms, milk vendors, and restaurants in Bishoftu town. Bishoftu town was purposefully selected because of its larger potential for dairy cattle density, which may pose a risk of Salmonella contamination in dairy products due to cross-contamination along the milk value chain. Bishoftu town is located in the east Showa zone of the Oromia region, situated approximately 45 km southeast of Addis Ababa (Fig. 1 ). The city is situated at 9° North latitude and 40° East longitude, with an altitude of 1850 m above sea level in the central highlands of Ethiopia. The town experiences an annual rainfall of 866 mm, with 84% occurring during the long rainy season from June to September, and the remainder in the short rainy season extending from March to May. The dry season extends from October to February. The mean annual maximum and minimum temperatures in the area are 26°C and 14°C, respectively, with a mean relative humidity of 61.3% (NMSA, 2010 ). Study population The study population was all dairy farms and milk and milk product sellers found in Bishoftu town. A total of 41 dairy farms, 14 milk vendors and 28 restaurants selected randomly were included in the study. The study animals were apparently, healthy dairy cows in small-scale, medium-scale, and large-scale dairy farms located in the selected study areas. The study population included crossbreeds and local breeds in small-scale, medium-scale, and large-scale dairy farms. Most of them (85%) were crossbreeds whereas a few were local (15%). Concerning management, (78%) of the herds were managed intensively while (22%) of herds were semi-intensive. The intensively managed cattle were kept indoors and received concentrate feeds in addition to hay and crop residues (such as corn stalks, wheat/barley straw and other leftovers from grain threshing). On the other hand, the semi-intensively managed cattle grazed freely on pasture but received supplementary feed in the morning and evening when they were milked. All cows were hand-milked twice daily, in the morning and evening. Study Design, Source of Sample and Sampling Method A cross-sectional study design was used to assess AMU and hygienic practices of dairy farmers, and the occurrence of AMR Salmonella isolated from raw cow milk and milk products in the study area from October 2023 to April 2024. For this study, raw milk and milk products (cheese and yogurt), floor swap, fecal samples and swabs from milk containers were gathered from various sources (milk vendors, restaurants, and dairy farms). Bulk milk, fecal samples, floor swap and swap from milk containers) in Bishoftu town. In addition, cheese and yogurt samples were collected from restaurants, whereas bulk milk samples were collected from milk vendors. A stratified random sampling method was used to collect samples from dairy farms. The farms were categorized based on their herd size into three strata; small-scale 50 animals using the classification made by Megersa et al., ( 2011 ). A simple random sampling technique was employed to select dairy farms, restaurants and milk vendors. Similarly, milk containers were selected by simple random sampling to collect appropriate raw milk and milk product samples. The milk and milk product samples were clearly labeled with the date of sampling, the type of sample, and the name of the farm and then held in an icebox with ice packs and transported to the Veterinary Public Health (VPH) laboratory of the College of Veterinary medicine and agriculture, Addis Ababa University (AAU-CVMA). In the laboratory, the samples were stored at 4°C for a maximum of 24h until they were transferred into an enrichment medium and inoculated onto a standard bacteriological media. After the isolation of Salmonella , the positive isolates were transported to Animal Health Institutes (AHI), Sebeta by standard transporting medium for confirmation. Sample Size Determination A simple random sampling technique was used. The necessary sample size was determined concerning the estimated prevalence of Salmonella and the desired minimum precision level, as outlined by Thrusfield (2007). The formula calculating the sample size, N = Z 2 * P exp (1-P exp ) n d 2 Where n = required sample size, d = desired absolute precision, and P exp = expected prevalence. According to (Geletu et al., 2022 ), the expected prevalence of Salmonella in this study is 4.8%, and the desired minimum level of precision is 5% at a 95% confidence level, with a z value of 1.96. Therefore, the minimum required sample size was 70. However, to increase the precision of the study, 200 samples were collected, including 41 bulk milk sample from dairy farms, 41 swab samples from milk containers, 21 fecal samples from apparently healthy cows, and 41-floor swab samples from cow environment and 14 cheese samples and 14 yogurt samples from restaurants and 14 raw milk samples and 14 swab samples of milk container from open market milk vendors. The sample collection process was on a voluntary basis, and the willingness of the owners to provide the samples was considered at the farm level. In contrast, raw milk at milk vendors and cheese and yogurt samples from restaurants were purchased. A structured questionnaire was also used to collect socio-demographic information and potential risk factors contributing to the antimicrobial-resistant profile of Salmonella isolated from milk and milk products. Sample collection and transportation Samples were obtained from various sources, including dairy cows (bulk milk, swap from milk containers, pooled floor swaps, and feces), raw milk from milk vendors, and cheese and yogurt from restaurants. These samples were collected at the beginning of the day, with the timing arranged in advance with the farmers and milkers. The fecal samples were collected directly from the rectum and placed in a 50 ml universal screw-capped bottle containing 10 ml of peptone water as transport media. After milking, the milk samples were collected aseptically from the bulk tank and placed in a milk container. The raw milk cheese and yogurt samples were purchased and collected in plastic bags. The swab samples were collected before milking using a sterile wooden cotton swab and placed in a sterile test tube containing 10 ml of buffered peptone water as transport media. All samples were labeled and transported immediately to the Veterinary Public Health Laboratory of the AAU-CVMA for bacterial isolation. Finally, the suspected colony of Salmonella was confirmed at the Animal Health Institute (AHI), Sebata by using the OmniLog system and antimicrobial susceptibility testing (AST) was performed on the isolates. Bacteriological Isolation of Salmonella The bacteriological analysis was conducted following the microbiology of the food chain guidelines, specifically, the horizontal method outlined in ISO-6579-1, 2017 (Mooijman et al., 2019 ), for the detection, enumeration, and serotyping of Salmonella . The process involved a standard three-stage approach: pre-enrichment, selective enrichment, and selective plating to isolate Salmonella . In the pre-enrichment stage, 1ml of the milk sample was aseptically measured and homogenized with 9 ml of buffered peptone water (HIMEDIA BM020, India), followed by an incubation at 37°C for 24 hours to enhance the recovery of Salmonella . Subsequently, in the secondary enrichment step, Rappaport-Vassiliadis with soya (RVS) was brought to room temperature as per the manufacturer's instructions. The mixture from the primary enrichment sample was thoroughly mixed, after which a 0.1 ml aliquot was transferred and added to 10 ml of Rappaport-Vassiliadis with soya (RVS) for further incubation. The enriched samples were then plated on Xylose Lysine Deoxycholate (XLD) agar, a selective medium for Salmonella isolation, adjusted to room temperature as per the manufacturer's instructions. After vortexing the secondary enrichment tubes, the samples were streaked onto XLD agar using a 10µl loop and incubated at 41.5°C for 24–48 hours. Suspect Salmonella colonies, characterized by pink coloration with or without black centers on XLD agar, were identified. Three to five typical Salmonella colonies were selected, streaked onto nutrient agar, and further incubated at 37°C for 18–24 hours for biochemical identification. Biochemical characterization of Salmonella isolates All potential Salmonella isolates underwent a series of biochemical tests for identification, including the Triple Sugar Iron (TSI) test, Indole test, Citrate utilization test, Methyl red test, Vogues Proskauer (VP) test, and urease test. Isolates showing characteristics such as red slant (alkaline) with a yellow butt (acid) on TSI, blackening due to hydrogen sulfide (H2S) production, and gas production in the butt, negative Indole test, positive Methyl red test (red broth culture), negative urea hydrolysis (yellow), positive citrate utilization (deep blue slant), and negative Voges-Proskauer (VP) test were identified as positive for Salmonella. Isolates meeting these criteria were then transferred and cultured on Nutrient Agar (NA) for antimicrobial sensitivity testing (Mooijman et al., 2019 ). Identification of Salmonella using OmniLog To identify Salmonella , the isolate to be identified was grown on Biolog Universal Growth (BUG) agar medium and then a single colony was suspended in a special "gelling" inoculating fluid (IFA) using inoculazer the recommended cell density. Then, 100 µL of the cell suspension was inoculated into a well of the GEN-III Micro Plate, and the Micro Plate was incubated to allow the phenotypic fingerprint to form. After incubation for 22 hours at 33 o C the phenotypic fingerprint pattern was read by a combination of the Biolog MicroStation reader. The fingerprint data was imported into Omnilog Data Collection software, which searched an extensive database and made an identification call in seconds. The identification process of Salmonella involves four main steps. These steps were isolation of a pure culture on Biolog media, preparation of inoculum, inoculation of Micro Plates and load into the reader, and obtaining of ID results from the printer (BIOLOG, 2010 ). Antimicrobial susceptibility test The pure isolates of Salmonella identified using OmniLog were subjected to AST using the Kirby–Bauer agar disc diffusion method recommended by the Clinical and Laboratory Standards Institute (CLSI) (CLSI, 2022). AST of the isolates was performed against eight selected drugs based on its usage, namely Tetracycline (TE 30µg), Ampicillin (AMP 10µg), Gentamicin (CN 10µg), Trimethoprim-Sulfamethoxazole (TMP-SXT 25µg), Ciprofloxacin (CIP 10µg), Amoxicillin (AX 2µg), Streptomycin (S 10µg), and Amoxicillin-Clavulanic acid (AMC 10µg) (OXOID, UK) based. Refreshed pure isolated colonies from the nutrient agar plates were transferred into tubes containing 5 ml of 0.85% of sterilized saline water. Then, it was measured by a McFarland Densitometer until it achieved 0.5 McFarland turbidity standards. A sterile cotton swab was used to swab the inoculum uniformly over the surface of the Mueller Hinton Agar (Criterion, C6421, USA) plate. The plates were held at room temperature for 3 minutes in a biosafety cabinet to allow drying. Then, antimicrobial disks with the known concentration of antimicrobials were placed on the Muller Hinton Agar plate and were incubated for 22 hr at 37ºC. The diameters of the clear zone of inhibition produced by diffused antimicrobial on lawn-inoculated bacterial colonies were measured to the nearest mm using a caliper. All eight zones of inhibition against eight antimicrobial agents for each isolate were recorded and compared with standards and interpreted as resistant, intermediate, or susceptible according to a published interpretive chart (CLSI, 2022). Data Analysis The raw data generated from the laboratory work was arranged, organized, coded and entered an Excel spreadsheet 2010. Additionally, the KAP survey data gathered through the Kobo Toolbox server was retrieved as Excel files, carefully reviewed for errors, coded, and subsequently imported into the data analysis software. Data were analyzed using Stata/IC version 14.2. The laboratory results of Salmonella detected, and their AMR profile were mostly described in proportion. Ethical clearance This study was granted ethical approval by the College of Veterinary Medicine Animal Research Ethics Committee of Addis Ababa University, with reference number VM/ERC/02/09/16/2024 (ANNEX 18). All procedures were executed by skilled professionals according to the guidelines and regulations established by the university's ethics committee. The welfare and well-being of the animals that participated in this study were ensured throughout the research. Before the commencement of the study, verbal consent was obtained from all farm owners for both the questionnaire interview and the collection of milk and fecal samples from their animals. Results Prevalence of Salmonella Based on Bacteriological Identification A total of 200 samples were collected from three separate sources, namely dairy farms, milk vendors, and restaurants, for bacterial examination. Out of these, 2% (4/200) of the samples tested positive for Salmonella . Specifically, 2.1% (95% CI: 0.7–6.3), 3/144 of the farm samples and 3.57% (95% CI: 0.44–23.7), and 1/28 of the milk vendor samples were found to have salmonella. However, no Salmonella was detected in any of the cheese or yogurt samples collected from the restaurants. In general, of the 4 isolates, three were isolated from samples collected from dairy farms, whereas on were isolated from milk vendors. The study revealed a higher prevalence of Salmonella enterica at the farm level in comparison to milk vendors (Table 1 ). Table 1 Prevalence of Salmonella from milk and milk products in Bishoftu town, Central Ethiopia Sample source Sample type Number of samples examined Salmonella positive Percentage (%) Dairy farm Bulk milk 41 1 2.44 Fecal sample 21 1 4.67 Pooled floor swap 41 1 2.44 Swap of milk container 41 0 0 Total 144 3 2.1 Milk seller Raw milk 14 1 7.1 Swap of milk container 14 0 Total 28 1 3.57 Restaurants Cheese 14 0 0 Yogurt 14 0 0 Total 28 0 0 Total 200 4 2 Pearson chi2(7) P-Value 4.6025 0.708 Prevalence of Salmonella Based on Farm types From the total of 41 dairy farms enrolled in this study (5 small scales, 34 medium scales and 3 large scales), the overall prevalence of Salmonella was 7.32%, with most samples testing negative (92.68%). Of these farms, 1 was small and the remaining 2 were medium-sized. From these, 1/41 (2.43%) and 2/41 (4.88%) Salmonella isolates were obtained from small-size and medium-size farms respectively; and no Salmonella was isolated from large-scale dairy farms. The Pearson chi-squared test revealed 9.65 with a p-value of 0.047. This suggests a statistically significant association between sample type and the occurrence of the pathogen across dairy farms (Table 2 ). Table 2 Prevalence of Salmonella in small, medium and large-scale dairy farms Sample type Result Farm size* Total Small scale Medium scale Large scale Bulk milk Positive 0 1(2.94%) 0% Negative 5(100%) 33(97.06%) 3(100%) Swap of milk container Positive 0 0 0% Negative 5(100%) 34(100%) 3(100%) Floor swap Positive 1(20%) 0 0% Negative 4(80%) 34(100) 3(100%) Fecal sample Positive 0 1(2.94) 0% Negative 5(100%) 33(97.06%) 3(100%) Total Positive 1(20%) 2(5.88) 0% 3(7.32%) Negative 4(80%) 32(94.12%) 3(100%) 38(92.68%) Pearson chi2(4) = 9.6471 P-value = 0.047 * Number of small-scale farms = 5, medium scale = 34 and large-scale farm = 3 Antimicrobial Susceptibility Profiles of Salmonella The study revealed that the common antimicrobials used in the farms were oxytetracycline, fixed combinations of penicillin + streptomycin (pen strep), and sulfonamide in 100%, 100% and 65.9% of the farms, respectively. Salmonella isolates were subjected to an AST against 8 selected antimicrobial agents. Accordingly, 100%, 75%, and 75% of the isolates were found to be susceptible to gentamicin, amoxicillin-clavulanic acid, and ciprofloxacin, respectively. On the other hand, 75%, 75%, and 50% of the isolates were resistant to amoxicillin, streptomycin, and tetracycline (Table 3 ). Table 3 Antimicrobial susceptibility profile of Salmonella isolated from cow milk and its product from the dairy farms and milk vendors in Bishoftu town, central Ethiopia Antimicrobial Class Antimicrobials tested The number of isolates tested Status of antimicrobial agent against the isolate R (%) I (% S (%) Tetracycline Tetracycline 4 50 0 50 B-lactam Ampicillin 4 0 50 50 Amoxicillin 4 75 0 25 AMC 4 0 25 75 Aminoglycosides Gentamicin 4 0 0 100 Streptomycin 4 75 0 25 Sulfonamides TMP-SXT 4 25 25 50 Quinolones Ciprofloxacin 4 25 0 75 Key: R = resistant, I = Intermediate, S = susceptible, %=percent; TMP-SXT = Trimethoprim-Sulfamethoxazole; AMC = Amoxicillin-Clavulanic acid Multidrug Resistance Profile of Salmonella Multidrug resistance (MDR) profile of Salmonella isolated from bulk milk samples, fecal samples and floor swap collected from dairy farms and raw milk collected from milk vendors showed 75% (n = 3/4) of the isolates were resistant to more than two classes of antibiotics. Salmonella isolates from fecal samples showed high resistance to four classes of antibiotics while from bulk milk the isolates showed resistance to three classes of antibiotics. Additionally, raw milk collected from milk vendors showed resistance to a minimum of two classes of antibiotics as shown in Table 4 . Table 4 Multidrug resistance profile of Salmonella Antibiotics Source of MDR Frequency Number of antibiotic classes Percentage AX, CIP, TE Bulk milk 1 3 25% AX, TE, S TMP-SXT Fecal sample 1 4 25% AX, S Floor swaps 1 2 25% S Raw milk 1 1 Overall MDR% 3 3 (75%) AX, amoxicillin; CIP, ciprofloxacin; TE, Tetracycline; S; Streptomycin; TMP-SXT; Trimethoprim-Sulfamethoxazole; MDR; multidrug resistance Discussion Globally, Salmonella species are recognized as prominent foodborne pathogens and rank as the third leading cause of death among diarrheal illnesses in human populations. The primary reservoir of this pathogen is in animals, with transmission to humans predominantly occurring through the consumption of animal-source foods including cow milk and its products (Ferrari et al., 2019 ). Contamination of the environment and along the food chain with bacteria is often attributed to the presence of animal and human wastes that have been contaminated by bacterial pathogens (Abrar et al. , 2020). The result of the present research indicated that the overall prevalence of Salmonella enterica based on the OmniLog system was 2% (4/200); of which 2.44%, 0%, 4.76%, and 2.44% were from bulk milk, swab of milk container, fecal sample and floor swab at dairy farms, 3.5% from raw milk and swab of milk container at milk vendors and 0% and 0% cheese and yogurt from restaurant, respectively. In the present study among the sample types, 2.44% of Salmonella enterica were isolated from bulk milk samples at dairy farms which is consistent with the previous research conducted in different locations. Specifically, it aligns closely with the results reported by Liyuwork et al . (2013) in Addis Ababa, Ethiopia, and by Van et al . (2013) in the United States of America where a prevalence rate of 2.1% and 2.6% were reported respectively. Similarly, the prevalence rate of Salmonella isolated from milk samples in Egypt, as reported by Ahmed et al . (2014) was 1.5% and in Jigjiga town by Reta et al . (2016), was 3.3%, which is within the range of the current study's findings. Additionally, the prevalence rate reported by Murinda et al. ( 2002 ) in the USA was 2.24%, further supporting the consistency of the present study's results. However, the prevalence of Salmonella isolated from bulk milk in this study is relatively higher than the report of Abunna et al. ( 2018 ) and Dadi et al. ( 2020 ) which was 0% and 0.7% at Meki and Sebata town Oromia, Ethiopia respectively. On the other hand, from Dire Daw (18.75%) by Tesfaye et al. (2013), Central Ethiopia (10%) by Geletu et al . (2023) and reports from Gondor (6.0%) by Ejo et al. ( 2016 ) are much higher than the current investigation. The difference in the relative amount of the bacteria present in milk between the current study and previous research carried out in various study areas in Ethiopia could be explained by variations in the potential risk factors contributing to the occurrence of Salmonella in milk. Several factors, such as milking procedures, milk handling practices, hygiene and management practices, stocking density, use of contaminated utensils, housing type, animal movement, milking environment, ventilation, and production facilities in different areas, are examples of the main risk factors that influence the occurrence of Salmonella (Abunna et al., 2017 ; Gebeyehu et al., 2022 ; Gezahegn et al., 2023 ). Furthermore, methods employed in the research areas may also be a factor in the variation in the relative isolation rate of Salmonella. Even though the current study isolated and identified only 2.44% of the Salmonella from the bulk milk, compared to previous studies, this could pose serious health risks to humans by causing Salmonellosis in high-risk populations like newborns, infants, the elderly, and people with immune-compromised, who are susceptible to Salmonella infections at a lower infective dose than healthy adults. Because dairy products are frequently consumed in Ethiopia without being properly boiled (Geletu et al., 2022 ), it is a source of Salmonella infection. In the current study, an isolation rate of 4.76% for Salmonella enterica was recorded in fecal samples. This finding is consistent with prior research conducted by Geletu et a l. (2023), who reported a similar prevalence rate of 4.7% in central Ethiopia. Additionally, the observed prevalence aligns with the results documented by Gezahegn et al. ( 2023 ) in the Bedele and Nekemte districts of western Ethiopia, where a prevalence rate of 2.97% was reported. Factors that could explain this consistency include the possibility that common problems with animal husbandry practices, sanitation, and hygiene could have an impact on the observed prevalence rates irrespective of geographical location. In this study, the fecal prevalence of Salmonella was found to be lower than that reported in previous studies conducted by Abunna et al. ( 2017 ) in Modjo town, Ethiopia, who documented a higher prevalence rate of 7.7% and 12% prevalence rate which was reported by Khan et al. ( 2021 ) in the Republic of Korea. Additionally, our results were lower than those reported by Hailu et al. ( 2015 ) in Northern Ethiopia. The observed differences in prevalence rates between our study and previous research can be due to various factors, including variations in sampling methods, duration of sampling period, environmental conditions, animal management practices, animal husbandry, biosecurity measures, sanitation protocols and geographical variability. Additionally, variations in laboratory techniques and procedures can affect the accuracy and comparability of prevalence estimates across studies. The prevalence rate of Salmonella isolated from floor swabs in the present study was 2.44%. This finding is consistent with previous studies by Gezahagn et al . (2023) in the town of Bedelle and Nekemte in western Ethiopia and by Geletu et al. ( 2022 ) in central Ethiopia, where the prevalence rate in dairy farms was reported to be 5% in both studies. The consistency of prevalence rates in these studies could be attributed to similar environmental conditions, management practices and biosecurity measures applied on dairy farms in these regions. Factors such as poor hygiene, animal overcrowding and inadequate cleaning and disinfection protocols could contribute to the presence of Salmonella on dairy farm floors. The average prevalence rate of Salmonella isolated from raw milk at milk vendors in the present study was found to be 3.5%, which agrees with the report of Tusa et al. ( 2024 ) in Asella Town Oromia, Ethiopia with a prevalence rate of 3.3% and the finding of Jassim et al. (2020) in Iraq with the prevalence rate of 3%. However, the prevalence rate of the present finding was much lower than the report of Tesfay et al . (2013), Ahmed et al. (2020) in Bangladesh and the finding of Anukampa et al . (2017) in India which was 41.7%, 45%, and 7.4% respectively. The prevalence of Salmonella in raw milk varies across different milk vendors due to various factors. These include study design, sampling techniques, geographic locations, hygiene practices, and storage conditions. Larger sample sizes and advanced detection methods can yield higher prevalence rates. The prevalence of Salmonella in raw milk can fluctuate depending on regional and local practices, environmental factors, animal health, and farm practices. The variation in hygiene practices during milk production, handling, and storage can increase the risk of bacterial contamination. Inadequate sanitation, equipment cleaning, and improper storage conditions can also increase the risk. The health status of dairy animals and the presence of infectious diseases can also impact the prevalence of Salmonella in raw milk. Cross-contamination during milk handling and processing can introduce Salmonella from external sources. In the present study, no Salmonella was isolated from cheese and yogurt samples, which agreed with the findings of Ejo et al. ( 2016 ) and Tesfaw et al. ( 2013 ), who reported no Salmonella species found in cheese and yogurt. The absence of Salmonella in cheese and yogurt samples can be attributed to several factors. Proper storage and handling practices, including adequate refrigeration and hygienic handling, help to prevent contamination after processing. The sensitivity of the sampling and detection methods can also influence the absence of Salmonella. In this study, an attempt was made to evaluate and compare the isolation rate of Salmonella in dairy farms of different herd sizes, namely small, medium, and large. The result showed out of 41 dairy farms (3 large-scale, 34 medium-scale and 5 small-scale dairy farms) the total prevalence rate of Salmonella was 7.32%. Our results showed that the isolation rate of Salmonella was significantly comparable between small and medium-sized farms. However, in this cross-sectional study, there was no Salmonella isolated from large-scale dairy farms. Several factors could contribute to this study's lack of Salmonella isolation from large dairy farms. Some possible reasons could be strict biosecurity measures: Large dairy farms may have stricter biosecurity protocols in place to prevent the introduction and spread of pathogens, including Salmonella , as compared to small-scale dairy farms. Management practices, such as regular cleaning and disinfecting facilities, can help reduce the spread of Salmonella . Antimicrobial resistance is a growing worldwide issue in human and veterinary health, affecting both developed and developing countries. The growing use of antimicrobial drugs in food animal production and humans was a significant contributor to the establishment of bacterial resistance (Gebremedhin et al., 2021 ). In the current investigation, Salmonella isolates (n = 4) were evaluated against eight frequently used antimicrobials using CLSI-2022 guidance. Antimicrobial susceptibility testing revealed 75%, 75%, and 50% resistance to amoxicillin, streptomycin, and tetracycline respectively. In comparison, 100% sensitivity to gentamycin was identified, followed by 75%, 75%, 50%, and 50% sensitivity to amoxicillin-clavulanic acid, ciprofloxacin, tetracycline, and ampicillin, respectively. The current findings revealed that 75% of the isolates were resistant to two or more classes of antibiotics, which was lower than the report of Fesseha et al. ( 2020 ), who documented the MDR rate of 96.4% from selected dairy farms in Hawasa town. However, these findings were higher than those previously reported by Tesfaw et al. ( 2013 ), who documented a 50% MDR of Salmonella isolate. The possible reasons for the high AMR level of Salmonella might be due to the increasing rate of irrational use of antimicrobials in dairy farms, frequent usage both in livestock and public health, use of counterfeit drugs in animal husbandry (Farhan et al., 2024 ), self-medication due to easy access to antimicrobials without prescription in the public health sector, and administration of subtherapeutic doses. The current investigation found 75% amoxicillin resistance, which was greater than the findings of Beyene et al. ( 2016 ) and Fesseha et al. ( 2020 ) in Asella and Hawasa Town, Ethiopia, who reported resistance rates of 58.3% and 25%, respectively. The observed high resistance to streptomycin is not surprising, as these antimicrobials are commonly used in all farms to manage bacterial infection. The streptomycin resistance in the current study is consistent with previous results in Addis Ababa, as reported by Zewdu and Cornelius ( 2009 ), who recorded a resistance rate of 75% among food items and personnel. However, the results of our research's resistance rate were lower than those reported by Ketema et al. ( 2018 ) and Obaidat and Stringer ( 2019 ), which were 80% and 89.3%, respectively. On the other hand, our data suggested a greater resistance rate than the studies by Abra et al . (2020), Geletu et al. ( 2022 ), and Beyene et al. ( 2016 ) who documented a 60%, 46% and 41.7% resistance rate respectively. The resistance profile towards tetracycline was 50%, which is comparable with the findings of Mulaw ( 2017 ), (52.8%) among lactating cows in dairy farms in Bahir Dar Town, Ethiopia. However, it is interesting to note that the tetracycline resistance rate found in the current study exceeds that of Xu et al. ( 2018 ) in the United States, which was 28% lower than the report of Fesseha et al. ( 2020 ), who recorded a resistant rate of 96.4%. This difference in resistance rates might be due to the increasing use of inappropriate antimicrobials on dairy farms. Such methods provide selection pressure, which increases the survival and growth of bacterial strains containing resistance genes (Fesseha et al., 2020 ). As a result, such action may contribute to the variations in resistance profiles found among studies. The growing frequency of antibiotic resistance highlights the critical need for extensive antimicrobial management procedures to prevent the emergence and spread of resistant bacterial strains. The present results showed that Salmonella isolates were susceptible to gentamycin and with a susceptibility rate of 100%. This was consistent with the reports of Tesfaw et al. ( 2013 ), Abunna et al. ( 2017 ) and Beyene et al . (2020) who documented a resistant rate of 100% but, higher than 73.3% and 75% reported by Addis et al. ( 2011 ) and Tadesse and Anbessa, respectively. Additionally, the susceptibility rate of ciprofloxacin was 75% which was lower than the report of 83.3% documented by Addis et al. ( 2011 ). The variation in ciprofloxacin effectiveness in Ethiopian dairy farming might be related to drug type, different bacterial strains, resistance gene evolution, and limited use in Ethiopian animal production. The Misuse of antimicrobials in livestock may lead to the emergence and spread of pathogens that are harmful to human, animal and environmental health (Hirwa et al., 2024 ). One of the major contributors to the rise of AMR is antibiotic misuse (Gebeyehu et al., 2021 ), which is linked to an antimicrobial knowledge gap. Conclusion The present study revealed the occurrence of contamination of cow milk and its products with Salmonella enterica along the milk value chain at farms and milk vendors. The isolations of the bacteria from bulk milk, fecal samples, and floor swabs of the cow environment were found to be the potential sources of milk contamination at the farms and milk vendors. The presence of Salmonella enterica in bulk milk at the farm level and milk vendors indicates that there was cross-contamination of milk possibly because of Salmonella shedding in cattle feces, poor animal hygiene and housing conditions, contact with contaminated water or feed, fecal contamination of milking equipment or milk storage tanks, unsanitary milking practice, poor hygiene of milk handlers/vendors, improper storage and incomplete or improper antibiotic treatment. The study has also revealed the possibility of a public health risk posed due to Salmonella enterica in the study area. In general, the assessment of AMR profile of Salmonella in dairy farms is critical for safeguarding public health, ensuring food safety, minimizing economic losses, and promoting the overall well-being of animals, the environment, and humans. By understanding the prevalence and dynamics of Salmonella in dairy environments, proactive measures can be taken to prevent contamination, reduce risks, and protect both the dairy industry and consumers. Therefore, creating public awareness about good milk handling practices, milk-borne diseases, and their prevention for dairy farmers and consumers should be implemented. Declarations Acknowledgements This work was supported by Addis Ababa University. We would like to appreciate dairy farmers for their cooperation during data collection. Author contributions L.T.: Conceptualization; Investigation; Formal analysis; Data Collection; Writing-original draft, Writing-review & Editing T.B.: Conceptualization, Investigation; Data Collection; Writing-review & Editing F.A: Conceptualization; Methodology; Writing-review & Editing, Fund Acquisition; Supervision; Writing-review & editing. Data availability Not applicable. Declarations Ethics approval and consent to participate This study was approved, and ethical clearance was obtained from the Institutional Review Board of the College of Veterinary medicine and Agriculture Sciences, Addis Ababa University (VM-ERC 02/09/16/2024). Consent for publication All authors consent to publication. Funding Logistics for data collection is financially supported by Addis Ababa University Competing interests The authors declare no competing interests References Abrar A, Beyene T, and Furgasa. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5353585","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":375297170,"identity":"db748fd1-619f-4ecb-97c5-4f7ed8b4d4fe","order_by":0,"name":"Lema Temesgen","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Lema","middleName":"","lastName":"Temesgen","suffix":""},{"id":375297171,"identity":"a5eee404-fac0-40c9-8118-dbde1ddef38a","order_by":1,"name":"Takele Beyene Tufa","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Takele","middleName":"Beyene","lastName":"Tufa","suffix":""},{"id":375297172,"identity":"6309a244-038c-4c41-8db9-7e36f75e753b","order_by":2,"name":"Fufa Abunna","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYBAC9gbGB0DqAIgNZgFBAn4tPAeYDWBawCyoFjzakLWwSRCnRSKZ8QNDzZ3E7dLNzyp+1Bxm4GfPMWD4+AOvFmYJhmPPEnfOOWZ2s+fYYQbJnjcGjDPw2GIvkX9AgoHtcOKGGwlmN3jYDjMY3MgxYObB7zDmHwz/QFrSvxX++XeYwR6k5Q9+LWwSjG0gLTlmzLxtQFskgFrwep/nMZtFYt8zY6CWYmnZvnQeiTPPCg72pOHRwp7MfOPDtzuyQIdt/Pjmm7Ucf3vyxgc/bHBrAQNkV/CAiAMENIyCUTAKRsEoIAAAlo1UVMn+DLQAAAAASUVORK5CYII=","orcid":"","institution":"Addis Ababa University","correspondingAuthor":true,"prefix":"","firstName":"Fufa","middleName":"","lastName":"Abunna","suffix":""}],"badges":[],"createdAt":"2024-10-29 10:46:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5353585/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5353585/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s42522-025-00134-y","type":"published","date":"2025-03-15T15:58:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69834315,"identity":"9e00e3ae-e7f4-4efe-abed-c54697c9297a","added_by":"auto","created_at":"2024-11-25 15:55:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":247332,"visible":true,"origin":"","legend":"\u003cp\u003eMap of study Area (Bishoftu town, Oromia Region, Central highland of Ethiopia\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5353585/v1/6204ad185bdda65e7a7e4585.png"},{"id":78689085,"identity":"118e8c3f-52f1-4dc7-9e02-72369dcf8544","added_by":"auto","created_at":"2025-03-17 16:11:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1297876,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5353585/v1/cfb41a01-65bd-4e2d-9405-167e0e47a50f.pdf"}],"financialInterests":"","formattedTitle":"Detection and Antimicrobial Resistance Profile of Salmonella Isolated From Raw Cow Milk and Its Products in Bishoftu Town, Central Ethiopia: Implication for Public Health","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFoodborne illnesses seriously threaten global public health, safety, and the economy. Every year, an estimated 600\u0026nbsp;million infections and 420,000 fatalities occur because of food-borne diseases (Havelaar et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). \u003cem\u003eSalmonella species\u003c/em\u003e, prominent among foodborne pathogens, ranks as the third largest cause of mortality from diarrheal diseases globally (Ferrari et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It is responsible for an estimated 115\u0026nbsp;million human infections and 370,000 fatalities every year (Qin et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The World Health Organization (WHO) estimates that around one in ten individuals become sick from foodborne Salmonella infections each year, resulting in the loss of millions of healthy life years (Lee and Yoon, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; WHO, 2022). This problem is widespread, affecting countries globally, but developing countries face challenges due to inadequate food safety regulations, poor food handling practices, and limited financial resources (Abunna et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ali \u003cem\u003eet al\u003c/em\u003e., 2022; Bedassa et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eSalmonella species\u003c/em\u003e are gram-negative, rod-shaped bacteria from the Enterobacteriaceae family (WHO, 2022) and consist of two species, \u003cem\u003eSalmonella bongori\u003c/em\u003e and \u003cem\u003eSalmonella enterica\u003c/em\u003e, according to the White-Kauffmann system. This categorization is based on the surface structures (lipopolysaccharides, flagella, and capsular polysaccharides). The species \u003cem\u003eSalmonella enterica\u003c/em\u003e has six subspecies: enterica, salamae, arizonae, diarizonae, houtenae, and indica, with around 2600 serovars (Vinueza, 2017; Ferrari et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Among these, the subspecies \u003cem\u003eSalmonella enterica\u003c/em\u003e is responsible for about 1500 serovars, of which 99% might cause infections in animals and humans (Ballal et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). \u003cem\u003eSalmonella enterica\u003c/em\u003e is classified into two classes based on clinical features of human infections: Typhoidal Salmonella is specific to humans and causes typhoid fever, but Nontyphoidal Salmonella (NTS) has a wide range of hosts and causes several illnesses other than typhoid fever (Fanta, 2021). NTS serotypes are the leading cause of bacterial diarrhea and invasive infections, posing a significant risk to young children, the elderly, and those with weakened immune systems in developing countries (Andoh et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eSalmonella\u003c/em\u003e, a ubiquitous bacterium, poses significant public health concerns due to its ability to infect various animals and contaminate the environment. It is commonly found in the digestive systems of both domestic and wild animals (Ehuwa et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and shed in their feces, facilitating its widespread presence in animal waste, sewage, and contaminated materials (Pal \u003cem\u003eet al\u003c/em\u003e., 2015; Abrar \u003cem\u003eet al\u003c/em\u003e., 2020). As a result, milk and dairy products are susceptible to contamination by infected animals or cross-contamination with fecal-containing pathogens during processing (Teklemariam \u003cem\u003eet al\u003c/em\u003e., 2023). When humans consume contaminated food, they can develop salmonellosis, a diarrheal illness that can range from mild to severe, including abdominal cramps, fever, nausea, and vomiting. In extreme circumstances, \u003cem\u003eSalmonellosis\u003c/em\u003e can cause dehydration and even death (Pal \u003cem\u003eet al\u003c/em\u003e., 2015).\u003c/p\u003e \u003cp\u003eMilk is considered a highly nutritious food, but it can also be a vehicle for microbial hazards, particularly in developing countries where the hygiene and sanitation practices of dairy farms are inadequate (Kashima \u003cem\u003eet al\u003c/em\u003e., 2013). The bacteria that are associated with raw milk include \u003cem\u003eEscherichia coli O157:H7, Salmonella enterica, Listeria monocytogenes, Campylobacter spp\u003c/em\u003e., and \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (Verra \u003cem\u003eet al\u003c/em\u003e., 2015). These can induce severe gastroenteritis in humans (WHO, 2015). Infections with \u003cem\u003eSalmonella species\u003c/em\u003e are particularly significant because they cause bacteremia in adults and children in developing countries (Andoh et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAntimicrobial resistance (AMR) has emerged as a significant worldwide public health problem, posing substantial challenges to effectively treating bacterial infections (Sobur et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). \u003cem\u003eSalmonella\u003c/em\u003e, a common foodborne pathogen, is among the bacteria that have developed resistance to various antibiotics. The inappropriate use of antibiotics in livestock particularly, dairy farms has contributed to the rise of antimicrobial-resistant (AMR) Salmonella which can increase human health risks (Endrias Zewdu and Cornelius \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Abunna et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Some MDR \u003cem\u003eSalmonella\u003c/em\u003e infections in humans have been connected to exposure to dairy farms or contaminated dairy products (Abrar \u003cem\u003eet\u003c/em\u003e al., 2020). \u003cem\u003eSalmonellosis\u003c/em\u003e, a costly disease affecting dairy producers, can lead to limited treatment options, prolonged illnesses, decreased milk yield, increased healthcare costs, and potentially fatal outcomes. Farmers must be aware of \u003cem\u003eSalmonella's\u003c/em\u003e presence in seemingly healthy cows, as it poses significant food safety concerns (Abunna et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bedhasa \u003cem\u003eet al\u003c/em\u003e., 2022).\u003c/p\u003e \u003cp\u003eIn nations with low and middle incomes, such as Ethiopia, there is a growing demand for animal protein, leading to the routine use of antibiotics for growth-promoting, therapeutic, and preventative reasons in livestock production (Van Boeckel et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Improper antibiotic use in livestock, particularly on dairy farms, along with inadequate waste management practices, can result in the release of resistant pathogens into the environment. This practice poses a significant risk as it can contribute to the emergence of antibiotic-resistant pathogens. This may lead to the development of antibiotic-resistant commensal organisms in livestock, posing a threat to public health (Pandey \u003cem\u003eet al.\u003c/em\u003e,2024).\u003c/p\u003e \u003cp\u003eBesides improper antibiotic use, the habit of consuming raw milk or unsafe food, cross-contamination, improper food storage, poor personal hygiene practices, inadequate cooling and reheating of food items, and a prolonged time lapse between preparing and consuming food items have been reported as contributing factors to an outbreak of salmonellosis in human (Vanga and Raghavan, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This suggests that milk and dairy products could be a source of \u003cem\u003eSalmonella\u003c/em\u003e in Ethiopia in general and may be particularly significant in the central part of Ethiopia, where consumption of milk and milk products is high. Therefore, it is important to isolate pathogenic organisms, identify relevant risk factors, and regularly assess their AMR profiles.\u003c/p\u003e \u003cp\u003eIn Ethiopia, despite multiple studies identifying \u003cem\u003eSalmonella\u003c/em\u003e in milk and dairy products, including evidence of its prevalence among raw milk consumers (Tesfaw et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ejo et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Beyene et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Abunna et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), there remains a critical gap in understanding the direct relationship between antimicrobial use (AMU), dairy hygiene practices, and the development of antimicrobial resistance (AMR) in \u003cem\u003eSalmonella\u003c/em\u003e isolated from dairy products in the current study area. These gaps need for systematic surveillance and comprehensive investigation along the entire farm-to-fork continuum, encompassing routine examination of raw milk and milk product samples from restaurants, milk vendors, and dairy farms. Addressing these gaps is crucial to safeguarding consumer health, mitigating foodborne illnesses, and minimizing both direct and indirect economic losses associated with contaminated dairy products in Ethiopia. Hence, the objectives of this study were to isolate \u003cem\u003eSalmonella\u003c/em\u003e from milk and milk products, to evaluate the AMR profile of \u003cem\u003eSalmonella\u003c/em\u003e isolated from milk and other dairy products and to assess dairy farmers' AMU and hygienic practices in Bishoftu dairy farms.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDescription of the Study Area\u003c/h2\u003e \u003cp\u003eThis study was conducted at dairy farms, milk vendors, and restaurants in Bishoftu town. Bishoftu town was purposefully selected because of its larger potential for dairy cattle density, which may pose a risk of \u003cem\u003eSalmonella\u003c/em\u003e contamination in dairy products due to cross-contamination along the milk value chain. Bishoftu town is located in the east Showa zone of the Oromia region, situated approximately 45 km southeast of Addis Ababa (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The city is situated at 9\u0026deg; North latitude and 40\u0026deg; East longitude, with an altitude of 1850 m above sea level in the central highlands of Ethiopia. The town experiences an annual rainfall of 866 mm, with 84% occurring during the long rainy season from June to September, and the remainder in the short rainy season extending from March to May. The dry season extends from October to February. The mean annual maximum and minimum temperatures in the area are 26\u0026deg;C and 14\u0026deg;C, respectively, with a mean relative humidity of 61.3% (NMSA, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eThe study population was all dairy farms and milk and milk product sellers found in Bishoftu town. A total of 41 dairy farms, 14 milk vendors and 28 restaurants selected randomly were included in the study. The study animals were apparently, healthy dairy cows in small-scale, medium-scale, and large-scale dairy farms located in the selected study areas. The study population included crossbreeds and local breeds in small-scale, medium-scale, and large-scale dairy farms. Most of them (85%) were crossbreeds whereas a few were local (15%). Concerning management, (78%) of the herds were managed intensively while (22%) of herds were semi-intensive. The intensively managed cattle were kept indoors and received concentrate feeds in addition to hay and crop residues (such as corn stalks, wheat/barley straw and other leftovers from grain threshing). On the other hand, the semi-intensively managed cattle grazed freely on pasture but received supplementary feed in the morning and evening when they were milked. All cows were hand-milked twice daily, in the morning and evening.\u003c/p\u003e\n\u003ch3\u003eStudy Design, Source of Sample and Sampling Method\u003c/h3\u003e\n\u003cp\u003eA cross-sectional study design was used to assess AMU and hygienic practices of dairy farmers, and the occurrence of AMR \u003cem\u003eSalmonella\u003c/em\u003e isolated from raw cow milk and milk products in the study area from October 2023 to April 2024. For this study, raw milk and milk products (cheese and yogurt), floor swap, fecal samples and swabs from milk containers were gathered from various sources (milk vendors, restaurants, and dairy farms). Bulk milk, fecal samples, floor swap and swap from milk containers) in Bishoftu town. In addition, cheese and yogurt samples were collected from restaurants, whereas bulk milk samples were collected from milk vendors.\u003c/p\u003e \u003cp\u003eA stratified random sampling method was used to collect samples from dairy farms. The farms were categorized based on their herd size into three strata; small-scale\u0026thinsp;\u0026lt;\u0026thinsp;10 animals, medium-scale 10 to 50 animals, and large-scale\u0026thinsp;\u0026gt;\u0026thinsp;50 animals using the classification made by Megersa et al., (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). A simple random sampling technique was employed to select dairy farms, restaurants and milk vendors. Similarly, milk containers were selected by simple random sampling to collect appropriate raw milk and milk product samples. The milk and milk product samples were clearly labeled with the date of sampling, the type of sample, and the name of the farm and then held in an icebox with ice packs and transported to the Veterinary Public Health (VPH) laboratory of the College of Veterinary medicine and agriculture, Addis Ababa University (AAU-CVMA). In the laboratory, the samples were stored at 4\u0026deg;C for a maximum of 24h until they were transferred into an enrichment medium and inoculated onto a standard bacteriological media. After the isolation of \u003cem\u003eSalmonella\u003c/em\u003e, the positive isolates were transported to Animal Health Institutes (AHI), Sebeta by standard transporting medium for confirmation.\u003c/p\u003e\n\u003ch3\u003eSample Size Determination\u003c/h3\u003e\n\u003cp\u003eA simple random sampling technique was used. The necessary sample size was determined concerning the estimated prevalence of \u003cem\u003eSalmonella\u003c/em\u003e and the desired minimum precision level, as outlined by Thrusfield (2007). The formula calculating the sample size,\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;Z\u003csup\u003e2\u003c/sup\u003e * \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eP\u003c/span\u003e\u003csub\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eexp\u003c/span\u003e\u003c/sub\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(1-P\u003c/span\u003e\u003csub\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eexp\u003c/span\u003e\u003c/sub\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e) n\u003c/span\u003e\u003c/p\u003e \u003cp\u003ed\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhere n\u0026thinsp;=\u0026thinsp;required sample size, d\u0026thinsp;=\u0026thinsp;desired absolute precision, and P \u003csub\u003eexp\u003c/sub\u003e= expected prevalence.\u003c/p\u003e \u003cp\u003eAccording to (Geletu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the expected prevalence of \u003cem\u003eSalmonella\u003c/em\u003e in this study is 4.8%, and the desired minimum level of precision is 5% at a 95% confidence level, with a z value of 1.96. Therefore, the minimum required sample size was 70. However, to increase the precision of the study, 200 samples were collected, including 41 bulk milk sample from dairy farms, 41 swab samples from milk containers, 21 fecal samples from apparently healthy cows, and 41-floor swab samples from cow environment and 14 cheese samples and 14 yogurt samples from restaurants and 14 raw milk samples and 14 swab samples of milk container from open market milk vendors. The sample collection process was on a voluntary basis, and the willingness of the owners to provide the samples was considered at the farm level. In contrast, raw milk at milk vendors and cheese and yogurt samples from restaurants were purchased. A structured questionnaire was also used to collect socio-demographic information and potential risk factors contributing to the antimicrobial-resistant profile of \u003cem\u003eSalmonella\u003c/em\u003e isolated from milk and milk products.\u003c/p\u003e\n\u003ch3\u003eSample collection and transportation\u003c/h3\u003e\n\u003cp\u003eSamples were obtained from various sources, including dairy cows (bulk milk, swap from milk containers, pooled floor swaps, and feces), raw milk from milk vendors, and cheese and yogurt from restaurants. These samples were collected at the beginning of the day, with the timing arranged in advance with the farmers and milkers. The fecal samples were collected directly from the rectum and placed in a 50 ml universal screw-capped bottle containing 10 ml of peptone water as transport media. After milking, the milk samples were collected aseptically from the bulk tank and placed in a milk container. The raw milk cheese and yogurt samples were purchased and collected in plastic bags.\u003c/p\u003e \u003cp\u003eThe swab samples were collected before milking using a sterile wooden cotton swab and placed in a sterile test tube containing 10 ml of buffered peptone water as transport media. All samples were labeled and transported immediately to the Veterinary Public Health Laboratory of the AAU-CVMA for bacterial isolation. Finally, the suspected colony of Salmonella was confirmed at the Animal Health Institute (AHI), Sebata by using the OmniLog system and antimicrobial susceptibility testing (AST) was performed on the isolates.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBacteriological Isolation of\u003c/b\u003e \u003cb\u003eSalmonella\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe bacteriological analysis was conducted following the microbiology of the food chain guidelines, specifically, the horizontal method outlined in ISO-6579-1, 2017 (Mooijman et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), for the detection, enumeration, and serotyping of \u003cem\u003eSalmonella\u003c/em\u003e. The process involved a standard three-stage approach: pre-enrichment, selective enrichment, and selective plating to isolate \u003cem\u003eSalmonella\u003c/em\u003e. In the pre-enrichment stage, 1ml of the milk sample was aseptically measured and homogenized with 9 ml of buffered peptone water (HIMEDIA BM020, India), followed by an incubation at 37\u0026deg;C for 24 hours to enhance the recovery of \u003cem\u003eSalmonella\u003c/em\u003e. Subsequently, in the secondary enrichment step, Rappaport-Vassiliadis with soya (RVS) was brought to room temperature as per the manufacturer's instructions. The mixture from the primary enrichment sample was thoroughly mixed, after which a 0.1 ml aliquot was transferred and added to 10 ml of Rappaport-Vassiliadis with soya (RVS) for further incubation.\u003c/p\u003e \u003cp\u003eThe enriched samples were then plated on Xylose Lysine Deoxycholate (XLD) agar, a selective medium for \u003cem\u003eSalmonella\u003c/em\u003e isolation, adjusted to room temperature as per the manufacturer's instructions. After vortexing the secondary enrichment tubes, the samples were streaked onto XLD agar using a 10\u0026micro;l loop and incubated at 41.5\u0026deg;C for 24\u0026ndash;48 hours. Suspect \u003cem\u003eSalmonella\u003c/em\u003e colonies, characterized by pink coloration with or without black centers on XLD agar, were identified. Three to five typical \u003cem\u003eSalmonella\u003c/em\u003e colonies were selected, streaked onto nutrient agar, and further incubated at 37\u0026deg;C for 18\u0026ndash;24 hours for biochemical identification.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBiochemical characterization of\u003c/b\u003e \u003cb\u003eSalmonella\u003c/b\u003e \u003cb\u003eisolates\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAll potential \u003cem\u003eSalmonella\u003c/em\u003e isolates underwent a series of biochemical tests for identification, including the Triple Sugar Iron (TSI) test, Indole test, Citrate utilization test, Methyl red test, Vogues Proskauer (VP) test, and urease test. Isolates showing characteristics such as red slant (alkaline) with a yellow butt (acid) on TSI, blackening due to hydrogen sulfide (H2S) production, and gas production in the butt, negative Indole test, positive Methyl red test (red broth culture), negative urea hydrolysis (yellow), positive citrate utilization (deep blue slant), and negative Voges-Proskauer (VP) test were identified as positive for Salmonella. Isolates meeting these criteria were then transferred and cultured on Nutrient Agar (NA) for antimicrobial sensitivity testing (Mooijman et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eIdentification of\u003c/b\u003e \u003cb\u003eSalmonella\u003c/b\u003e \u003cb\u003eusing OmniLog\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo identify \u003cem\u003eSalmonella\u003c/em\u003e, the isolate to be identified was grown on Biolog Universal Growth (BUG) agar medium and then a single colony was suspended in a special \"gelling\" inoculating fluid (IFA) using inoculazer the recommended cell density. Then, 100 \u0026micro;L of the cell suspension was inoculated into a well of the GEN-III Micro Plate, and the Micro Plate was incubated to allow the phenotypic fingerprint to form. After incubation for 22 hours at 33 \u003csup\u003eo\u003c/sup\u003eC the phenotypic fingerprint pattern was read by a combination of the Biolog MicroStation reader. The fingerprint data was imported into Omnilog Data Collection software, which searched an extensive database and made an identification call in seconds. The identification process of \u003cem\u003eSalmonella\u003c/em\u003e involves four main steps. These steps were isolation of a pure culture on Biolog media, preparation of inoculum, inoculation of Micro Plates and load into the reader, and obtaining of ID results from the printer (BIOLOG, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAntimicrobial susceptibility test\u003c/h2\u003e \u003cp\u003eThe pure isolates of \u003cem\u003eSalmonella\u003c/em\u003e identified using OmniLog were subjected to AST using the Kirby\u0026ndash;Bauer agar disc diffusion method recommended by the Clinical and Laboratory Standards Institute (CLSI) (CLSI, 2022). AST of the isolates was performed against eight selected drugs based on its usage, namely Tetracycline (TE 30\u0026micro;g), Ampicillin (AMP 10\u0026micro;g), Gentamicin (CN 10\u0026micro;g), Trimethoprim-Sulfamethoxazole (TMP-SXT 25\u0026micro;g), Ciprofloxacin (CIP 10\u0026micro;g), Amoxicillin (AX 2\u0026micro;g), Streptomycin (S 10\u0026micro;g), and Amoxicillin-Clavulanic acid (AMC 10\u0026micro;g) (OXOID, UK) based. Refreshed pure isolated colonies from the nutrient agar plates were transferred into tubes containing 5 ml of 0.85% of sterilized saline water. Then, it was measured by a McFarland Densitometer until it achieved 0.5 McFarland turbidity standards. A sterile cotton swab was used to swab the inoculum uniformly over the surface of the Mueller Hinton Agar (Criterion, C6421, USA) plate. The plates were held at room temperature for 3 minutes in a biosafety cabinet to allow drying. Then, antimicrobial disks with the known concentration of antimicrobials were placed on the Muller Hinton Agar plate and were incubated for 22 hr at 37\u0026ordm;C. The diameters of the clear zone of inhibition produced by diffused antimicrobial on lawn-inoculated bacterial colonies were measured to the nearest mm using a caliper. All eight zones of inhibition against eight antimicrobial agents for each isolate were recorded and compared with standards and interpreted as resistant, intermediate, or susceptible according to a published interpretive chart (CLSI, 2022).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe raw data generated from the laboratory work was arranged, organized, coded and entered an Excel spreadsheet 2010. Additionally, the KAP survey data gathered through the Kobo Toolbox server was retrieved as Excel files, carefully reviewed for errors, coded, and subsequently imported into the data analysis software. Data were analyzed using Stata/IC version 14.2. The laboratory results of \u003cem\u003eSalmonella\u003c/em\u003e detected, and their AMR profile were mostly described in proportion.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical clearance\u003c/h3\u003e\n\u003cp\u003e This study was granted ethical approval by the College of Veterinary Medicine Animal Research Ethics Committee of Addis Ababa University, with reference number VM/ERC/02/09/16/2024 (ANNEX 18). All procedures were executed by skilled professionals according to the guidelines and regulations established by the university's ethics committee. The welfare and well-being of the animals that participated in this study were ensured throughout the research. Before the commencement of the study, verbal consent was obtained from all farm owners for both the questionnaire interview and the collection of milk and fecal samples from their animals.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003ePrevalence of\u003c/b\u003e \u003cb\u003eSalmonella\u003c/b\u003e \u003cb\u003eBased on Bacteriological Identification\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 200 samples were collected from three separate sources, namely dairy farms, milk vendors, and restaurants, for bacterial examination. Out of these, 2% (4/200) of the samples tested positive for \u003cem\u003eSalmonella\u003c/em\u003e. Specifically, 2.1% (95% CI: 0.7\u0026ndash;6.3), 3/144 of the farm samples and 3.57% (95% CI: 0.44\u0026ndash;23.7), and 1/28 of the milk vendor samples were found to have salmonella. However, no \u003cem\u003eSalmonella\u003c/em\u003e was detected in any of the cheese or yogurt samples collected from the restaurants. In general, of the 4 isolates, three were isolated from samples collected from dairy farms, whereas on were isolated from milk vendors. The study revealed a higher prevalence of \u003cem\u003eSalmonella enterica\u003c/em\u003e at the farm level in comparison to milk vendors (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003ePrevalence of \u003cem\u003eSalmonella\u003c/em\u003e from milk and milk products in Bishoftu town, Central Ethiopia\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=\"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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample source\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u0026nbsp;of\u0026nbsp;samples examined\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSalmonella\u003c/em\u003e positive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDairy farm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBulk milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFecal sample\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePooled floor swap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSwap\u0026nbsp;of\u0026nbsp;milk container\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMilk seller\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRaw milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSwap\u0026nbsp;of\u0026nbsp;milk container\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRestaurants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCheese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYogurt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePearson chi2(7)\u003c/p\u003e \u003cp\u003eP-Value\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6025\u003c/p\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of \u003cem\u003eSalmonella\u003c/em\u003e Based on Farm types\u003c/h2\u003e \u003cp\u003eFrom the total of 41 dairy farms enrolled in this study (5 small scales, 34 medium scales and 3 large scales), the overall prevalence of \u003cem\u003eSalmonella\u003c/em\u003e was 7.32%, with most samples testing negative (92.68%). Of these farms, 1 was small and the remaining 2 were medium-sized. From these, 1/41 (2.43%) and 2/41 (4.88%) \u003cem\u003eSalmonella\u003c/em\u003e isolates were obtained from small-size and medium-size farms respectively; and no \u003cem\u003eSalmonella\u003c/em\u003e was isolated from large-scale dairy farms. The Pearson chi-squared test revealed 9.65 with a p-value of 0.047. This suggests a statistically significant association between sample type and the occurrence of the pathogen across dairy farms (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\u003ePrevalence of \u003cem\u003eSalmonella\u003c/em\u003e in small, medium and large-scale dairy farms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSample type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eFarm size*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSmall scale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMedium scale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLarge scale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"8\" rowspan=\"9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBulk milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(2.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(97.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSwap\u0026nbsp;of\u0026nbsp;milk\u0026nbsp;container\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFloor swap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFecal sample\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(2.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(97.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(5.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(7.32%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32(94.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38(92.68%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003ePearson chi2(4) = 9.6471\u003c/p\u003e \u003cp\u003eP-value = 0.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003e*\u003c/em\u003e Number of small-scale farms\u0026thinsp;=\u0026thinsp;5, medium scale\u0026thinsp;=\u0026thinsp;34 and large-scale farm\u0026thinsp;=\u0026thinsp;3\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eAntimicrobial Susceptibility Profiles of\u003c/b\u003e \u003cb\u003eSalmonella\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe study revealed that the common antimicrobials used in the farms were oxytetracycline, fixed combinations of penicillin\u0026thinsp;+\u0026thinsp;streptomycin (pen strep), and sulfonamide in 100%, 100% and 65.9% of the farms, respectively. \u003cem\u003eSalmonella\u003c/em\u003e isolates were subjected to an AST against 8 selected antimicrobial agents. Accordingly, 100%, 75%, and 75% of the isolates were found to be susceptible to gentamicin, amoxicillin-clavulanic acid, and ciprofloxacin, respectively. On the other hand, 75%, 75%, and 50% of the isolates were resistant to amoxicillin, streptomycin, and tetracycline (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003eAntimicrobial susceptibility profile of \u003cem\u003eSalmonella\u003c/em\u003e isolated from cow milk and its product from the dairy farms and milk vendors in Bishoftu town, central Ethiopia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAntimicrobial Class\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAntimicrobials tested\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eThe number of isolates tested\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eStatus\u0026nbsp;of\u0026nbsp;antimicrobial\u0026nbsp;agent\u0026nbsp;against the isolate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eR\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI\u003c/p\u003e \u003cp\u003e(%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eB-lactam\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\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmoxicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\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\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStreptomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\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\u003eTMP-SXT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuinolones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCiprofloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eKey: R\u0026thinsp;=\u0026thinsp;resistant, I\u0026thinsp;=\u0026thinsp;Intermediate, S\u0026thinsp;=\u0026thinsp;susceptible, %=percent; TMP-SXT\u0026thinsp;=\u0026thinsp;Trimethoprim-Sulfamethoxazole; AMC\u0026thinsp;=\u0026thinsp;Amoxicillin-Clavulanic acid\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eMultidrug Resistance Profile of\u003c/b\u003e \u003cb\u003eSalmonella\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultidrug resistance (MDR) profile of \u003cem\u003eSalmonella\u003c/em\u003e isolated from bulk milk samples, fecal samples and floor swap collected from dairy farms and raw milk collected from milk vendors showed 75% (n\u0026thinsp;=\u0026thinsp;3/4) of the isolates were resistant to more than two classes of antibiotics. \u003cem\u003eSalmonella\u003c/em\u003e isolates from fecal samples showed high resistance to four classes of antibiotics while from bulk milk the isolates showed resistance to three classes of antibiotics. Additionally, raw milk collected from milk vendors showed resistance to a minimum of two classes of antibiotics as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultidrug resistance profile of \u003cem\u003eSalmonella\u003c/em\u003e\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=\"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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibiotics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSource\u0026nbsp;of\u0026nbsp;MDR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber\u0026nbsp;of\u0026nbsp;antibiotic classes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAX, CIP, TE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBulk milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAX,\u0026nbsp;TE,\u0026nbsp;S TMP-SXT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFecal sample\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAX, S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFloor swaps\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRaw milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOverall\u0026nbsp;MDR%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3 (75%)\u003c/b\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\u003eAX, amoxicillin; CIP, ciprofloxacin; TE, Tetracycline; S; Streptomycin; TMP-SXT; Trimethoprim-Sulfamethoxazole; MDR; multidrug resistance\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGlobally, \u003cem\u003eSalmonella species\u003c/em\u003e are recognized as prominent foodborne pathogens and rank as the third leading cause of death among diarrheal illnesses in human populations. The primary reservoir of this pathogen is in animals, with transmission to humans predominantly occurring through the consumption of animal-source foods including cow milk and its products (Ferrari et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Contamination of the environment and along the food chain with bacteria is often attributed to the presence of animal and human wastes that have been contaminated by bacterial pathogens (Abrar \u003cem\u003eet al.\u003c/em\u003e, 2020).\u003c/p\u003e \u003cp\u003eThe result of the present research indicated that the overall prevalence of \u003cem\u003eSalmonella enterica\u003c/em\u003e based on the OmniLog system was 2% (4/200); of which 2.44%, 0%, 4.76%, and 2.44% were from bulk milk, swab of milk container, fecal sample and floor swab at dairy farms, 3.5% from raw milk and swab of milk container at milk vendors and 0% and 0% cheese and yogurt from restaurant, respectively.\u003c/p\u003e \u003cp\u003eIn the present study among the sample types, 2.44% of \u003cem\u003eSalmonella enterica\u003c/em\u003e were isolated from bulk milk samples at dairy farms which is consistent with the previous research conducted in different locations. Specifically, it aligns closely with the results reported by Liyuwork \u003cem\u003eet al\u003c/em\u003e. (2013) in Addis Ababa, Ethiopia, and by Van \u003cem\u003eet al\u003c/em\u003e. (2013) in the United States of America where a prevalence rate of 2.1% and 2.6% were reported respectively. Similarly, the prevalence rate of \u003cem\u003eSalmonella\u003c/em\u003e isolated from milk samples in Egypt, as reported by Ahmed \u003cem\u003eet al\u003c/em\u003e. (2014) was 1.5% and in Jigjiga town by Reta \u003cem\u003eet al\u003c/em\u003e. (2016), was 3.3%, which is within the range of the current study's findings.\u003c/p\u003e \u003cp\u003eAdditionally, the prevalence rate reported by Murinda et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) in the USA was 2.24%, further supporting the consistency of the present study's results. However, the prevalence of \u003cem\u003eSalmonella\u003c/em\u003e isolated from bulk milk in this study is relatively higher than the report of Abunna et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Dadi et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) which was 0% and 0.7% at Meki and Sebata town Oromia, Ethiopia respectively. On the other hand, from Dire Daw (18.75%) by Tesfaye \u003cem\u003eet al.\u003c/em\u003e (2013), Central Ethiopia (10%) by Geletu \u003cem\u003eet al\u003c/em\u003e. (2023) and reports from Gondor (6.0%) by Ejo et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) are much higher than the current investigation.\u003c/p\u003e \u003cp\u003eThe difference in the relative amount of the bacteria present in milk between the current study and previous research carried out in various study areas in Ethiopia could be explained by variations in the potential risk factors contributing to the occurrence of \u003cem\u003eSalmonella\u003c/em\u003e in milk. Several factors, such as milking procedures, milk handling practices, hygiene and management practices, stocking density, use of contaminated utensils, housing type, animal movement, milking environment, ventilation, and production facilities in different areas, are examples of the main risk factors that influence the occurrence of \u003cem\u003eSalmonella\u003c/em\u003e (Abunna et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Gebeyehu et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gezahegn et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, methods employed in the research areas may also be a factor in the variation in the relative isolation rate of \u003cem\u003eSalmonella.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eEven though the current study isolated and identified only 2.44% of the \u003cem\u003eSalmonella\u003c/em\u003e from the bulk milk, compared to previous studies, this could pose serious health risks to humans by causing \u003cem\u003eSalmonellosis\u003c/em\u003e in high-risk populations like newborns, infants, the elderly, and people with immune-compromised, who are susceptible to \u003cem\u003eSalmonella\u003c/em\u003e infections at a lower infective dose than healthy adults. Because dairy products are frequently consumed in Ethiopia without being properly boiled (Geletu et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), it is a source of \u003cem\u003eSalmonella\u003c/em\u003e infection.\u003c/p\u003e \u003cp\u003eIn the current study, an isolation rate of 4.76% for \u003cem\u003eSalmonella enterica\u003c/em\u003e was recorded in fecal samples. This finding is consistent with prior research conducted by Geletu \u003cem\u003eet a\u003c/em\u003el. (2023), who reported a similar prevalence rate of 4.7% in central Ethiopia. Additionally, the observed prevalence aligns with the results documented by Gezahegn et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) in the Bedele and Nekemte districts of western Ethiopia, where a prevalence rate of 2.97% was reported. Factors that could explain this consistency include the possibility that common problems with animal husbandry practices, sanitation, and hygiene could have an impact on the observed prevalence rates irrespective of geographical location.\u003c/p\u003e \u003cp\u003eIn this study, the fecal prevalence of \u003cem\u003eSalmonella\u003c/em\u003e was found to be lower than that reported in previous studies conducted by Abunna et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) in Modjo town, Ethiopia, who documented a higher prevalence rate of 7.7% and 12% prevalence rate which was reported by Khan et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) in the Republic of Korea. Additionally, our results were lower than those reported by Hailu et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) in Northern Ethiopia. The observed differences in prevalence rates between our study and previous research can be due to various factors, including variations in sampling methods, duration of sampling period, environmental conditions, animal management practices, animal husbandry, biosecurity measures, sanitation protocols and geographical variability. Additionally, variations in laboratory techniques and procedures can affect the accuracy and comparability of prevalence estimates across studies.\u003c/p\u003e \u003cp\u003eThe prevalence rate of \u003cem\u003eSalmonella\u003c/em\u003e isolated from floor swabs in the present study was 2.44%. This finding is consistent with previous studies by Gezahagn \u003cem\u003eet al\u003c/em\u003e. (2023) in the town of Bedelle and Nekemte in western Ethiopia and by Geletu et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) in central Ethiopia, where the prevalence rate in dairy farms was reported to be 5% in both studies. The consistency of prevalence rates in these studies could be attributed to similar environmental conditions, management practices and biosecurity measures applied on dairy farms in these regions. Factors such as poor hygiene, animal overcrowding and inadequate cleaning and disinfection protocols could contribute to the presence of \u003cem\u003eSalmonella\u003c/em\u003e on dairy farm floors.\u003c/p\u003e \u003cp\u003eThe average prevalence rate of \u003cem\u003eSalmonella\u003c/em\u003e isolated from raw milk at milk vendors in the present study was found to be 3.5%, which agrees with the report of Tusa et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in Asella Town Oromia, Ethiopia with a prevalence rate of 3.3% and the finding of Jassim et al. (2020) in Iraq with the prevalence rate of 3%. However, the prevalence rate of the present finding was much lower than the report of Tesfay \u003cem\u003eet al\u003c/em\u003e. (2013), Ahmed \u003cem\u003eet al.\u003c/em\u003e (2020) in Bangladesh and the finding of Anukampa \u003cem\u003eet al\u003c/em\u003e. (2017) in India which was 41.7%, 45%, and 7.4% respectively.\u003c/p\u003e \u003cp\u003eThe prevalence of \u003cem\u003eSalmonella\u003c/em\u003e in raw milk varies across different milk vendors due to various factors. These include study design, sampling techniques, geographic locations, hygiene practices, and storage conditions. Larger sample sizes and advanced detection methods can yield higher prevalence rates. The prevalence of \u003cem\u003eSalmonella\u003c/em\u003e in raw milk can fluctuate depending on regional and local practices, environmental factors, animal health, and farm practices. The variation in hygiene practices during milk production, handling, and storage can increase the risk of bacterial contamination. Inadequate sanitation, equipment cleaning, and improper storage conditions can also increase the risk. The health status of dairy animals and the presence of infectious diseases can also impact the prevalence of \u003cem\u003eSalmonella\u003c/em\u003e in raw milk. Cross-contamination during milk handling and processing can introduce \u003cem\u003eSalmonella\u003c/em\u003e from external sources.\u003c/p\u003e \u003cp\u003eIn the present study, no \u003cem\u003eSalmonella\u003c/em\u003e was isolated from cheese and yogurt samples, which agreed with the findings of Ejo et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Tesfaw et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who reported no \u003cem\u003eSalmonella species\u003c/em\u003e found in cheese and yogurt. The absence of \u003cem\u003eSalmonella\u003c/em\u003e in cheese and yogurt samples can be attributed to several factors. Proper storage and handling practices, including adequate refrigeration and hygienic handling, help to prevent contamination after processing. The sensitivity of the sampling and detection methods can also influence the absence of \u003cem\u003eSalmonella.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eIn this study, an attempt was made to evaluate and compare the isolation rate of \u003cem\u003eSalmonella\u003c/em\u003e in dairy farms of different herd sizes, namely small, medium, and large. The result showed out of 41 dairy farms (3 large-scale, 34 medium-scale and 5 small-scale dairy farms) the total prevalence rate of \u003cem\u003eSalmonella\u003c/em\u003e was 7.32%. Our results showed that the isolation rate of \u003cem\u003eSalmonella\u003c/em\u003e was significantly comparable between small and medium-sized farms. However, in this cross-sectional study, there was no \u003cem\u003eSalmonella\u003c/em\u003e isolated from large-scale dairy farms. Several factors could contribute to this study's lack of \u003cem\u003eSalmonella\u003c/em\u003e isolation from large dairy farms. Some possible reasons could be strict biosecurity measures: Large dairy farms may have stricter biosecurity protocols in place to prevent the introduction and spread of pathogens, including \u003cem\u003eSalmonella\u003c/em\u003e, as compared to small-scale dairy farms. Management practices, such as regular cleaning and disinfecting facilities, can help reduce the spread of \u003cem\u003eSalmonella\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eAntimicrobial resistance is a growing worldwide issue in human and veterinary health, affecting both developed and developing countries. The growing use of antimicrobial drugs in food animal production and humans was a significant contributor to the establishment of bacterial resistance (Gebremedhin et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In the current investigation, \u003cem\u003eSalmonella\u003c/em\u003e isolates (n\u0026thinsp;=\u0026thinsp;4) were evaluated against eight frequently used antimicrobials using CLSI-2022 guidance. Antimicrobial susceptibility testing revealed 75%, 75%, and 50% resistance to amoxicillin, streptomycin, and tetracycline respectively. In comparison, 100% sensitivity to gentamycin was identified, followed by 75%, 75%, 50%, and 50% sensitivity to amoxicillin-clavulanic acid, ciprofloxacin, tetracycline, and ampicillin, respectively.\u003c/p\u003e \u003cp\u003eThe current findings revealed that 75% of the isolates were resistant to two or more classes of antibiotics, which was lower than the report of Fesseha et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who documented the MDR rate of 96.4% from selected dairy farms in Hawasa town. However, these findings were higher than those previously reported by Tesfaw et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who documented a 50% MDR of \u003cem\u003eSalmonella\u003c/em\u003e isolate. The possible reasons for the high AMR level of \u003cem\u003eSalmonella\u003c/em\u003e might be due to the increasing rate of irrational use of antimicrobials in dairy farms, frequent usage both in livestock and public health, use of counterfeit drugs in animal husbandry (Farhan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), self-medication due to easy access to antimicrobials without prescription in the public health sector, and administration of subtherapeutic doses.\u003c/p\u003e \u003cp\u003eThe current investigation found 75% amoxicillin resistance, which was greater than the findings of Beyene et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Fesseha et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) in Asella and Hawasa Town, Ethiopia, who reported resistance rates of 58.3% and 25%, respectively. The observed high resistance to streptomycin is not surprising, as these antimicrobials are commonly used in all farms to manage bacterial infection. The streptomycin resistance in the current study is consistent with previous results in Addis Ababa, as reported by Zewdu and Cornelius (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), who recorded a resistance rate of 75% among food items and personnel. However, the results of our research's resistance rate were lower than those reported by Ketema et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Obaidat and Stringer (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which were 80% and 89.3%, respectively.\u003c/p\u003e \u003cp\u003eOn the other hand, our data suggested a greater resistance rate than the studies by Abra \u003cem\u003eet al\u003c/em\u003e. (2020), Geletu et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and Beyene et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) who documented a 60%, 46% and 41.7% resistance rate respectively. The resistance profile towards tetracycline was 50%, which is comparable with the findings of Mulaw (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), (52.8%) among lactating cows in dairy farms in Bahir Dar Town, Ethiopia. However, it is interesting to note that the tetracycline resistance rate found in the current study exceeds that of Xu et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) in the United States, which was 28% lower than the report of Fesseha et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who recorded a resistant rate of 96.4%. This difference in resistance rates might be due to the increasing use of inappropriate antimicrobials on dairy farms. Such methods provide selection pressure, which increases the survival and growth of bacterial strains containing resistance genes (Fesseha et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As a result, such action may contribute to the variations in resistance profiles found among studies. The growing frequency of antibiotic resistance highlights the critical need for extensive antimicrobial management procedures to prevent the emergence and spread of resistant bacterial strains.\u003c/p\u003e \u003cp\u003eThe present results showed that \u003cem\u003eSalmonella\u003c/em\u003e isolates were susceptible to gentamycin and with a susceptibility rate of 100%. This was consistent with the reports of Tesfaw et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Abunna et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Beyene \u003cem\u003eet al\u003c/em\u003e. (2020) who documented a resistant rate of 100% but, higher than 73.3% and 75% reported by Addis et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Tadesse and Anbessa, respectively. Additionally, the susceptibility rate of ciprofloxacin was 75% which was lower than the report of 83.3% documented by Addis et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The variation in ciprofloxacin effectiveness in Ethiopian dairy farming might be related to drug type, different bacterial strains, resistance gene evolution, and limited use in Ethiopian animal production. The Misuse of antimicrobials in livestock may lead to the emergence and spread of pathogens that are harmful to human, animal and environmental health (Hirwa et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). One of the major contributors to the rise of AMR is antibiotic misuse (Gebeyehu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which is linked to an antimicrobial knowledge gap.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe present study revealed the occurrence of contamination of cow milk and its products with \u003cem\u003eSalmonella enterica\u003c/em\u003e along the milk value chain at farms and milk vendors. The isolations of the bacteria from bulk milk, fecal samples, and floor swabs of the cow environment were found to be the potential sources of milk contamination at the farms and milk vendors. The presence of \u003cem\u003eSalmonella enterica\u003c/em\u003e in bulk milk at the farm level and milk vendors indicates that there was cross-contamination of milk possibly because of Salmonella shedding in cattle feces, poor animal hygiene and housing conditions, contact with contaminated water or feed, fecal contamination of milking equipment or milk storage tanks, unsanitary milking practice, poor hygiene of milk handlers/vendors, improper storage and incomplete or improper antibiotic treatment. The study has also revealed the possibility of a public health risk posed due to \u003cem\u003eSalmonella enterica\u003c/em\u003e in the study area. In general, the assessment of AMR profile of \u003cem\u003eSalmonella\u003c/em\u003e in dairy farms is critical for safeguarding public health, ensuring food safety, minimizing economic losses, and promoting the overall well-being of animals, the environment, and humans. By understanding the prevalence and dynamics of \u003cem\u003eSalmonella\u003c/em\u003e in dairy environments, proactive measures can be taken to prevent contamination, reduce risks, and protect both the dairy industry and consumers. Therefore, creating public awareness about good milk handling practices, milk-borne diseases, and their prevention for dairy farmers and consumers should be implemented.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Addis Ababa University. We would like to appreciate dairy farmers for their cooperation during data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL.T.: Conceptualization; Investigation; Formal analysis; Data Collection; Writing-original draft, Writing-review \u0026amp; Editing T.B.: Conceptualization, Investigation; Data Collection; Writing-review \u0026amp; Editing F.A: Conceptualization; Methodology; Writing-review \u0026amp; Editing, Fund Acquisition; Supervision; Writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was approved, and ethical clearance was obtained from the Institutional Review Board of the College of Veterinary medicine and Agriculture\u003c/p\u003e\n\u003cp\u003eSciences, Addis Ababa University (VM-ERC 02/09/16/2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLogistics for data collection is financially supported by Addis Ababa University\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbrar A, Beyene T, and Furgasa. 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(2022) Salmonella (non-typhoidal). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/factsheets/detail/salmonella-(non-typhoidal)\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/factsheets/detail/salmonella-(non-typhoidal)\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Y, Tao S, Hinkle N, Harrison M, Chen J. Salmonella, including antibiotic-resistant Salmonella, from flies captured from cattle farms in Georgia, USA. Sci Total Environ. 2018;616:90\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZewdu E, Cornelius P. Antimicrobial resistance pattern of Salmonella serotypes isolated from food items and personnel in Addis Ababa, Ethiopia. Trop Anim Health Prod. 2009;41(2):241\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\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":"AMU and AMR, KAP assessment, Milk vendors, and S. enterica","lastPublishedDoi":"10.21203/rs.3.rs-5353585/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5353585/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e \u003cem\u003eSalmonella\u003c/em\u003e is a significant foodborne pathogen, with milk and milk products commonly implicated in its transmission. However, limited information is available regarding the direct link between antimicrobial use (AMU), dairy hygiene practices, and antimicrobial resistance (AMR) in \u003cem\u003eSalmonella\u003c/em\u003e strains isolated from dairy products in Bishoftu town.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eCross-sectional research was done from October 2023 to April 2024 to assess dairy farmers' antimicrobial usage (AMU) and hygiene practices and the occurrence of antimicrobial resistance (AMR) profiles of \u003cem\u003eSalmonella\u003c/em\u003e isolated from raw cow milk and its products. Two hundred samples were collected from dairy farms, milk vendors, and restaurants and analyzed using standard microbiological methods. Using the OmniLog system, \u003cem\u003eSalmonella enterica\u003c/em\u003e was successfully identified. Then, the antimicrobial susceptibility was evaluated using the Kirby-Bauer disc diffusion technique. Data were analyzed using STATA version 14.2.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOverall, 2% (n\u0026thinsp;=\u0026thinsp;4) of the samples tested positive for \u003cem\u003eS. enterica\u003c/em\u003e. Of the 4 isolates, 3 were identified in dairy farm samples, whereas 1 were isolated from milk vendors. However, no \u003cem\u003eSalmonella\u003c/em\u003e was identified in cheese or yogurt samples obtained from the restaurants. Regarding the AMR profile, \u003cem\u003eS. enterica\u003c/em\u003e isolates were resistant to amoxicillin (75%), streptomycin (75%), and tetracycline (50%). Resistant to two or more antimicrobials were identified in 75% of the isolates.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study indicated contamination of cow milk and its products with \u003cem\u003eS. enterica\u003c/em\u003e. Therefore, appropriate control measures, including awareness creation among personnel and improving hygienic practices at the milk value chains is recommended to mitigate cross-contamination.\u003c/p\u003e","manuscriptTitle":"Detection and Antimicrobial Resistance Profile of Salmonella Isolated From Raw Cow Milk and Its Products in Bishoftu Town, Central Ethiopia: Implication for Public Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-25 15:55:33","doi":"10.21203/rs.3.rs-5353585/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2024-12-29T18:24:58+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-11-20T08:28:24+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-07T11:53:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-31T07:01:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"One Health Outlook","date":"2024-10-31T02:34:25+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":"b0d39f49-eb5a-4747-865b-7f5bb9b6eb59","owner":[],"postedDate":"November 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-17T16:05:22+00:00","versionOfRecord":{"articleIdentity":"rs-5353585","link":"https://doi.org/10.1186/s42522-025-00134-y","journal":{"identity":"one-health-outlook","isVorOnly":false,"title":"One Health Outlook"},"publishedOn":"2025-03-15 15:58:31","publishedOnDateReadable":"March 15th, 2025"},"versionCreatedAt":"2024-11-25 15:55:33","video":"","vorDoi":"10.1186/s42522-025-00134-y","vorDoiUrl":"https://doi.org/10.1186/s42522-025-00134-y","workflowStages":[]},"version":"v1","identity":"rs-5353585","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5353585","identity":"rs-5353585","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}