Systematic Review and Meta-Analysis of Coliform Bacteria and Antibiotic Resistance in Mastitic Cow Milk in Ethiopia

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The quality assessment was performed using the AMSTAR-2 tool. The pooled proportion, the rate of resistance, and a 95% confidence interval were calculated with a random effects model using R software version 4.1.3. Funnel plots, and Eggers were used to assess publication bias. Results Twenty six articles were included for this meta-analysis. The overall pooled proportion of mastitis associated coliform bacteria was 9% (95% CI: 7-11.65%).Substantial heterogeneity was observed in included studies ( I 2 = 90.6%; P <0.01).Among the major coliform bactera, Eshercia spp had the highest pooled prevalence at 12%, followed by Enterobacter spp at 8%, and Klebsiella spp at 6%. Sub-analysis by level of mastitis, the proportion of occurrence of coliforms isolates was higher 24% (15–37%) compare with subclinical bovine mastitis 15% (10–22%). The subgroup of subgroup analysis of studies under clinical mastitis, Escherichia isolstes was highest proportion (14%), followed Enterobacter spp (9%) and Klebsiella spp (7%) while in subclinical masttis Escherichia was highest proportion (10%), and followed by Klebsiella spp (7%) and Enterobacter spp (5%). In study region, the highest proportion was reported in Somali (53%), followed by Tigray (18%), Amhara (11%), Oromia (9%), SNNPR (8%), AA (7%) and Sidama (6%). Erythromycin (82%) and pencillin (81%) were the higest resistance rate for the treatment of mastitis associated Eshercia spp . The resistance rate of Kelbesila spp for aminoglycoside, sulphonamides, beta-lactm, chloramphenicol and tetracycline was 60%, 49%, 43%, 35% and 22%, respectively. In the present meta-analysis, Escherichia isolates were identified as the most common coliforms in intramammary gland infections. The current investigation supports the claim that cow milk can be considered a significant source of Escherichia spp . The study found that the emergence of antibiotic resistance in Escherichia spp could pose a severe risk to consumers in Ethiopia, emphasizing the importance of strict surveillance and the implementation of effective hygiene measures in dairy farms and milk production. Animal Science Systematic Review and Meta-Analysis of Coliform Bacteria and Antibiotic Resistance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Milk and various other dairy commodities possess valuable nutritional properties, encompassing proteins, lipids, minerals, and vitamins, which are regularly consumed by a vast number of individuals worldwide (Ababu, Endashaw and Fesseha, 2020 ). In regions south of the Sahara, such as Ethiopia, milk production is predominantly overseen by minuscule-scale cultivators (Gebreyohanes et al., 2021 ). The dairy sector plays a significant role in alleviating poverty and reducing malnutrition, particularly in rural and semi-urban areas, while also serving as a source of income for mainly female, small-scale farmers (Webster, 2022 ). However, dairy products serve as an optimal environment for the propagation of various bacterial pathogens (Karmaker, Das and Iqbal, 2020 ). Mastitis, a preeminent endemic infectious ailment afflicting dairy cattle on a global scale. This affliction imposes significant financial burdens upon dairy producers and the milk processing sector, manifesting in reduced milk output, alterations in milk composition, the discarding of milk, escalated costs for replacement, treatment, and veterinary services (Ali Yusuf-Isleged, 2022 ). On average, the collective cost of mastitis-induced failures is approximated to be $ 147 annually per cow, primarily due to the losses incurred in milk production and culling, which represents between 11–18% of the gross margin per cow each year (Hogeveen, Steeneveld and Wolf, 2019 ). A notable 70% of these overall losses are attributed to the harm inflicted upon mammary tissue, resulting in diminished milk production (Zhao and Lacasse, 2008 ). In addition to the substantial economic drawbacks associated with this condition, mastitis poses a significant zoonotic threat and has been linked to the proliferation and rapid emergence of multidrug-resistant strains on a global scale (Pol and Ruegg, 2007 ; Hogeveen, Steeneveld and Wolf, 2019 ) Mastitis typically arises from the adherence, invasion, and colonization of bacteria within the mammary gland [GÜRLER, Sun1 Sun1]. The classification of mastitis depends on whether it presents clinically or sub-clinically. The clinical manifestation is characterized by a rapid onset, accompanied by swelling and redness in the affected quadrant. On the other hand, sub-clinical mastitis (SCM) can be challenging to detect, as there may be no obvious changes in the milk or clinical signs in the cow, even when the somatic cell count exceeds 200,000 cells/mL. [V. Tanči The etiology of mastitis is attributed to environmental bacteria that are not retained on the teat and infectious microorganisms that persist and accumulate on the skin and in teat wounds. A multitude of disease-causing microorganisms, numbering over 137, have been documented [Nazmul Hoque). Bacteria, in particular, are the most frequently identified culprits [bradely]. The majority of bacterial infections arise from various species of staphylococci, gram-negative rods, and streptococci, notably lactose-fermenting enteric-originating microorganisms referred to as coliforms (Radostits et al., 2007; Junaidu et al., 2011). 483E among the most prevalent types of bacteria responsible for mastitis is the Coliform bacterium. Abegewi Coliform bacteria, commonly found in the digestive system, soil, and manure, are considered normal inhabitants. Even in well-managed dairy herds, these bacteria are ubiquitous in the cow's surrounding environment and are challenging to completely eradicate [Peek]. According to documented cases, 32% of instances of coliform mastitis exhibited bacteremia, or the presence of bacteria in the bloodstream [27, 28]. Approximately 10% of coliform-induced clinical mastitis cases conclude with a fatal outcome [29]. The primary genera of coliform bacteria accountable for clinical mastitis [24] include Enterobacter, Klebsiella , and Escherichia . The most frequently encountered Gram-negative bacteria are Escherichia coli and Klebsiella spp which are the principal environmental pathogenic bacteria belonging to the Enterobacteriaceae family within the coliform group. Escherichia coli is isolated in around 80% of coliform mastitis cases(25,26).balemi et al The primary categories of coliform bacteria accountable for the occurrence of clinical mastitis [24] encompass Enterobacter, Klebsiella, and Escherichia [23]. The most frequently detected Gram-negative bacteria are Escherichia coli and Klebsiella spp which constitute the predominant pathogenic bacteria inhabiting the environment and belong to the Enterobacteriaceae family within the coliform group [Redding]. Escherichia coli and Klebsiella pneumoniae are microorganisms that are found in milk and are opportunistic pathogens in both humans and animals. They are responsible for causing a wide range of infections, including diarrhea, urinary tract infections, pneumonia, wound infections, septicemia, hemolytic uremic syndrome, and nosocomial infections, particularly meningitis in infants [Struelens, Slama]. Escherichia coli , typically infect the mammary glands during the dry period and can progress to inflammation and clinical mastitis during early lactation. This can result in both local and sometimes severe systemic clinical symptoms. However, if the infection remains localized in the mammary gland without systemic involvement, it is not recommended to treat it with antibiotics. This is because antibiotic treatment could exacerbate the inflammatory response due to bacterial death and the release of lipopolysaccharide (LPS), which may lead to a poor prognosis and worsen the animal's welfare. Clinical mastitis can exhibit severe systemic clinical manifestations. Many of the inflammatory and systemic changes observed in severe coliform mastitis occur as a result of the release of lipopolysaccharide (LPS) endotoxin, which is a component of the bacterial cell wall. This release leads to the activation of cytokine and arachidonic acid–derived mediators of inflammation and the acute phase response. Escherichia coli O157:H7 is commonly associated with foodborne illnesses, and it can result in life-threatening infections such as hemorrhagic colitis, abdominal pain, bloody diarrhea, hemolytic uremic syndrome, and kidney failure [Mersha, Jarboui]. Milk and other dairy products are often contaminated with E. coli O157: H7 due to direct exposure to feces resulting from poor handling systems [bacon, Belanger ´ 1,]. Improper milking hygiene, inadequate house hygiene, the absence of post-milking teat dipping, the use of lubricant during milking by contact laborers, and the lack of order in milking cows of different ages are all potential factors that contribute to the contamination of dairy products and the high prevalence of E. coli O157: H7 [Radostits, 2016]. The treatment of mastitis in cattle involves the use of several antimicrobial medicines. Antimicrobials used to treat mastitis typically make up a large fraction of all the antibiotics used at a dairy farm (González Pereyra et al., 2015; Kuipers et al., 2016). The dairy farms may be a source of antimicrobial-resistant human pathogenic bacteria, particularly E. coli that produces extended spectrum beta-lactamases [masses] and E.coli that is resistant to colistin [Brennan]. Widespread use of third-generation cephalosporin in dairy cattle for the treatment and prevention of mastitis [olvier,USAD(diry] as well as other infections [pol, Wichmann] may cause the enterobacteriaceae that produces extended-spectrum beta-lactamase [Massé]. balemi et al Misuse and overuse of antimicrobials in humans and livestock has led to the emergence of antimicrobial resistant bacterial strains compromising the effectivenessof antimicrobial therapy [Davies, cantas]. In Sokoto State, Nigeria, a research found that E. coli accounted for 9.78% of the samples, followed by Klebsiella spp . (4.35%), and Enterobacter spp . (1.09%). [Junaidu, 2011]. A cross-sectional investigation conducted in Hawass Town, Ethiopia, found 200 distinct species of bacteria; nevertheless, the most frequently discovered gram-negative staining bacterial pathogens were E. Col (12.5%), Enterobacter spp . (5%), and Klebsiella spp . (2.5%) (Megerssa et al., 2012). In Khartoum, Sudan, raw milk was used in a study where the majority of coliform isolates were E. Col (32%), Enterobacter spp. (29.2%) and Klebsiella spp . (19.4%) Megersa Antimicrobial resistance (AMR) has been acknowledged as a highly significant peril to the well-being of individuals and animals involved in the production of food. The dynamics of AMR in developing nations, particularly in rural community settings, remain insufficiently comprehended owing to an inadequate awareness of the AMR [Ingle]. The utilization of antibiotics in food animals, such as cattle, is anticipated to increase by 67% in BRICS countries (Brazil, Russia, India, China, and South Africa) by 2030 [van, Wichmann]. Approximately 20–80% of the antibiotics administered to livestock are discharged into the environment, where they persist [Agga]. The excessive usage of antibiotics in livestock has also led to the emergence of antibiotic-resistant bacteria and genes [van]. The World Health Organization (WHO) has recently released a list of antibiotic-resistant priority pathogens that pose a significant threat to human health. Among the reported dangers, coliforms, including E. coli , were identified as one of the most pivotal categories of bacteria that are resistant to multiple drugs, leading to treatment failures and posing threats in medical institutions. pathogens In Ethiopia several studies have been conducted over the years on human patients, livestock, foods and the environment and AMR is increasing rapidly [Seboxa, Ibrahim]. For example, the resistance of Escherichia coli ( E. coli ) and Klebsiella spp to last-resort third-generation cephalosporins and carbapenems antibiotics has reached up to 54% [ WHO, Iwu-Jaja].Antibiotics. It is crucial to compile the results of different studies conducted in various areas and at different times in order to assess the extent of these problems at the national level within a specific time frame. Additionally, it is important to have a comprehensive understanding of these issues across the entire country, as this knowledge can inform future intervention programs aimed at evidence-based disease control and prevention. Understanding the prevalence and antimicrobial resistance rate of coliform bacteria associated with bovine mastitis is of utmost importance in improving therapeutic interventions and preventive measures. Conducting research on this pathogenic organism contributes to a better understanding of its epidemiology and the patterns of antibiotic resistance exhibited by coliform isolates in lactating cows. Furthermore, conducting microbiological and antibiotic resistance assessments of mastitis-associated coliform bacterial isolates plays a crucial role in safeguarding public health and minimizing economic losses in the dairy industry. To the best of our knowledge, this meta-analysis represents the first attempt to summarize the epidemiology and distribution of coliform bacteria isolates in dairy cows in Ethiopia. Thus, the purpose of this systematic review and meta-analysis was to offer a comprehensive estimation of the proportion and antibiotic resistance rate of mastitis-associated coliform bacteria isolates in milk among lactating cows in Ethiopia. What are the major coliform bacteria isolates in dairy cattle? What is the over all prevalence of coliform bacteraia isolates causing milk spoilage in dairy cattle? Which type of coliform genera is the most prevalent in dairy cattle? What is the pooled and indiviual antibiotic resistance rate for the treatment of mastitis associated coliforms? Methods The literature search was carried out between October and March 2023. A comprehensive analysis of articles that reported on the total proportion of major coliform bacteria associated with mastitis and assessed the rate of resistance was performed using the PRISMA checklist (Page et al., 2021 ). This process was carried out in seven key steps: determining the eligibility criteria for studies, identifying the information sources to be used, developing a search strategy, defining the outcome variable, extracting data, evaluating the quality of the studies, synthesizing the data, and conducting statistical analysis. Descrpition of study stetings The research was undertaken in Ethiopia, a nation situated in the horn of Africa, encompassed by 3° 00′–150 °00′ N latitude and 320 °30′–480 °00′ E longitude. This country boasts a sizeable area of 1.04 million km 2 and is home to a population of 94.10 million, making it the second most populous country in Africa, following Nigeria. Ethiopia's agricultural potential is remarkable, with an estimated 70, 52.5 and 42.9 million heads of cattle, sheep, and goats, respectively (CSA, 2021). The country's diverse topography forms the basis of several agro-climatic zones, with areas above 2300 m above sea level (m.a.s.l.) considered highland and surrounded by a temperate transition zone between 1500 and 2300 m.a.s.l. Areas below 1500 m.a.s.l. are classified as lowlands Search Strategy A comprehensive and thorough search strategy was implemented in order to detect all pertinent studies. Various databases, including PubMed, Google Scholar, Web of Science, as well as other manual approaches, were employed for the purpose of conducting literature searches. The search was performed by three field experts (Veterinary microbiology, Veterinary pharmacy and Veterinary Clinica Medicine) to avoid reviewer bias.The research question was “what are the proportion/ prevelenec/ and its antibiotic resistsance of coliform causing bovine mastitis in Ethiopia?”Searching MeSH terms used were (bacterial mastitis OR coliform bacterial infection OR enterobacter OR Escherichia spp OR kelbesila spp OR E. coli ) AND (epidemiology OR prevalence OR infection rate) AND (cattle OR dairy cows OR bovine OR animals) AND (resistance rate OR antibiotic resistance) AND (mastitis) AND (Ethiopia OR Amhara region OR Afar region OR Oromia region OR Tigray region OR Somalia region OR SNNRP). A restriction was placed on the language of publication as English. All identified studies were imported to EndNote 20 software to remove duplicates. Study eligibility criteria Inclusion criteria This meta-analysis includes all of the primary descriptive studies that have been published in the English language that document the occurrence of genera Escherichia, Klebsiella , and Enterobacter in dairy cattle. Inclusion criteria were (I) articles with clear estimation of the proportion of each baeterial isolates, the strains have to be isolated from clinical and /or subclinical bovine mastitis (II) any observational studies capturing the prevalence of the main coliform baceterial isolates, (III) study animals became restricted to domestic cattle commonly used for milk production(cattle), (IV) samples had to be collected from animals which had not been experimentally infected, (V) bacterial isolates were identified at least in genus level, (VI)geographical location (Ethiopia). Exclusion criteria The following types of studies were not included in the analysis: those involving camels or other species, those with unclear or imprecise estimates of bacterial species in relation to the affected host, review articles, duplicates, abstract-only studies, qualitative studies or KAP questionnaire-based studies, book chapters, case reports, editorials, short communications, opinions, or studies without original data. Intervention studies lacking baseline data on the association between animal exposure and disease were also excluded from the meta-analysis. Definition of outcome variable In our review we have two outcome variables; 1) Prevealnce of coliforms 2) AMR of coliforms. Therefore, in the first case, the number of coliform isolets over the total number of bacterial isolstes in milk smaple used to estimate the prevalnce of mastitis associated coliforms. In second case, the number of AMR isolates over the total number of isolates was used to calculatethe ColiformAMR prevalence. Data extraction The selected studies were subjected to a thorough eligibility assessment, and the relevant data were independently extracted by two investigators (M.D and M.G). The data extraction process involved the creation of two tables in a word document and an Excel spreadsheet. The final database included 26 articles that focused on the prevalence of coliform bacterial pathogens in raw milk and 15 articles that estimated the pooled antibiotic resistance rate in raw milk. The extracted data included the name of the primary author, year of publication, year of study, geographical location, region, species/genera of coliform bacteria, sample size, number of coliform bacteria isolates, diagnostic methods, data collection methodologies, and proportion (prevalence). Some of the elements were specific to certain bacterial pathogens and varied across the different data sources. Disagreements were resolved by discussion and consultation with a third author, who was a senior author. Study quality assessment An independent quality assessment was conducted by two researchers (M.D and A.S) using the AMSTAR-2 tool (supplement file). The tool consists of 15 questions that evaluate the methodological quality of both randomized and non-randomized trials of health interventions. This critical appraisal quality assessment tool was used to ensure the reliability and validity of the findings of this systematic review. Data synthesis and statistical analysis The restricted maximum likelihood method was employed to calculate within- and between-study variability, and to estimate the pooled prevalence and 95% confidence intervals using a random effects model. This approach was utilized for the overall meta-analysis, as well as for the resistance rate, heterogeneity, and weight of each study. The "metaprop" function of the "meta" package version 4.1.3-0 in R statistical software was used to perform a proportional meta-analysis for the estimation of coliform isolate proportion and its resistance rate, utilizing data extracted from the number of events (coliform isolates) and the total number of bacterial isolates. Pooled proportions were estimated using a logit transformation in a logistic-normal random-effect regression model, as described by Nyaga et al. (2014) [36], while a mixed effect logistic regression model was used for the subgroup analysis. Investigation of heterogeneity The Cochran's Q test (reported as the p-value), τ 2 (between study variance)and inverse variance index (I 2 ) were used to assess the sources of heterogeneity, which describes the percentage of observed total variation between studies that is due to heterogeneity rather than chance. As explained by Higgins and Thompson [ 16 ], the I 2 index was estimated to represent low, moderate, and high heterogeneity, if this corresponds to I 2 values of 25%, 50%, and 75%, respectively. Heterogeneity was deemed to be statistically significant if the I 2 value exceeded 50% and the Q test revealed a P value of less than 0.10. The degree of study heterogeneity has been evaluated using a forest plot diagram. The forest plot diagram displayed the weights, magnitude of effects, and 95% confidence intervals for each study. Sub-group sets and bias assesment To determine specific between-study variability, a subgroup analysis of the proportion of the major coliform bacteria in bovine mastitis was performedby using as a factor variablel include publicationyear, study location or regions, genera of bacteria (Eschercia, Kelbesisla and eneterobacter) and the level mastitis( clinical and subclinical). Publication bias was visualized using funnel plot diagramsand Egger’s regressiontest. Egger's regression test is used to test the funnel-plot symmetry. Results The results of this systematic review and Meta analysis includes article search results, overveiw of the inclded studies, syntehnsis of results( meta analysis), heterogenity and bias assesments and subgroup analysis. Search Results As shown in PRISM 2020 flow-chart (Fig. 1 ), a total of 1476 articles in various electronic databases were searched, from which were excluded after article duplication assessment (n = 30), records were marked as ineligible by automation tools (n = 101), and records were removed for other reasons (n = 110). Among 1135 articles, 571articles were excluded by article title and abstract screening and 664 studies were reports searched for retrieval and five hundred nine (n = 509) articles were reports not retrieved. One hundred fifthy five (n = 155) articles were reports being evaluated for eligibility, and one hundred twenty nine (n = 129) of them were excluded for various reasons. Finally, tewnty six (n = 26) studies were included in systematic review and meta-analysis. Overviewof included articles The characteristics of the studies related to each coliform isolates are intricately described in a step-by-step manner. The study animals comprised of dairy cattle which are lactating cows. A total of 26 independat articles were considered for the analysis for all prevalence coliforms in associated with mastitis and 44 articles based on type of coliform isolates. In our investigation, we found most of the isoalted coliforms are Escherichia spp (n = 25), Klebsiella spp (n = 12) and eneterobacter spp (n = 7). However, one article may include two and/ or three of the bacterial coliform genera.The included studies for this systematic review and meta-analysis were conducted in different parts of Ethiopia between 2008 and 2023.The majority of these studies were conducted in the southern (oromia reginal states) and central regions of Ethiopia and studied in btween 2010, 2011 and 2012. Only one study was found in Somali regional state. Methods of diagnosis (CMT and bacterial culture) and bacteriological isolation and characterizationin milk samples were culturally examined according to the procedures described by Quinn et al. (2002). Study designs (cross-sectional) and type of sample (milk) were almost similar. So it helps to reduce the variablity of between studies.The included studies in each region were 14 (32%) in Oromia, 9(20%) in AA,7 (16%) in SNNPR, 6(13%) in Sidama,3(6%) in Amhara, 3(6%) in Tigray and 1(2%) in Somali. In this systematic review, 28 (Wubshet et al., 2017 ) cattle served as the minimum sample size and 1019 cattle were used as the maximum sample size (Boggale et al., 2018 ).To evaluate the proportion of mastitis associated coliform isolates in Ethiopia among lactating cows, 11441dairy cows were used in this case. The prevalence of mastitis associated coliform baceteria isolates ranged between 1% and 53% (Getahun et al., 2008 ; Reta, Bereda and Alemu, 2016 ).The detailed characteristics of the included studies are presented in Table 1 Table 1 the charachterstics of studies included in Meta- analysis (n = 44) First Author Study year Region Stu.design, St Type sample MDx TAE TBI TCB NCI PCB (Dereje et al., 2018 ) 2014–2015 AA CS, PS milk CMT, BC 186 97 Escherichia spp 6 0.062 (Dereje et al., 2018 ) 2014–2015 AA CS, PS milk CMT, BC 186 97 Klebsiella spp 2 0.021 (Etifu. Melesse and Tilahun Minyahil, 2019) 2011–2012 Oromia CS, SR milk CMT, BC 111 138 Escherichia spp 13 0.094 (Etifu. Melesse and Tilahun Minyahil, 2019) 2011–2012 Oromia CS, SR milk CMT, BC 111 138 Klebsiella spp 8 0.058 (Etifu. Melesse and Tilahun Minyahil, 2019) 2011–2012 Oromia CS, SR milk CMT, BC 111 138 enterobacter SPP 6 0.043 (Zenebe, Habtamu and Endale, 2014 ) 2011–2012 Tigray CS, SR milk CMT, BC 322 698 Escherichia spp 146 0.209 (Ababu, Endashaw and Fesseha, 2020 ) 2018–2019 AA CS, SR milk BC 210 51 Escherichia spp 11 0.216 (Moges et al, 2017 ) 2009–2010 Amhara CS, SR milk CMT, BC 322 164 Escherichia spp 7 0.043 (Boggale et al., 2018 ) 2009–2010 Oromia CS, SR milk CMT, BC 1019 1493 Klebsiella spp 148 0.099 (Boggale et al., 2018 ) 2009–2010 Oromia CS, SR milk CMT, BC 1019 1493 Escherichia spp 161 0.108 Takle and berihe., 2016 2010–2011 Sidama CS, SR milk CMT, BC 96 52 Escherichia spp 2 0.038 Takle and berihe., 2016 2010–2011 Sidama CS, SR milk CMT, BC 96 52 Klebsiella spp 7 0.135 Takle and berihe., 2016 2010–2011 Sidama CS, SR milk CMT, BC 96 52 enterobacter SPP 2 0.038 (Adane et al., 2012 ) 2010–2011 Oromia CS, SR milk CMT, BC 460 641 Escherichia spp 81 0.126 (Tegegne et al., 2020 ) 2015–2016 Amhara CS, SR milk CMT, BC 303 187 Escherichia spp 25 0.134 (Fesseha Haben, Mesfin Mathewos, Saliman Aliye, 2021) 2018–2019 Oromia CS, SR milk CMT, BC 283 144 Escherichia spp 44 0.306 (Getahun et al., 2008 ) 2018–2019 Oromia CS, SR milk CMT, BC 500 195 Escherichia spp 2 0.010 (Girma et al., 2012 ) 2010–2011 Oromia CS, SR milk CMT, BC 384 121 Escherichia spp 7 0.058 (Girma et al., 2012 ) 2010–2011 Oromia CS, SR milk CMT, BC 384 121 Klebsiella spp 3 0.025 Redeat et al.,2014 2008–2009 AA CS, SR milk CMT, BC 200 86 Escherichia spp 6 0.070 (Megersa et al., 2012 ) 2009–2010 sidama CS, SR milk CMT, BC 245 200 Escherichia spp 25 0.125 (Megersa et al., 2012 ) 2009–2010 Sidama CS, SR milk CMT, BC 245 200 Klebsiella spp 5 0.025 (Megersa et al., 2012 ) 2009–2010 Sidama CS, SR milk CMT, BC 245 200 Enterobacter spp 10 0.050 (Mekonnen and Tesfaye, 2010 ) 2009–2010 Oromia CS, SR milk CMT, BC 206 95 Escherichia spp 7 0.074 (Mekonnen and Tesfaye, 2010 ) 2009–2010 Oromia CS, SR milk CMT, BC 206 95 Enterobacter spp 10 0.105 (Mekibib, B., Furgasa, M., Abunna, F., Megersa, B. and Regassa, 2010 ) 2008–2009 AA CS, SR milk CMT,BC 107 153 Escherichia spp 7 0.046 (Mekibib, B., Furgasa, M., Abunna, F., Megersa, B. and Regassa, 2010 ) 2008–2009 AA CS, SR milk CMT, BC 107 153 Klebsiella spp 5 0.033 (Wubshet et al., 2017 ) 2012–2013 SNNPR CS, SR milk CMT, BC 28 72 Escherichia spp 7 0.097 (Wubshet et al., 2017 ) 2012–2013 SNNPR CS, SR milk CMT, BC 28 72 Klebsiella spp 5 0.069 (Yohannes.K and and Alemu.B, 2018) 2017–2018 SNNPR CS, SR milk CMT, BC 245 51 Escherichia spp 7 0.137 (Yohannes.K and and Alemu.B, 2018) 2017–2018 SNNPR CS,SR milk CMT,BC 245 51 Klebsiella spp 5 0.098 Tefera et al.,2022 2019–2021 AA CS.PS milk CMT,BC 203 226 Escherichia spp 24 0.106 Tefera et al.,2022 2019–2021 AA CS.PS milk CMT,BC 203 226 Enterobacter spp 30 0.133 Tefera et al.,2022 2019–2021 AA CS.PS milk CMT,BC 203 226 Klebsiella spp 10 0.044 (Kitila and Kebede, 2021 ) 2017 Oromia CS.PS milk CMT,BC 532 153 Enterobacter spp 47 0.307 (Balemi et al., 2021 ) 2017–2018 Oromia CS, SR mil CMT,BC 171 62 Escherichia spp 6 0.097 (Bitew, Tafere and Tolosa, 2010 ) 2009–2010 Amhara CS.Srsm milk CMT, BC 302 79 Escherichia spp 16 0.203 (Haftu, Taddele and Gugsa, 2012 ) 2009–2010 Tigray CS, SR milk CMT, BC 305 128 Escherichia spp 35 0.273 (Haftu, Taddele and Gugsa, 2012 ) 2009–2010 Tigray CS,SR milk CMT, BC 305 128 Klebsiella spp 11 0.086 (Reta, Bereda and Alemu, 2016 ) 2013–2014 Somali CS,SR milk CMT,BC 120 133 Escherichia spp 70 0.526 (Abera et al., 2012 ) 2010–2011 SNNPR CS, SR milk CMT,BC 245 217 Escherichia spp 23 0.106 (Abera et al., 2012 ) 2010–2011 SNNPR CS, SR milk CMT,BC 245 217 Klebsiella spp 17 0.078 (Abera et al., 2012 ) 2010–2011 SNNPR CS,SR milk CMT, BC 245 217 Enterobacter spp 8 0.037 Yusuf and Husen, 2023 2021 Oromia CS,LS milk CMT, BC 56 112 Escherichia spp 12 0.107 MDx = Methods of diagnosis, TAE = total animal examine, TBI = total bacteria isolates, NCI = number of coliform isolates, TCB = type of Coliform bacteria, PCB = proportion of Coliform bacteria, CS = crossectional, PS = purposive sampling, SR = simple randm sampling, St = sampling technique, Srsm = systematic random sampling Meta-analysis, testing heterogeneity and bias assessment The meta-analysis encompassed a total of 44 articles that examined mastitis associated coliform bacteria. It is worth noting that certain articles were included multiple times due to their relevance in similar years but in different bacterial genera and/or spp. The studies that were included demonstrated a considerable level of heterogeneity (I 2 = 90.6%: τ2 = 0.6321; P < 0.01). The estimated pooled proportion of mastitis associated coliform among overall bacterial isolates was determined to be 9% (95% CI: 7-11.65%; Fig. 2 ). The variability between the studies was statistically significant (Q = 456.52, DF = 43, p < 0.0001). Similarly, the heterogeneity and outliers of the studies were graphically represented. It is noteworthy that not all studies fell within the range bounded by the two confidence interval lines (95% range). The Galbraith test confirmed the presence of inter-study heterogeneity, as almost 95% of the studies were outside the confidence interval. More than ten out of the 44 studies exceeded the limits of the 95% confidence interval depicted in the chart. The funnel plots (Fig. 4 ) and the Egger’s regression asymmetry did not indicate the presence of publication bias (p > 0.05) (Fig. 3 ). Subgroup analysis Due to significant variability across studies, a sub-analysis was conducted based on the level of mastitis, types of coliform bacteria, study area or region, and publication year. As shown in Fig. 4 , the proportion of coliform isolates at the genus level was higher in clinical mastitis (24%, 95% CI: 15–37%) than in subclinical bovine mastitis (15%, 95% CI: 10–22%), with a study weight of 41.6% and 58.3%, respectively. Considerable variability was also observed across studies for both categories of mastitis (I 2 = 82%, p < 0.01 for clinical mastitis and I 2 = 84%, p < 0.01 for subclinical mastitis). To further investigate the proportion of coliform isolates in each category of clinical and subclinical mastitis, a subgroup of subgroup analysis was conducted (Supplementary materials). The subgroup of subgroup analysis for clinical mastitis based on types of coliform bacteria isolates showed that Escherichia had the highest proportion (14%), followed by Enterobacter spp (9%) and Klebsiella spp (7%). The heterogeneity across studies was significant (I 2 = 72%, p < 0.01). For subclinical mastitis, the proportion of coliform genus bacteria was highest for Escherichia (10%), followed by Klebsiella spp (7%) and Enterobacter spp (5%). The heterogeneity across studies was also significant (I2 = 86%, p < 0.01 for Escherichia, I2 = 64%, p < 0.01 for Klebsiella spp , and I 2 = 93%, p < 0.01 for Enterobacter spp ). Sub-analysis based on the types of coliform in genus level, the included studies were categorized into three groups: Escherichia spp (n = 25), Klebsiella spp (n = 12), and Enterobacter spp (n = 7). Significant discrepancies were found in the sub-analysis of the proportion mastitis associated coliform isolates bytypes of coliforms.As shown in Figs. 5 , the subgroup analysis revealed that the pooled proportion of Escherichia in lactating cows was 12% (95% CI: 9% -16) and (I 2 = 93%: τ 2 = 0.7311; p < 0.01), followed by enterobacter SPPat 8% (95% CI: 4% − 16%) and (I 2 = 92%: τ 2 = 0.7816; P < 0.01) and Klebsiella spp at 6% (95% CI : 5% − 8% ) and (I 2 = 65% : τ 2 = 0.1614; P < 0.01).Test of heterogeneity showed that statistical significant difference (Q = 608.56; D.F. =2; p < 0.001). Subanalysis by region revealed significant heterogeneity between studies, and testing for subgroup differences suggests that there is a statistically significant subgroup effect (p < 0.001).Subgroup analysis of bovine mastitis associated coliform by region had shown the highest heterogeneity (I 2 = 90.91; p < 0.01) (Fig. 6 ) in Oromia region.Based on regional subgroup, the highest overall proportion of mastitis associated coliform bacteria was reported in Somali (53%), followed by Tigray (18%), Amhara (11%), Oromia (9%), SNNPR (8%), AA (7%)and Sidama (6%). In terms year of publication, sub analysis of publication year was carried out. Year of publication was categorized into at and before 2015, 2015–2019, at and after 2019. In this case we encountered considerable heterogeneity (I 2 \(\:\ge\:\) 89) in each group. The highest study heterogeneity (I 2 =92) was revealed in publication year in between 2015–2019. The sub-pooled proportion of mastitis associated coliform isolates was highest in the publication year after 2019(14%), followed 2015–2019 (9%) and before 2015 (8%) (Fig. 7 ). The subgroup difference test suggested that there was a statistically significant group effect (Q=5.78; DF=2; p<0.0001). Molecular characteristics and serotype of coliforms Molecular characterization of mastitis-causing pathogens allows monitoring of specific features at the strain level, such as transmission routes and antimicrobial resistance. Understanding the molecular nature of coliforms is essential to devise prevention and control strategies and reduce risk of the disease associated with these bacteria. However, from all the studies included in this review, only a single study was found that focused on molecular characteristics of coliforms from milk, specifically E.coli . This study used polymerase chain reaction (PCR) technique and characterized virulence genes of E. coli . The PCR result indicated that all (100%) of the tested isolates of E. coli carried the pal gene and 41.67% eaeA gene (EHEC). Among the eaeA gene-carried E. coli isolates, 40% carried the stx1 gene and 60% of them carried the stx2 gene (source: for mb). Some of the included studies have done the isolation and identification of E. coli O157: H7 was performed using techniques recommended by Quinn et al. [18]. Selection of articles for antibiotic resistance estimation One article was used multiple times for quantitative data analysis. The selection criteria for the chosen studies were as follows, (1) almost all of the included studies provided a comprehensive overview of the pathogen isolation rates for both clinical and sub-clinical bovine mastitis, (2) each article had conducted multiple antimicrobial susceptibility tests (3), the chosen articles had one of the genera or spp of coliform isolates and one other species in mastitis cows, (4) in each study,at least one genera or spp of coliform antimicrobial resistance rate was present, (5) the chosen article may or may not be included in the previous section of our meta-analysis which focused on the prevalence of mastitis associated coliform isolates, (6) we select articles which clearly estimated the proportion of antimicrobial resistance andsusceptibility, (7) we only selected articles that exclusively used milk as the primary sample for dairy cattle in Ethiopia. Finally, we only included studies that conducted the antimicrobial susceptibility test according to the criteria of the laboratory standards institute. Antiboitic resistance of mastitis associated coliform isolates In the management of bovine mastitis in Ethiopia, antibiotics are the sole essential component utilized in dairy farms and veterinary clinics. Currently, there exists no alternative for the treatment of bovine mastitis. The improper use of antimicrobials has contributed to the rise in antimicrobial resistance [Gelalch). The dairy farms in Ethiopia do not adhere to hygienic conditions. As coliform bacteria serve as an environmental source of mastitis, recurrent mastitis is a frequent occurrence. Due to the recurrent nature of the pathogen, antibiotics are frequently employed, thereby increasing the likelihood of resistance. The recovery rate is influenced by various factors including individual cow characteristics, management-related factors, and bacterial-associated factors such as strain and the presence of antimicrobial resistance, all of which play a role in determining the success of treatment [Mcdougall et al., 2007]. Coliform bacteria are prevalent in the cow's environment and are not easily eradicated, even in well-managed dairy herds (Jones and Bailey, 2009). The antimicrobial sensitivity test conducted in all the included studies utilized the Kirby-Baur disc diffusion method. Among a total of 1759 isolates of Escherichia spp, 626 exhibited antimicrobial resistance, while 445 out of a total of 1130 Kelbesila spp isolates were found to be resistant. Erythromycin exhibited the highest rate of resistance for the treatment of Escherichia spp (93%, 14/15), followed by Streptomycin (90%) as reported by Haftu et al. ( 2012 ) and Babu et al. (2020). Conversely, the minimum resistance rate (0%) was observed in gentamicin, cotrimazole, and oxytetracycline, as reported by Babu et al. (2020), Etifu and Tilahun (2018), and Moges et al. (2011). Further details of the included studies are presented in Table 2 . Table 2 various antimicrobials resistance rate in the treatment of mastitis associated Escherichia spp Author Type antibiotics Total Escherichia spp isolates N o . resitance Isolates RR (Reta, Bereda and Alemu, 2016 ) Gentamycin 70 21 0.300 (Haftu, Taddele and Gugsa, 2012 ) Erythromycin 15 14 0.933 (Haftu, Taddele and Gugsa, 2012 ) Co-trimoxazole 15 11 0.733 (Haftu, Taddele and Gugsa, 2012 ) Co-trimoxazole 70 12 0.171 (Balemi et al., 2021 ) Pencillin 4 4 1.000 (Reta, Bereda and Alemu, 2016 ) Chloramphenicol 70 15 0.214 (Balemi et al., 2021 ) Chloramphenicol 4 4 1.00 Ababu et al.,2020 Cloxacillin 11 11 1.00 (Boggale et al., 2018 ) oxytetracycline 158 40 0.250 (Reta, Bereda and Alemu, 2016 ) Amoxicillin 70 15 0.214 (Reta, Bereda and Alemu, 2016 ) Ampicillin 70 21 0.300 (Haftu, Taddele and Gugsa, 2012 ) Ampicillin 15 7 0.467 (Haftu, Taddele and Gugsa, 2012 ) Chloramphenicol 15 9 0.600 Ababu et al.,2020 Streptomycin 11 10 0.909 Ababu et al.,2020 Tetracycline 11 4 0.364 Ababu et al.,2020 oxytetracycline 11 0 0.000 Ababu et al.,2020 Co-trimoxazole 11 10 0.909 Ababu et al.,2020 Gentamycin 11 0 0.00 Ababu et al.,2020 Chloramphenicol 11 8 0.727 (Boggale et al., 2018 ) Streptomycin 158 62 0.39 (Boggale et al., 2018 ) Gentamycin 158 20 0.13 (Boggale et al., 2018 ) Ampicillin 158 46 0.29 (Boggale et al., 2018 ) Amoxicillin 158 35 0.22 (Boggale et al., 2018 ) Pencillin 158 128 0.81 (Boggale et al., 2018 ) Cloxacillin 158 53 0.34 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Ampicillin 13 5 0.385 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Gentamycin 13 6 0.462 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Co-trimoxazole 13 0 0.000 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Tetracycline 13 7 0.538 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Erythromycin 13 9 0.692 (Dereje et al., 2018 ) Tetracycline 6 2 0.333 (Dereje et al., 2018 ) Pencillin 6 6 1.000 (Dereje et al., 2018 ) Erythromycin 6 5 0.833 (Dereje et al., 2018 ) Gentamycin 6 0 0.00 (Dereje et al., 2018 ) Co-trimoxazole 6 0 0.00 (Moges et al, 2017 ) Tetracycline 5 3 0.60 (Moges et al, 2017 ) Chloramphenicol 5 0 0.00 (Moges et al, 2017 ) Streptomycin 5 1 0.200 (Moges et al, 2017 ) oxytetracycline 5 3 0.200 (Moges et al, 2017 ) Ampicillin 5 3 0.600 (Moges et al, 2017 ) Co-trimoxazole 5 0 0.600 (Moges et al, 2017 ) Erythromycin 5 5 0.000 (Girma et al., 2012 ) oxytetracycline 4 2 1.000 (Girma et al., 2012 ) Gentamycin 4 1 0.500 (Girma et al., 2012 ) Streptomycin 4 1 0.250 (Girma et al., 2012 ) Ampicillin 4 2 0.250 (Girma et al., 2012 ) Amoxicillin 4 1 0.500 (Girma et al., 2012 ) Pencillin 4 3 0.750 (Girma et al., 2012 ) Cloxacillin 4 1 0.250 *ASTM = Antibiotic susceptibility testing methodology, RR = Resistance Rate Pooled analysis of the antimicrobial resistanec rate In this review, we have uncovered a range of antibiotics that exhibit resistance, namely cotrimoxazole, gentamycin, erythromycin, pencillin, amoxacillin, ampicillin, chloramphenicol, and cloxacillin. The overall pooled prevalence of antimicrobial resistance (AMR) for E.coli in relation to the aforementioned antibiotics has been estimated at 43% (95%CI; 34.35%-52.09%), with a considerable level of heterogeneity indicated by an I2 value of 82.8% [78.0%; 86.6%] and an H value of 2.41 [2.13; 2.73]. Amongst the listed antibiotics, it has been observed that erythromycin (82%) and pencillin (81%) exhibit the highest rates of resistance when it comes to treating mastitis associated with Eshercia spp in lactating cows. However, Eshercia spp has shown a high susceptibility rate to gentamycin (79%) and amoxcillin (78%) amongst the listed antibiotics, indicating a lower resistance rate in the treatment of Eshercia spp such as E.coli. In the current pooled analysis results, Escherichia spp have demonstrated roughly similar resistance rates for cotrimazole (29%) and ampicillin (32%). Chloramphenicol (48%) and cloxacillin (55%) also exhibit nearly identical rates of resistance in the treatment of mastitis associated with Eshercia spp in lactating dairy cows. The current meta-analysis has also identified the source of heterogeneity between studies. Amongst the studies included, heterogeneity ranged from I 2 = 0–83% (Fig. 9 ). The subgroup analysis revealed that the maximum source of heterogeneity (83%) was found in the studies included in the cot-rimazole subgroup, while the minimum heterogeneity was recorded in studies under the subgroups of erythromycin, ampicillin, amoxaccillin, and pencillin. Antibiotic resistance rate for mastitis associated kelbesila spp From a total of 1130 isolates of kelbesila spp , 445 isolates were discovered to be resistant. In this particular study, a single article may examine multiple types of antibiotics, such as the work of (Haftu, Taddele and Gugsa, 2012 ), who identified Ampicillin, Erythromycin, Co-trimoxazole, and Chloramphenicol, among others. Similar studies have been conducted using the same methodology. Among the antibiotics considered in this study, the highest rate of resistance was observed for co-trimoxazole (85.7%; 6/7), followed by Gentamycin (80%; 147/118) ((Haftu, Taddele and Gugsa, 2012 ; Boggale et al., 2018 ). In contrast, kelbesila SPP exhibited high susceptibility to norfloxacin and doxycycline (100%) ((Etifu. Melesse* and Tilahun Minyahil, 2019 ). A meta-analysis revealed an overall pooled resistance rate of 42% [95%CI; 31–54%] for Kelbesila against all antimicrobials, with a significant heterogeneity of I2 = 86% [72%; 90.7%] (Fig. 10 ). As depicted in Fig. 11 , the overall pooled resistance proportion of Kelbesila spp to aminoglycosides, sulfonamides, beta-lactam, chloramphenicol, and tetracycline was 60%, 49%, 43%, 35%, and 22%, respectively. Furthermore, the overall antimicrobial data, number of isolates, and resistance rates are summarized in Table 3 . Table 3 resistance rate of kelbesila spp for various antimicrobials in bovine mastitis Author Type of antibioltics No. isolates Resistance isoaltes Rate (Haftu, Taddele and Gugsa, 2012 ) Ampicillin 7 3 0.429 (Haftu, Taddele and Gugsa, 2012 ) Erythromycin 7 7 1 (Haftu, Taddele and Gugsa, 2012 ) Clindamycin 7 5 0.714 (Haftu, Taddele and Gugsa, 2012 ) Co-trimoxazole 7 6 0.857 (Haftu, Taddele and Gugsa, 2012 ) Chloramphenicol 7 3 0.429 (Boggale et al., 2018 ) Streptomycin 147 58 0.395 (Boggale et al., 2018 ) Gentamycin 147 118 0.803 (Boggale et al., 2018 ) Oxytetracycline 147 33 0.224 (Boggale et al., 2018 ) Ampicillin 147 42 0.286 (Boggale et al., 2018 ) Amoxicillin 147 26 0.177 (Boggale et al., 2018 ) Pencillin 147 74 0.503 (Boggale et al., 2018 ) Cloxacillin 147 50 0.34 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Norfloxacin 8 0 0 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Ampicillin 8 5 0.625 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Gentamycin 8 1 0.125 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Doxycycline 8 0 0 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) co-trimoxazole 8 1 0.125 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Tetracycline 8 2 0.25 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Erythromycin 8 5 0.625 (Etifu. Melesse* and Tilahun Minyahil, 2019 ) Tetracycline 2 1 0.5 (Dereje et al., 2018 ) Pencillin 2 2 1 (Dereje et al., 2018 ) Erythromycin 2 2 1 (Dereje et al., 2018 ) Gentamycin 2 0 0 (Dereje et al., 2018 ) Co-trimoxazole 2 1 0.5 Discussion Milk, a perishable complete nutritious food is considered to be a good medium of growth for many of the microorganisms [FAO ].The majority of mastitis cases are of bacterial origin, with coliform bacteria being among the few predominant causative pathogens [Makovec, Bradley]. Abegewi There exists explicit data and an all-encompassing summary pertaining solely to the cow level and quarter level general prevalence of bovine mastitis (both clinical and subclinical). Nevertheless, there is an absence of comprehensive epidemiological information regarding the proportions and antibiotic resistance profile in relation to the etiological agents among the bacterial causes of mastitis, which encompasses coliform bacteria. We hope that recognizing the specific etiological agent of mastitis in dairy cattle is very essential to take special attention since each agent has its own characteristics, even it is important to make vaccine and /or other intervention for prevention and control of mastitis in dairy sector. Inline to this, understanding the occurrence rate and antimicrobial resistance rate of coliform bacteria associated with bovine mastitis is crucial in enhancing therapeutic interventions and preventive measures as the bacteria is endemic in Ethiopia. Therefore, conducting this systematic review and meta-analysis very useful to systematize and analyze existing information regarding to the etiological and resistance rate of coliform bacteria associated with bovine mastitis.This meta-analysis comprising twenty six observational studies which estimated the pooled proportion of bovine mastitis associated coliform among the bacterial pathogens causing mastitis in lactating cows in Ethiopia. They are typically acquired from the surrounding environment during the process of milking, as coliform organisms contaminate the teat canal and enter the udder when the teat-ends come into contact with an environmental site that is contaminated [Contreras]. Therefore, it is of utmost importance to enhance hygiene practices and minimize exposure of the teat ends to environmental contamination (source: Abegewi). The proportion of coliform isolates at the genus level was higher in cases of clinical mastitis (24%) compared to subclinical bovine mastitis (15%), with a study weight of 41.6% and 58.3% respectively. In contrast to our findings, Belayneh et al. (2014) reported that all (100%) coliform isolates were obtained from subclinical mastitis. Boggale et al. ( 2018 ) also found 1.3% coliform isolates from clinical mastitis and 98.7% coliform isolates from subclinical mastitis. In this current study, the higher prevalence of subclinical mastitis in comparison to the clinical form indicates the magnitude of the problem of subclinical mastitis and the insufficient attention it receives in terms of diagnosis and treatment (Source: Etifu). According to the analysis of proportions of the different types of coliform bacteria isolates found in cases of clinical mastitis, it was observed that Escherichia was the most prevalent (14%), followed by Enterobacter spp (9%) and Klebsiella spp (7%). Upon further analysis of the types of coliform bacteria at the genus level, it was observed that the coliform bacteria isolated from milk samples of mastitis cases were primarily E. coli (12%), followed by Klebsiella spp (8%) and Enterobacter spp (6%). Notably, E. coli stood out as the predominant coliform. This finding is consistent with the studies conducted by Ahmed and Shimamoto [48] in Egypt and Kateete et al. [18] in Kampala-Uganda, where these coliform genera were also isolated, with E. coli being the most prevalent. Similarly, Ngwa et al. [35] in Adamawa Cameroon reported E. coli as the predominant coliform among those associated with mastitis. (Source: Abegewi). In opposite of our finding, reported a higher proportion of Enterobacter spp (13.7%), followed by E.coli (7.0%), Klebsiella spp (3.2%). Makolo et al. [43] and Mbuk et al. [49] in Nigeria also reported that Klebsiella spp. as the predominant coliform. The differences in the relative occurrence of coliform bacteria could be due to differences in bacterial load of the various coliforms in the various environmental sources and the nature of the coliforms (Source: Abegewi). Based on the classification according to regional subgroup, the Somali subgroup exhibited the highest overall proportion of coliform bacteria associated with mastitis, with a reported rate of 53%. This was followed by the Tigray subgroup at 18%, the Amhara subgroup at 11%, the Oromia subgroup at 9%, the SNNPR subgroup at 8%, the AA subgroup at 7%, and finally the Sidama subgroup at 6%. This variation in proportions could potentially be attributed to disparities in awareness levels, treatment methodologies, milking practices, environmental conditions, and hygiene protocols across the observed regions. The variations in management practices among the dairy herds could potentially lead to an upsurge in the exposure and infection pressure on cows, ultimately resulting in heightened infection levels. Additionally, it is important to note that the variation in the prevalence of these pathogens may also be influenced by the number of studies conducted, the sample sizes utilized, and the breeds of animals included within each region (Bitew et al.) In their study, Bitew et al. found that the prevalence of mastitis differed between crossbreed and local breed cows, with crossbreeds exhibiting higher susceptibility compared to local breeds. The sub-pooled proportion of coliform isolates linked to mastitis was found to be highest (14%) in articles published after the year 2019.This was followed by the years 2015–2019, when the percentage was 9%, and the years prior to 2015, when the percentage was 8%. These results imply that the nation's rate of coliform bacterial infection in cows is rising with time. This could be related to the growth of dairy farms, which are frequently run by people who are not professionals in this field and who may not know enough about good hygiene practices, how to milk cows, or the reasons why milk gets contaminated before, during, or after milking. It is worth noting that these coliform bacteria are considered environmental pathogens, and their occurrence may be associated with inadequate management practices in terms of housing and bedding quality (Radostits et al., 2007). (Source: Abera et al). An additional factor contributing to the increase in mastitis related to coliforms may be the proliferation of exotic or hybrid breeds over time. The development and persistence of antibiotic resistance traits in pathogenic bacteria are associated with the utilization of antibiotics (13). Generally speaking, owners of herds and experts in animal health may be excessively and improperly using antibiotics, which could result in the emergence of antibiotic resistance. The World Health Organization's (WHO) report on antimicrobial resistance (AMR) reveals that there has been a concerning rises in the resistance of common bacteria in numerous regions across the globe. According to certain projections, the economic repercussions of AMR are expected to reach trillions of dollars in damages by the middle of the twenty-first century [3]. The overall pooled prevalnce of AMR rate of E.coli in the listed antibiotics was etimated 43% (95%CI; 34.35%-52.09%). From the given antibiotics, erythromycin (82%) and pencillin (81%) were the higest resistance rate for the treatment of mastitis associated Eshercia spp in lactating coaws. The development of resistance mechanisms in coliform bacteria have evolved rapidly, owing to the presence of selective pressures. Their defense mechanisms against antibiotics involves the production of antibiotic deactivating enzymes such as the several classes of β-lactamases (class A, B, C and class D of β-lactamases) or aminoglycoside modifying enzymeswith diverse activities (adenylation, acetylation or phosphorylation), changes in antibiotic targets such as alteration of penicillin binding proteins (PBPs), reduction of intracellular antibiotic concentration either by limiting the entrance of the antibiotic or facilitating its expulsion and point mutations in specific areas of DNA gyrase (for example genes gyrA and gyrB for resistance mechanism of K. pneumoniae against fluoroquinolone drugs. However, most coliform bacteria highly suspteblity rate for gentamycin and amoxcillin among the listed antibiotics which means it has lowest resistance rate in the treatment of Eshercia spp like E.coli. Antimicrobial resistance occurs when commensal or disease-causing organisms survive upon exposure to a concentration of the drug that would normally kill or inhibit their growth (kakullis, Nardomnn). The majority of bacteria examined in the present study displayed sensitivity towards Streptomycin, Gentamycin, and Norfloxacin. In contrast, a study conducted in Nigeria [ Mbuk) revealed a significant resistance among coliform bacterial isolates towards Streptomycin. This resistance could potentially be attributed to the excessive use of this antibiotic in the treatment of goat diseases within the study region. The observed sensitivity of bacterial isolates towards Streptomycin in this study can potentially be attributed to its limited utilization in mastitis treatment within the study area. Another study conducted in Ethiopia [Haftu] reported varying degrees of resistance among bacteria towards Chloramphenicol, Gentamycin, and Streptomycin. These studies demonstrate the existence of variations in antibiotic sensitivity based on geographical location and the utilization of specific antibiotics (Garcı´a-Rey). The prevalence of antimicrobial resistance has become a global concern, necessitating the implementation of international initiatives and the establishment of monitoring systems to assess resistance occurrence in all countries (Aarestrup, 2004). Overall, this meta-analysis highlights the substantial occurrence of coliform bacteria in bovine mastitis in Ethiopia, with a notably high level of resistance. In Ethiopia, the consumption of raw milk is a common practice throughout the country. Contaminated milk and milk products serve as the primary transmission pathway for certain coliform bacterial strains, such as E. coli O157: H7, from animals to humans (Fusco). Although the disease caused by E. coli is of great public health concern in the country, E. coli O157: H7 has received limited attention in previous studies. Furthermore, dairy farms may function as a reservoir for human pathogenic bacteria that are resistant to antimicrobial agents, particularly strains of E.coli that produce extended spectrum beta-lactamases. Consequently, the implementation of an extensive ten-point mastitis control plan is crucial. Certain components of this plan should be tailored specifically for Ethiopia, with a focus on raising awareness among farmers and milkers. For instance, the adoption of strategies such as establishing udder health goals, maintaining a clean and dry environment, ensuring animal comfort, maintaining comprehensive records, managing clinical mastitis during lactation, and implementing biosecurity measures are already being implemented by many larger farms.The evaluation of the antimicrobial resistance profile of various bacterial pathogens in bovine mastitis is of utmost importance in assessing the potential risk of disseminating resistant pathogens to humans. This systematic review has several limitations, which must be taken into consideration. Firstly, despite the vast quantity of literature that has been systematically reviewed, the Meta analysis depends on arelatively small number of articles, with just small number of studies included for the analysis of antimicrobial resistance.Secondly, the meta-analysis was limited to studies in Ethiopia, even no studies included in some of regions. This may limit the generalizability of the findings. It is important to note that our eligibility criteria were limited to articles published in English, which creates potential language bias. Thirdly, the review was not registerd in any prospective database. Conclusion The findings of the current meta-analysis have shown that the overall prevalence of coliform bacteria, the primary cause of bovine mastitis, has been estimated. Additionally, the study has evaluated the antimicrobial resistance profile of these bacteria. It is worth noting that the prevalence of coliform bacteria in bovine mastitis has increased in recent years (14%) compared to previous decades (8%). The highest proportion of coliform bacteria (18%) was found in the Tigray regional state in Ethiopia. Subgroup analysis revealed that among lactating dairy cows in Ethiopia, Escherichia had the highest pooled proportion, followed by Enterobacter spp and Klebsiella spp . Furthermore, a sub-analysis based on the level of mastitis showed that the proportion of coliform isolates at the genus level was higher in clinical mastitis (24%) than in subclinical bovine mastitis (15%).The meta-analysis also showed that the overall pooled resistance rate of Klebsiella for all antimicrobials was 42%, while E.coli showed a resistance rate of 43% in the treatment of bovine mastitis. Among the given antibiotics, erythromycin and penicillin exhibited the highest resistance rate for the treatment of mastitis associated with coliform bacteria. The information provided in this report can be of great assistance in making well-informed decisions regarding the control and prevention of coliform-associated bovine mastitis in Ethiopia. It emphasizes the importance of integrating veterinarians, pharmacists, and other healthcare professionals to reduce or control the spread of coliforms in dairy cows in Ethiopia. M. Radostits, K. W. Hinchcliff, S. H. Done, and W. Gr¨unberg, Mastitis in Veterinary Medicine, Elsevier Health Sciences, London, UK, 9th edition, 2016 World Health Organization, 2020. Global antimicrobial resistance surveillance system (GLASS) report: early implementation 2020. World Health Organization. GLASS|Global Antimicrobial Resistance Surveillance System (GLASS) 2020 ; World Health Organization (WHO): Geneva, Switzerland, 2020. Quinn PJ, Markey BK, Carter ME, Donelly WJ, Leonard FC (2002) Veterinary Microbiology and Microbial Disease. 2nd [Edn.], Blackwell Science Ltd, a Blackwell publishing Company, pp: 465–475. 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(2012) ‘Mastitis in Lactating Cows at Hawassa Town : Prevalence , Risk Factors , Major Bacterial Causes and Treatment Response to Routinely Used Antibiotics’, 7(2), pp. 86–91. doi: 10.5829/idosi.aejsr.2012.7.2.6391. Mekibib, B., Furgasa, M., Abunna, F., Megersa, B. and Regassa, A. (2010) ‘Bovine Mastitis : Prevalence , Risk Factors and Major Pathogens in Dairy Farms of Holeta’, 3(9), pp. 397–403. Mekonnen, H. and Tesfaye, A. (2010) ‘Prevalence and etiology of mastitis and related management factors in market oriented smallholder dairy farms in Adama ’, pp. 574–579. Moges et al (2017) ‘Aantimicrobial Susceptibility of Mastitis Pathogens from Smallholder Dairy Herds in and Around Gondar , Ethiopia’, (January). doi: 10.3923/javaa.2011.1616.1622. Page, M. J. et al. (2021) ‘The PRISMA 2020 statement : An updated guideline for reporting systematic reviews Asbj ø rn Hr o’, 88(March). doi: 10.1016/j.ijsu.2021.105906. Pol, M. and Ruegg, P. L. (2007) ‘Relationship Between Antimicrobial Drug Usage and Antimicrobial Susceptibility of Gram-Positive Mastitis Pathogens’, Journal of Dairy Science . Elsevier, 90(1), pp. 262–273. doi: 10.3168/jds.S0022-0302(07)72627-9. Reta, M. A., Bereda, T. W. and Alemu, A. N. (2016) ‘Bacterial contaminations of raw cow ’ s milk consumed at Jigjiga City of Somali Regional State , Eastern Ethiopia’. doi: 10.1186/s40550-016-0027-5. Tegegne, D. T. et al. (2020) ‘Study of Prevalence , Associated Risk Factors and Causative Bacteria of Bovine Mastitis in Ethiopia -’, 4(1), pp. 1–6. Webster, D. M. (2022) ‘Research to Guide the Increase of Dairy Products to Address Nutritional Deficiencies’, Journal of Innovation in Social Science , 3(1), pp. 40–48. Available at: https://www.aurora-pub.com/JISS/article/view/38%0Ahttps://www.aurora-pub.com/JISS/article/download/38/31. Wubshet, A. K. et al. (2017) ‘Incidence of heifer mastitis and identification of major associated pathogens in dairy farms at wolaita soddo town , southern Ethiopia’, 5(5), pp. 169–176. doi: 10.15406/jdvar.2017.05.00156. Yohannes.K and and Alemu.B (2018) ‘International Journal of Advanced Research in Biological Sciences Prevalence of Bovine Mastitis in lactating Cows and Associated risk factors in and around Wolayta Soddo , Southern Ethiopia’, 5, pp. 60–69. doi: 10.22192/ijarbs. Zenebe, N., Habtamu, T. and Endale, B. (2014) ‘Study on bovine mastitis and associated risk factors in Adigrat , Northern Ethiopia’, 8(4), pp. 327–331. doi: 10.5897/AJMR2013.6483. Zhao, X. and Lacasse, P. (2008) ‘Mammary tissue damage during bovine mastitis: causes and control.’, Journal of animal science , 86(13 Suppl), pp. 57–65. doi: 10.2527/jas.2007-0302. Jones GM, Bailey TL. Understanding the basics of mastitis. Virginia Cooperative Extension. Publication404–234. 2009. ttps://vtechworks.lib.vt.edu/bitstream/handle/10919/48392/404-233_pdf.pdf?sequence=1 Mcdougall S, Agnew KE, Cursons R, Hou XX, Compton CRW. Parenteral Treatment of Clinical Mastitis with Tylosin Base or Penethamate Hydriodide in Dairy Cattle. J Dairy Sci [Internet]. 2007;90(2):779–89. Available from: http://dx.doi.org/10.3168/jds.S0022-0302(07)71562-X CSA: Central statistical authority of Ethiopia: report on livestock and livestock characteristics (private peasant holdings). STATISTICAL BULLETIN 587 II. 2020. Radostits, K. W. Hinchcliff, S. H. Done, and W. Gr¨unberg, Mastitis in Veterinary Medicine, Elsevier Health Sciences, London, UK, 9th edition, 2016 World Health Organization, 2020. Global antimicrobial resistance surveillance system (GLASS) report: early implementation 2020. World Health Organization. GLASS|Global Antimicrobial Resistance Surveillance System (GLASS) 2020 ; World Health Organization (WHO): Geneva, Switzerland, 2020. Quinn PJ, Markey BK, Carter ME, Donelly WJ, Leonard FC (2002) Veterinary Microbiology and Microbial Disease. 2nd [Edn.], Blackwell Science Ltd, a Blackwell publishing Company, pp: 465-475. Additional Declarations The authors declare no competing interests. Supplementary Files SuppFile2Qualityassessmenttool.docx Figure 2 prisma quality asesment tool, AXIX Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-4941592","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":342410756,"identity":"7f348b77-2b73-4e12-8e10-9bc14dc622b5","order_by":0,"name":"Melkie Dagnaw 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analysis based on type coliform bacteria isolates in bovine mastitis\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4941592/v1/3d934ed56e36fd412f06efd0.png"},{"id":62979012,"identity":"df55d8e1-31a5-4f74-b8da-ba8972333e85","added_by":"auto","created_at":"2024-08-21 16:48:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":330671,"visible":true,"origin":"","legend":"\u003cp\u003esubgroup analysis of the prevalence mastitis associated coliforms in milk sample based on region\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4941592/v1/7de6c95c7d8dd1617dccdac0.png"},{"id":62979013,"identity":"54a651bf-3dee-41d2-a4fb-d2a9544322ed","added_by":"auto","created_at":"2024-08-21 16:48:37","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":347240,"visible":true,"origin":"","legend":"\u003cp\u003esubgroup analysis of the proportion of mastiti associated coliforms by publication year\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4941592/v1/19ebf923308be02c69e13dcc.png"},{"id":62978586,"identity":"4b49ede9-5d19-48a3-9fca-625803f0c1bf","added_by":"auto","created_at":"2024-08-21 16:40:37","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":314721,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 9 pooled resistance rate of each antimicrobials for the treatment coliform associated mastitis\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-4941592/v1/d180f8498eb3601f74ad0602.png"},{"id":62978581,"identity":"9291e9ff-34b4-4369-934c-d9b2972ce1b5","added_by":"auto","created_at":"2024-08-21 16:40:37","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":158632,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 10 pooled prevalence of AMR in the treatment of bovine mastitis associated \u003cem\u003eKelbesila\u003c/em\u003ebacteria\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-4941592/v1/5e2ec93978d65e7b1109b8f8.png"},{"id":62978584,"identity":"897dbc89-5fb7-4cbc-a171-23b0d99a647d","added_by":"auto","created_at":"2024-08-21 16:40:37","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":337265,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 11 subgroup analysis of the antimicrobial resistance of \u003cem\u003ekelbesila\u003c/em\u003e based on class of 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AXIX\u003c/p\u003e","description":"","filename":"SuppFile2Qualityassessmenttool.docx","url":"https://assets-eu.researchsquare.com/files/rs-4941592/v1/1b140da06a81346cd00b6553.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eSystematic Review and Meta-Analysis of Coliform Bacteria and Antibiotic Resistance in Mastitic Cow Milk in Ethiopia\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMilk and various other dairy commodities possess valuable nutritional properties, encompassing proteins, lipids, minerals, and vitamins, which are regularly consumed by a vast number of individuals worldwide (Ababu, Endashaw and Fesseha, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In regions south of the Sahara, such as Ethiopia, milk production is predominantly overseen by minuscule-scale cultivators (Gebreyohanes et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The dairy sector plays a significant role in alleviating poverty and reducing malnutrition, particularly in rural and semi-urban areas, while also serving as a source of income for mainly female, small-scale farmers (Webster, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, dairy products serve as an optimal environment for the propagation of various bacterial pathogens (Karmaker, Das and Iqbal, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMastitis, a preeminent endemic infectious ailment afflicting dairy cattle on a global scale. This affliction imposes significant financial burdens upon dairy producers and the milk processing sector, manifesting in reduced milk output, alterations in milk composition, the discarding of milk, escalated costs for replacement, treatment, and veterinary services (Ali Yusuf-Isleged, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). On average, the collective cost of mastitis-induced failures is approximated to be \u003cspan\u003e$\u003c/span\u003e147 annually per cow, primarily due to the losses incurred in milk production and culling, which represents between 11\u0026ndash;18% of the gross margin per cow each year (Hogeveen, Steeneveld and Wolf, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A notable 70% of these overall losses are attributed to the harm inflicted upon mammary tissue, resulting in diminished milk production (Zhao and Lacasse, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In addition to the substantial economic drawbacks associated with this condition, mastitis poses a significant zoonotic threat and has been linked to the proliferation and rapid emergence of multidrug-resistant strains on a global scale (Pol and Ruegg, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Hogeveen, Steeneveld and Wolf, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eMastitis typically arises from the adherence, invasion, and colonization of bacteria within the mammary gland [G\u0026Uuml;RLER, Sun1 Sun1]. The classification of mastitis depends on whether it presents clinically or sub-clinically. The clinical manifestation is characterized by a rapid onset, accompanied by swelling and redness in the affected quadrant. On the other hand, sub-clinical mastitis (SCM) can be challenging to detect, as there may be no obvious changes in the milk or clinical signs in the cow, even when the somatic cell count exceeds 200,000 cells/mL. [V. Tanči\u003c/p\u003e \u003cp\u003eThe etiology of mastitis is attributed to environmental bacteria that are not retained on the teat and infectious microorganisms that persist and accumulate on the skin and in teat wounds. A multitude of disease-causing microorganisms, numbering over 137, have been documented [Nazmul Hoque). Bacteria, in particular, are the most frequently identified culprits [bradely]. The majority of bacterial infections arise from various species of staphylococci, gram-negative rods, and streptococci, notably lactose-fermenting enteric-originating microorganisms referred to as coliforms (Radostits et al., 2007; Junaidu et al., 2011). 483E among the most prevalent types of bacteria responsible for mastitis is the Coliform bacterium. \u003cb\u003eAbegewi\u003c/b\u003e Coliform bacteria, commonly found in the digestive system, soil, and manure, are considered normal inhabitants. Even in well-managed dairy herds, these bacteria are ubiquitous in the cow's surrounding environment and are challenging to completely eradicate [Peek].\u003c/p\u003e \u003cp\u003eAccording to documented cases, 32% of instances of coliform mastitis exhibited bacteremia, or the presence of bacteria in the bloodstream [27, 28]. Approximately 10% of coliform-induced clinical mastitis cases conclude with a fatal outcome [29]. The primary genera of coliform bacteria accountable for clinical mastitis [24] include \u003cem\u003eEnterobacter, Klebsiella\u003c/em\u003e, and \u003cem\u003eEscherichia\u003c/em\u003e. The most frequently encountered Gram-negative bacteria are \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella spp\u003c/em\u003e which are the principal environmental pathogenic bacteria belonging to the Enterobacteriaceae family within the coliform group. Escherichia coli is isolated in around 80% of coliform mastitis cases(25,26).balemi et al\u003c/p\u003e \u003cp\u003eThe primary categories of coliform bacteria accountable for the occurrence of clinical mastitis [24] encompass Enterobacter, Klebsiella, and Escherichia [23]. The most frequently detected Gram-negative bacteria are \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eKlebsiella spp\u003c/em\u003e which constitute the predominant pathogenic bacteria inhabiting the environment and belong to the Enterobacteriaceae family within the coliform group [Redding].\u003c/p\u003e \u003cp\u003eEscherichia coli and Klebsiella pneumoniae are microorganisms that are found in milk and are opportunistic pathogens in both humans and animals. They are responsible for causing a wide range of infections, including diarrhea, urinary tract infections, pneumonia, wound infections, septicemia, hemolytic uremic syndrome, and nosocomial infections, particularly meningitis in infants [Struelens, Slama]. \u003cem\u003eEscherichia coli\u003c/em\u003e, typically infect the mammary glands during the dry period and can progress to inflammation and clinical mastitis during early lactation. This can result in both local and sometimes severe systemic clinical symptoms. However, if the infection remains localized in the mammary gland without systemic involvement, it is not recommended to treat it with antibiotics. This is because antibiotic treatment could exacerbate the inflammatory response due to bacterial death and the release of lipopolysaccharide (LPS), which may lead to a poor prognosis and worsen the animal's welfare. Clinical mastitis can exhibit severe systemic clinical manifestations. Many of the inflammatory and systemic changes observed in severe coliform mastitis occur as a result of the release of lipopolysaccharide (LPS) endotoxin, which is a component of the bacterial cell wall. This release leads to the activation of cytokine and arachidonic acid\u0026ndash;derived mediators of inflammation and the acute phase response.\u003c/p\u003e \u003cp\u003e \u003cem\u003eEscherichia coli\u003c/em\u003e O157:H7 is commonly associated with foodborne illnesses, and it can result in life-threatening infections such as hemorrhagic colitis, abdominal pain, bloody diarrhea, hemolytic uremic syndrome, and kidney failure [Mersha, Jarboui]. Milk and other dairy products are often contaminated with \u003cem\u003eE. coli\u003c/em\u003e O157: H7 due to direct exposure to feces resulting from poor handling systems [bacon, Belanger \u0026acute; 1,]. Improper milking hygiene, inadequate house hygiene, the absence of post-milking teat dipping, the use of lubricant during milking by contact laborers, and the lack of order in milking cows of different ages are all potential factors that contribute to the contamination of dairy products and the high prevalence of \u003cem\u003eE. coli\u003c/em\u003e O157: H7 [Radostits, 2016].\u003c/p\u003e \u003cp\u003eThe treatment of mastitis in cattle involves the use of several antimicrobial medicines. Antimicrobials used to treat mastitis typically make up a large fraction of all the antibiotics used at a dairy farm (Gonz\u0026aacute;lez Pereyra et al., 2015; Kuipers et al., 2016). The dairy farms may be a source of antimicrobial-resistant human pathogenic bacteria, particularly \u003cem\u003eE. coli\u003c/em\u003e that produces extended spectrum beta-lactamases [masses] and \u003cem\u003eE.coli\u003c/em\u003e that is resistant to colistin [Brennan]. Widespread use of third-generation cephalosporin in dairy cattle for the treatment and prevention of mastitis [olvier,USAD(diry] as well as other infections [pol, Wichmann] may cause the enterobacteriaceae that produces extended-spectrum beta-lactamase [Mass\u0026eacute;]. balemi et al\u003c/p\u003e \u003cp\u003eMisuse and overuse of antimicrobials in humans and livestock has led to the emergence of antimicrobial resistant bacterial strains compromising the effectivenessof antimicrobial therapy [Davies, cantas].\u003c/p\u003e \u003cp\u003eIn Sokoto State, Nigeria, a research found that \u003cem\u003eE. coli\u003c/em\u003e accounted for 9.78% of the samples, followed by \u003cem\u003eKlebsiella spp\u003c/em\u003e. (4.35%), and Enterobacter \u003cem\u003espp\u003c/em\u003e. (1.09%). [Junaidu, 2011]. A cross-sectional investigation conducted in Hawass Town, Ethiopia, found 200 distinct species of bacteria; nevertheless, the most frequently discovered gram-negative staining bacterial pathogens were \u003cem\u003eE. Col\u003c/em\u003e (12.5%), \u003cem\u003eEnterobacter spp\u003c/em\u003e. (5%), and \u003cem\u003eKlebsiella spp\u003c/em\u003e. (2.5%) (Megerssa et al., 2012). In Khartoum, Sudan, raw milk was used in a study where the majority of coliform isolates were E. Col (32%), Enterobacter spp. (29.2%) and \u003cem\u003eKlebsiella spp\u003c/em\u003e. (19.4%)\u003c/p\u003e\n\u003ch3\u003eMegersa\u003c/h3\u003e\n\u003cp\u003eAntimicrobial resistance (AMR) has been acknowledged as a highly significant peril to the well-being of individuals and animals involved in the production of food. The dynamics of AMR in developing nations, particularly in rural community settings, remain insufficiently comprehended owing to an inadequate awareness of the AMR [Ingle]. The utilization of antibiotics in food animals, such as cattle, is anticipated to increase by 67% in BRICS countries (Brazil, Russia, India, China, and South Africa) by 2030 [van, Wichmann]. Approximately 20\u0026ndash;80% of the antibiotics administered to livestock are discharged into the environment, where they persist [Agga]. The excessive usage of antibiotics in livestock has also led to the emergence of antibiotic-resistant bacteria and genes [van]. The World Health Organization (WHO) has recently released a list of antibiotic-resistant priority pathogens that pose a significant threat to human health. Among the reported dangers, coliforms, including \u003cem\u003eE. coli\u003c/em\u003e, were identified as one of the most pivotal categories of bacteria that are resistant to multiple drugs, leading to treatment failures and posing threats in medical institutions. pathogens\u003c/p\u003e \u003cp\u003eIn Ethiopia several studies have been conducted over the years on human patients, livestock, foods and the environment and AMR is increasing rapidly [Seboxa, Ibrahim]. For example, the resistance of \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eE. coli\u003c/em\u003e) and \u003cem\u003eKlebsiella spp\u003c/em\u003e to last-resort third-generation cephalosporins and carbapenems antibiotics has reached up to 54% [ WHO, Iwu-Jaja].Antibiotics.\u003c/p\u003e \u003cp\u003eIt is crucial to compile the results of different studies conducted in various areas and at different times in order to assess the extent of these problems at the national level within a specific time frame. Additionally, it is important to have a comprehensive understanding of these issues across the entire country, as this knowledge can inform future intervention programs aimed at evidence-based disease control and prevention.\u003c/p\u003e \u003cp\u003eUnderstanding the prevalence and antimicrobial resistance rate of coliform bacteria associated with bovine mastitis is of utmost importance in improving therapeutic interventions and preventive measures. Conducting research on this pathogenic organism contributes to a better understanding of its epidemiology and the patterns of antibiotic resistance exhibited by coliform isolates in lactating cows. Furthermore, conducting microbiological and antibiotic resistance assessments of mastitis-associated coliform bacterial isolates plays a crucial role in safeguarding public health and minimizing economic losses in the dairy industry. To the best of our knowledge, this meta-analysis represents the first attempt to summarize the epidemiology and distribution of coliform bacteria isolates in dairy cows in Ethiopia. Thus, the purpose of this systematic review and meta-analysis was to offer a comprehensive estimation of the proportion and antibiotic resistance rate of mastitis-associated coliform bacteria isolates in milk among lactating cows in Ethiopia.\u003c/p\u003e \u003cp\u003eWhat are the major coliform bacteria isolates in dairy cattle?\u003c/p\u003e \u003cp\u003eWhat is the over all prevalence of coliform bacteraia isolates causing milk spoilage in dairy cattle?\u003c/p\u003e \u003cp\u003eWhich type of coliform genera is the most prevalent in dairy cattle?\u003c/p\u003e \u003cp\u003eWhat is the pooled and indiviual antibiotic resistance rate for the treatment of mastitis associated coliforms?\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe literature search was carried out between October and March 2023. A comprehensive analysis of articles that reported on the total proportion of major coliform bacteria associated with mastitis and assessed the rate of resistance was performed using the PRISMA checklist (Page et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This process was carried out in seven key steps: determining the eligibility criteria for studies, identifying the information sources to be used, developing a search strategy, defining the outcome variable, extracting data, evaluating the quality of the studies, synthesizing the data, and conducting statistical analysis.\u003c/p\u003e\n\u003ch3\u003eDescrpition of study stetings\u003c/h3\u003e\n\u003cp\u003eThe research was undertaken in Ethiopia, a nation situated in the horn of Africa, encompassed by 3\u0026deg; 00\u0026prime;\u0026ndash;150 \u0026deg;00\u0026prime; N latitude and 320 \u0026deg;30\u0026prime;\u0026ndash;480 \u0026deg;00\u0026prime; E longitude. This country boasts a sizeable area of 1.04\u0026nbsp;million km\u003csup\u003e2\u003c/sup\u003e and is home to a population of 94.10\u0026nbsp;million, making it the second most populous country in Africa, following Nigeria. Ethiopia's agricultural potential is remarkable, with an estimated 70, 52.5 and 42.9\u0026nbsp;million heads of cattle, sheep, and goats, respectively (CSA, 2021). The country's diverse topography forms the basis of several agro-climatic zones, with areas above 2300 m above sea level (m.a.s.l.) considered highland and surrounded by a temperate transition zone between 1500 and 2300 m.a.s.l. Areas below 1500 m.a.s.l. are classified as lowlands\u003c/p\u003e\n\u003ch3\u003eSearch Strategy\u003c/h3\u003e\n\u003cp\u003eA comprehensive and thorough search strategy was implemented in order to detect all pertinent studies. Various databases, including PubMed, Google Scholar, Web of Science, as well as other manual approaches, were employed for the purpose of conducting literature searches. The search was performed by three field experts (Veterinary microbiology, Veterinary pharmacy and Veterinary Clinica Medicine) to avoid reviewer bias.The research question was \u0026ldquo;what are the proportion/ prevelenec/ and its antibiotic resistsance of coliform causing bovine mastitis in Ethiopia?\u0026rdquo;Searching MeSH terms used were (bacterial mastitis OR coliform bacterial infection OR enterobacter OR \u003cem\u003eEscherichia spp\u003c/em\u003e OR \u003cem\u003ekelbesila\u003c/em\u003e spp OR \u003cem\u003eE. coli\u003c/em\u003e) AND (epidemiology OR prevalence OR infection rate) AND (cattle OR dairy cows OR bovine OR animals) AND (resistance rate OR antibiotic resistance) AND (mastitis) AND (Ethiopia OR Amhara region OR Afar region OR Oromia region OR Tigray region OR Somalia region OR SNNRP). A restriction was placed on the language of publication as English. All identified studies were imported to EndNote 20 software to remove duplicates.\u003c/p\u003e\n\u003ch3\u003eStudy eligibility criteria\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eInclusion criteria\u003c/h2\u003e \u003cp\u003eThis meta-analysis includes all of the primary descriptive studies that have been published in the English language that document the occurrence of genera \u003cem\u003eEscherichia, Klebsiella\u003c/em\u003e, and \u003cem\u003eEnterobacter\u003c/em\u003e in dairy cattle. Inclusion criteria were (I) articles with clear estimation of the proportion of each baeterial isolates, the strains have to be isolated from clinical and /or subclinical bovine mastitis (II) any observational studies capturing the prevalence of the main coliform baceterial isolates, (III) study animals became restricted to domestic cattle commonly used for milk production(cattle), (IV) samples had to be collected from animals which had not been experimentally infected, (V) bacterial isolates were identified at least in genus level, (VI)geographical location (Ethiopia).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eExclusion criteria\u003c/h2\u003e \u003cp\u003eThe following types of studies were not included in the analysis: those involving camels or other species, those with unclear or imprecise estimates of bacterial species in relation to the affected host, review articles, duplicates, abstract-only studies, qualitative studies or KAP questionnaire-based studies, book chapters, case reports, editorials, short communications, opinions, or studies without original data. Intervention studies lacking baseline data on the association between animal exposure and disease were also excluded from the meta-analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDefinition of outcome variable\u003c/h2\u003e \u003cp\u003eIn our review we have two outcome variables; 1) Prevealnce of coliforms 2) AMR of coliforms. Therefore, in the first case, the number of coliform isolets over the total number of bacterial isolstes in milk smaple used to estimate the prevalnce of mastitis associated coliforms. In second case, the number of AMR isolates over the total number of isolates was used to calculatethe ColiformAMR prevalence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eData extraction\u003c/h2\u003e \u003cp\u003eThe selected studies were subjected to a thorough eligibility assessment, and the relevant data were independently extracted by two investigators (M.D and M.G). The data extraction process involved the creation of two tables in a word document and an Excel spreadsheet. The final database included 26 articles that focused on the prevalence of coliform bacterial pathogens in raw milk and 15 articles that estimated the pooled antibiotic resistance rate in raw milk. The extracted data included the name of the primary author, year of publication, year of study, geographical location, region, species/genera of coliform bacteria, sample size, number of coliform bacteria isolates, diagnostic methods, data collection methodologies, and proportion (prevalence). Some of the elements were specific to certain bacterial pathogens and varied across the different data sources. Disagreements were resolved by discussion and consultation with a third author, who was a senior author.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy quality assessment\u003c/h2\u003e \u003cp\u003eAn independent quality assessment was conducted by two researchers (M.D and A.S) using the AMSTAR-2 tool (supplement file). The tool consists of 15 questions that evaluate the methodological quality of both randomized and non-randomized trials of health interventions. This critical appraisal quality assessment tool was used to ensure the reliability and validity of the findings of this systematic review.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData synthesis and statistical analysis\u003c/h2\u003e \u003cp\u003eThe restricted maximum likelihood method was employed to calculate within- and between-study variability, and to estimate the pooled prevalence and 95% confidence intervals using a random effects model. This approach was utilized for the overall meta-analysis, as well as for the resistance rate, heterogeneity, and weight of each study. The \"metaprop\" function of the \"meta\" package version 4.1.3-0 in R statistical software was used to perform a proportional meta-analysis for the estimation of coliform isolate proportion and its resistance rate, utilizing data extracted from the number of events (coliform isolates) and the total number of bacterial isolates. Pooled proportions were estimated using a logit transformation in a logistic-normal random-effect regression model, as described by Nyaga et al. (2014) [36], while a mixed effect logistic regression model was used for the subgroup analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eInvestigation of heterogeneity\u003c/h2\u003e \u003cp\u003eThe Cochran's Q test (reported as the p-value), \u003cem\u003eτ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e (between study variance)and inverse variance index (I\u003csup\u003e2\u003c/sup\u003e) were used to assess the sources of heterogeneity, which describes the percentage of observed total variation between studies that is due to heterogeneity rather than chance. As explained by Higgins and Thompson [\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e16\u003c/span\u003e], the I\u003csup\u003e2\u003c/sup\u003e index was estimated to represent low, moderate, and high heterogeneity, if this corresponds to I\u003csup\u003e2\u003c/sup\u003e values of 25%, 50%, and 75%, respectively. Heterogeneity was deemed to be statistically significant if the I\u003csup\u003e2\u003c/sup\u003e value exceeded 50% and the Q test revealed a P value of less than 0.10. The degree of study heterogeneity has been evaluated using a forest plot diagram. The forest plot diagram displayed the weights, magnitude of effects, and 95% confidence intervals for each study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSub-group sets and bias assesment\u003c/h2\u003e \u003cp\u003eTo determine specific between-study variability, a subgroup analysis of the proportion of the major coliform bacteria in bovine mastitis was performedby using as a factor variablel include publicationyear, study location or regions, genera of bacteria (Eschercia, Kelbesisla and eneterobacter) and the level mastitis( clinical and subclinical). Publication bias was visualized using funnel plot diagramsand Egger\u0026rsquo;s regressiontest. Egger's regression test is used to test the funnel-plot symmetry.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe results of this systematic review and Meta analysis includes article search results, overveiw of the inclded studies, syntehnsis of results( meta analysis), heterogenity and bias assesments and subgroup analysis.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSearch Results\u003c/h2\u003e \u003cp\u003eAs shown in PRISM 2020 flow-chart (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), a total of 1476 articles in various electronic databases were searched, from which were excluded after article duplication assessment (n\u0026thinsp;=\u0026thinsp;30), records were marked as ineligible by automation tools (n\u0026thinsp;=\u0026thinsp;101), and records were removed for other reasons (n\u0026thinsp;=\u0026thinsp;110). Among 1135 articles, 571articles were excluded by article title and abstract screening and 664 studies were reports searched for retrieval and five hundred nine (n\u0026thinsp;=\u0026thinsp;509) articles were reports not retrieved. One hundred fifthy five (n\u0026thinsp;=\u0026thinsp;155) articles were reports being evaluated for eligibility, and one hundred twenty nine (n\u0026thinsp;=\u0026thinsp;129) of them were excluded for various reasons. Finally, tewnty six (n\u0026thinsp;=\u0026thinsp;26) studies were included in systematic review and meta-analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eOverviewof included articles\u003c/h2\u003e \u003cp\u003eThe characteristics of the studies related to each coliform isolates are intricately described in a step-by-step manner. The study animals comprised of dairy cattle which are lactating cows. A total of 26 independat articles were considered for the analysis for all prevalence coliforms in associated with mastitis and 44 articles based on type of coliform isolates. In our investigation, we found most of the isoalted coliforms are \u003cem\u003eEscherichia spp\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;25), \u003cem\u003eKlebsiella spp\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;12) and \u003cem\u003eeneterobacter spp\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;7). However, one article may include two and/ or three of the bacterial coliform genera.The included studies for this systematic review and meta-analysis were conducted in different parts of Ethiopia between 2008 and 2023.The majority of these studies were conducted in the southern (oromia reginal states) and central regions of Ethiopia and studied in btween 2010, 2011 and 2012. Only one study was found in Somali regional state. Methods of diagnosis (CMT and bacterial culture) and bacteriological isolation and characterizationin milk samples were culturally examined according to the procedures described by Quinn et al. (2002). Study designs (cross-sectional) and type of sample (milk) were almost similar. So it helps to reduce the variablity of between studies.The included studies in each region were 14 (32%) in Oromia, 9(20%) in AA,7 (16%) in SNNPR, 6(13%) in Sidama,3(6%) in Amhara, 3(6%) in Tigray and 1(2%) in Somali. In this systematic review, 28 (Wubshet et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) cattle served as the minimum sample size and 1019 cattle were used as the maximum sample size (Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).To evaluate the proportion of mastitis associated coliform isolates in Ethiopia among lactating cows, 11441dairy cows were used in this case. The prevalence of mastitis associated coliform baceteria isolates ranged between 1% and 53% (Getahun et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Reta, Bereda and Alemu, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).The detailed characteristics of the included studies are presented in 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\u003ethe charachterstics of studies included in Meta- analysis (n\u0026thinsp;=\u0026thinsp;44)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst Author\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudy year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStu.design, St\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eType sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMDx\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTAE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTBI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTCB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNCI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ePCB\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, PS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, PS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eKlebsiella spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse and Tilahun Minyahil, 2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2011\u0026ndash;2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse and Tilahun Minyahil, 2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2011\u0026ndash;2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eKlebsiella spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse and Tilahun Minyahil, 2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2011\u0026ndash;2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eenterobacter SPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Zenebe, Habtamu and Endale, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2011\u0026ndash;2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTigray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Ababu, Endashaw and Fesseha, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eKlebsiella spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTakle and berihe., 2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTakle and berihe., 2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eKlebsiella spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTakle and berihe., 2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eenterobacter SPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Adane et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Tegegne et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Fesseha Haben, Mesfin Mathewos, Saliman Aliye, 2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.306\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Getahun et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEscherichia spp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRedeat et al.,2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2008\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Megersa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Megersa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Megersa et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSidama\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Mekonnen and Tesfaye, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Mekonnen and Tesfaye, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Mekibib, B., Furgasa, M., Abunna, F., Megersa, B. and Regassa, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2008\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Mekibib, B., Furgasa, M., Abunna, F., Megersa, B. and Regassa, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2008\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Wubshet et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2012\u0026ndash;2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Wubshet et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2012\u0026ndash;2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Yohannes.K and and Alemu.B, 2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Yohannes.K and and Alemu.B, 2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS,SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTefera et al.,2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS.PS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTefera et al.,2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS.PS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTefera et al.,2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS.PS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Kitila and Kebede, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS.PS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Balemi et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Bitew, Tafere and Tolosa, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2010\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS.Srsm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTigray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTigray\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS,SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Reta, Bereda and Alemu, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2013\u0026ndash;2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSomali\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS,SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Abera et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Abera et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS, SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT,BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eKlebsiella spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Abera et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2010\u0026ndash;2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS,SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEnterobacter spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYusuf and Husen, 2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCS,LS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003emilk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCMT, BC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eEscherichia spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eMDx\u0026thinsp;=\u0026thinsp;Methods of diagnosis, TAE\u0026thinsp;=\u0026thinsp;total animal examine, TBI\u0026thinsp;=\u0026thinsp;total bacteria isolates, NCI\u0026thinsp;=\u0026thinsp;number of coliform isolates, TCB\u0026thinsp;=\u0026thinsp;type of Coliform bacteria, PCB\u0026thinsp;=\u0026thinsp;proportion of Coliform bacteria, CS\u0026thinsp;=\u0026thinsp;crossectional, PS\u0026thinsp;=\u0026thinsp;purposive sampling, SR\u0026thinsp;=\u0026thinsp;simple randm sampling, St\u0026thinsp;=\u0026thinsp;sampling technique, Srsm\u0026thinsp;=\u0026thinsp;systematic random sampling\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eMeta-analysis, testing heterogeneity and bias assessment\u003c/h2\u003e \u003cp\u003eThe meta-analysis encompassed a total of 44 articles that examined mastitis associated coliform bacteria. It is worth noting that certain articles were included multiple times due to their relevance in similar years but in different bacterial genera and/or spp. The studies that were included demonstrated a considerable level of heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;90.6%: τ2\u0026thinsp;=\u0026thinsp;0.6321; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The estimated pooled proportion of mastitis associated coliform among overall bacterial isolates was determined to be 9% (95% CI: 7-11.65%; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The variability between the studies was statistically significant (Q\u0026thinsp;=\u0026thinsp;456.52, DF\u0026thinsp;=\u0026thinsp;43, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eSimilarly, the heterogeneity and outliers of the studies were graphically represented. It is noteworthy that not all studies fell within the range bounded by the two confidence interval lines (95% range). The Galbraith test confirmed the presence of inter-study heterogeneity, as almost 95% of the studies were outside the confidence interval. More than ten out of the 44 studies exceeded the limits of the 95% confidence interval depicted in the chart. The funnel plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and the Egger\u0026rsquo;s regression asymmetry did not indicate the presence of publication bias (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eDue to significant variability across studies, a sub-analysis was conducted based on the level of mastitis, types of coliform bacteria, study area or region, and publication year. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the proportion of coliform isolates at the genus level was higher in clinical mastitis (24%, 95% CI: 15\u0026ndash;37%) than in subclinical bovine mastitis (15%, 95% CI: 10\u0026ndash;22%), with a study weight of 41.6% and 58.3%, respectively. Considerable variability was also observed across studies for both categories of mastitis (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;82%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for clinical mastitis and I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;84%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for subclinical mastitis).\u003c/p\u003e \u003cp\u003eTo further investigate the proportion of coliform isolates in each category of clinical and subclinical mastitis, a subgroup of subgroup analysis was conducted (Supplementary materials). The subgroup of subgroup analysis for clinical mastitis based on types of coliform bacteria isolates showed that \u003cem\u003eEscherichia\u003c/em\u003e had the highest proportion (14%), followed by \u003cem\u003eEnterobacter spp\u003c/em\u003e (9%) and \u003cem\u003eKlebsiella spp\u003c/em\u003e (7%). The heterogeneity across studies was significant (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;72%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). For subclinical mastitis, the proportion of coliform genus bacteria was highest for Escherichia (10%), followed by Klebsiella spp (7%) and \u003cem\u003eEnterobacter spp\u003c/em\u003e (5%). The heterogeneity across studies was also significant (I2\u0026thinsp;=\u0026thinsp;86%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for Escherichia, I2\u0026thinsp;=\u0026thinsp;64%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for \u003cem\u003eKlebsiella spp\u003c/em\u003e, and I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;93%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 for \u003cem\u003eEnterobacter spp\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eSub-analysis based on the types of coliform in genus level, the included studies were categorized into three groups: \u003cem\u003eEscherichia spp\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;25), \u003cem\u003eKlebsiella spp\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;12), and \u003cem\u003eEnterobacter spp\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;7). Significant discrepancies were found in the sub-analysis of the proportion mastitis associated coliform isolates bytypes of coliforms.As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, the subgroup analysis revealed that the pooled proportion of \u003cem\u003eEscherichia\u003c/em\u003e in lactating cows was 12% (95% CI: 9% -16) and (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;93%: \u003cem\u003eτ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.7311; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), followed by enterobacter SPPat 8% (95% CI: 4% \u0026minus;\u0026thinsp;16%) and (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;92%: \u003cem\u003eτ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.7816; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and \u003cem\u003eKlebsiella spp\u003c/em\u003e at 6% (95% CI : 5% \u0026minus;\u0026thinsp;8% ) and (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;65% : \u003cem\u003eτ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.1614; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).Test of heterogeneity showed that statistical significant difference (Q\u0026thinsp;=\u0026thinsp;608.56; D.F. =2; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eSubanalysis by region revealed significant heterogeneity between studies, and testing for subgroup differences suggests that there is a statistically significant subgroup effect (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).Subgroup analysis of bovine mastitis associated coliform by region had shown the highest heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;90.91;\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) in Oromia region.Based on regional subgroup, the highest overall proportion of mastitis associated coliform bacteria was reported in Somali (53%), followed by Tigray (18%), Amhara (11%), Oromia (9%), SNNPR (8%), AA (7%)and Sidama (6%).\u003c/p\u003e \u003cp\u003eIn terms year of publication, sub analysis of publication year was carried out. Year of publication was categorized into at and before 2015, 2015\u0026ndash;2019, at and after 2019. In this case we encountered considerable heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\ge\\:\\)\u003c/span\u003e\u003c/span\u003e89) in each group. The highest study heterogeneity (I\u003csup\u003e2\u003c/sup\u003e=92) was revealed in publication year in between 2015\u0026ndash;2019. The sub-pooled proportion of mastitis associated coliform isolates was highest in the publication year after 2019(14%), followed 2015\u0026ndash;2019 (9%) and before 2015 (8%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The subgroup difference test suggested that there was a statistically significant group effect (Q=5.78; DF=2; p\u0026lt;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMolecular characteristics and serotype of coliforms\u003c/h2\u003e \u003cp\u003eMolecular characterization of mastitis-causing pathogens allows monitoring of specific features at the strain level, such as transmission routes and antimicrobial resistance. Understanding the molecular nature of coliforms is essential to devise prevention and control strategies and reduce risk of the disease associated with these bacteria. However, from all the studies included in this review, only a single study was found that focused on molecular characteristics of coliforms from milk, specifically \u003cem\u003eE.coli\u003c/em\u003e. This study used polymerase chain reaction (PCR) technique and characterized virulence genes of \u003cem\u003eE. coli\u003c/em\u003e. The PCR result indicated that all (100%) of the tested isolates of \u003cem\u003eE. coli\u003c/em\u003e carried the pal gene and 41.67% eaeA gene (EHEC). Among the \u003cem\u003eeaeA\u003c/em\u003e gene-carried \u003cem\u003eE. coli\u003c/em\u003e isolates, 40% carried the \u003cem\u003estx1\u003c/em\u003e gene and 60% of them carried the stx2 gene (source: for mb). Some of the included studies have done the isolation and identification of \u003cem\u003eE. coli O157: H7\u003c/em\u003e was performed using techniques recommended by Quinn et al. [18].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSelection of articles for antibiotic resistance estimation\u003c/h2\u003e \u003cp\u003eOne article was used multiple times for quantitative data analysis. The selection criteria for the chosen studies were as follows, (1) almost all of the included studies provided a comprehensive overview of the pathogen isolation rates for both clinical and sub-clinical bovine mastitis, (2) each article had conducted multiple antimicrobial susceptibility tests (3), the chosen articles had one of the genera or spp of coliform isolates and one other species in mastitis cows, (4) in each study,at least one genera or spp of coliform antimicrobial resistance rate was present, (5) the chosen article may or may not be included in the previous section of our meta-analysis which focused on the prevalence of mastitis associated coliform isolates, (6) we select articles which clearly estimated the proportion of antimicrobial resistance andsusceptibility, (7) we only selected articles that exclusively used milk as the primary sample for dairy cattle in Ethiopia. Finally, we only included studies that conducted the antimicrobial susceptibility test according to the criteria of the laboratory standards institute.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eAntiboitic resistance of mastitis associated coliform isolates\u003c/h2\u003e \u003cp\u003eIn the management of bovine mastitis in Ethiopia, antibiotics are the sole essential component utilized in dairy farms and veterinary clinics. Currently, there exists no alternative for the treatment of bovine mastitis. The improper use of antimicrobials has contributed to the rise in antimicrobial resistance [Gelalch). The dairy farms in Ethiopia do not adhere to hygienic conditions. As coliform bacteria serve as an environmental source of mastitis, recurrent mastitis is a frequent occurrence. Due to the recurrent nature of the pathogen, antibiotics are frequently employed, thereby increasing the likelihood of resistance. The recovery rate is influenced by various factors including individual cow characteristics, management-related factors, and bacterial-associated factors such as strain and the presence of antimicrobial resistance, all of which play a role in determining the success of treatment [Mcdougall et al., 2007]. Coliform bacteria are prevalent in the cow's environment and are not easily eradicated, even in well-managed dairy herds (Jones and Bailey, 2009).\u003c/p\u003e \u003cp\u003eThe antimicrobial sensitivity test conducted in all the included studies utilized the Kirby-Baur disc diffusion method. Among a total of 1759 isolates of Escherichia spp, 626 exhibited antimicrobial resistance, while 445 out of a total of 1130 \u003cem\u003eKelbesila spp\u003c/em\u003e isolates were found to be resistant. Erythromycin exhibited the highest rate of resistance for the treatment of \u003cem\u003eEscherichia spp\u003c/em\u003e (93%, 14/15), followed by Streptomycin (90%) as reported by Haftu et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and Babu et al. (2020). Conversely, the minimum resistance rate (0%) was observed in gentamicin, cotrimazole, and oxytetracycline, as reported by Babu et al. (2020), Etifu and Tilahun (2018), and Moges et al. (2011). Further details of the included studies are presented in 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\u003evarious antimicrobials resistance rate in the treatment of mastitis associated \u003cem\u003eEscherichia spp\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType antibiotics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal Escherichia spp isolates\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eo\u003c/span\u003e. resitance\u003c/p\u003e \u003cp\u003eIsolates\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Reta, Bereda and Alemu, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Balemi et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePencillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Reta, Bereda and Alemu, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Balemi et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbabu et al.,2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCloxacillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoxytetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Reta, Bereda and Alemu, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmoxicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Reta, Bereda and Alemu, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2016\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.467\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbabu et al.,2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStreptomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbabu et al.,2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbabu et al.,2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoxytetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbabu et al.,2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbabu et al.,2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbabu et al.,2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStreptomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmoxicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePencillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCloxacillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.538\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePencillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStreptomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoxytetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Moges et al, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoxytetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStreptomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmoxicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePencillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Girma et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCloxacillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.250\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\u003e*ASTM\u0026thinsp;=\u0026thinsp;Antibiotic susceptibility testing methodology, RR\u0026thinsp;=\u0026thinsp;Resistance Rate\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003ePooled analysis of the antimicrobial resistanec rate\u003c/h2\u003e \u003cp\u003eIn this review, we have uncovered a range of antibiotics that exhibit resistance, namely cotrimoxazole, gentamycin, erythromycin, pencillin, amoxacillin, ampicillin, chloramphenicol, and cloxacillin. The overall pooled prevalence of antimicrobial resistance (AMR) for \u003cem\u003eE.coli\u003c/em\u003e in relation to the aforementioned antibiotics has been estimated at 43% (95%CI; 34.35%-52.09%), with a considerable level of heterogeneity indicated by an I2 value of 82.8% [78.0%; 86.6%] and an H value of 2.41 [2.13; 2.73]. Amongst the listed antibiotics, it has been observed that erythromycin (82%) and pencillin (81%) exhibit the highest rates of resistance when it comes to treating mastitis associated with Eshercia spp in lactating cows. However, Eshercia spp has shown a high susceptibility rate to gentamycin (79%) and amoxcillin (78%) amongst the listed antibiotics, indicating a lower resistance rate in the treatment of Eshercia spp such as E.coli. In the current pooled analysis results, \u003cem\u003eEscherichia spp\u003c/em\u003e have demonstrated roughly similar resistance rates for cotrimazole (29%) and ampicillin (32%). Chloramphenicol (48%) and cloxacillin (55%) also exhibit nearly identical rates of resistance in the treatment of mastitis associated with Eshercia spp in lactating dairy cows.\u003c/p\u003e \u003cp\u003eThe current meta-analysis has also identified the source of heterogeneity between studies. Amongst the studies included, heterogeneity ranged from I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0\u0026ndash;83% (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The subgroup analysis revealed that the maximum source of heterogeneity (83%) was found in the studies included in the cot-rimazole subgroup, while the minimum heterogeneity was recorded in studies under the subgroups of erythromycin, ampicillin, amoxaccillin, and pencillin.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAntibiotic resistance rate for mastitis associated\u003c/b\u003e \u003cb\u003ekelbesila spp\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFrom a total of 1130 isolates of \u003cem\u003ekelbesila spp\u003c/em\u003e, 445 isolates were discovered to be resistant. In this particular study, a single article may examine multiple types of antibiotics, such as the work of (Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), who identified Ampicillin, Erythromycin, Co-trimoxazole, and Chloramphenicol, among others. Similar studies have been conducted using the same methodology. Among the antibiotics considered in this study, the highest rate of resistance was observed for co-trimoxazole (85.7%; 6/7), followed by Gentamycin (80%; 147/118) ((Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, kelbesila SPP exhibited high susceptibility to norfloxacin and doxycycline (100%) ((Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A meta-analysis revealed an overall pooled resistance rate of 42% [95%CI; 31\u0026ndash;54%] for \u003cem\u003eKelbesila\u003c/em\u003e against all antimicrobials, with a significant heterogeneity of I2\u0026thinsp;=\u0026thinsp;86% [72%; 90.7%] (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e). As depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003e, the overall pooled resistance proportion of \u003cem\u003eKelbesila spp\u003c/em\u003e to aminoglycosides, sulfonamides, beta-lactam, chloramphenicol, and tetracycline was 60%, 49%, 43%, 35%, and 22%, respectively. Furthermore, the overall antimicrobial data, number of isolates, and resistance rates are summarized in 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\u003eresistance rate of kelbesila spp for various antimicrobials in bovine mastitis\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of antibioltics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. isolates\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResistance isoaltes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClindamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Haftu, Taddele and Gugsa, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChloramphenicol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStreptomycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOxytetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmoxicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePencillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Boggale et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCloxacillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNorfloxacin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmpicillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDoxycycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eco-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Etifu. Melesse* and Tilahun Minyahil, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTetracycline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePencillin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErythromycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentamycin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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=\"c1\"\u003e \u003cp\u003e(Dereje et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCo-trimoxazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\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\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMilk, a perishable complete nutritious food is considered to be a good medium of growth for many of the microorganisms [FAO ].The majority of mastitis cases are of bacterial origin, with coliform bacteria being among the few predominant causative pathogens [Makovec, Bradley].\u003cb\u003eAbegewi\u003c/b\u003eThere exists explicit data and an all-encompassing summary pertaining solely to the cow level and quarter level general prevalence of bovine mastitis (both clinical and subclinical). Nevertheless, there is an absence of comprehensive epidemiological information regarding the proportions and antibiotic resistance profile in relation to the etiological agents among the bacterial causes of mastitis, which encompasses \u003cem\u003ecoliform bacteria.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWe hope that recognizing the specific etiological agent of mastitis in dairy cattle is very essential to take special attention since each agent has its own characteristics, even it is important to make vaccine and /or other intervention for prevention and control of mastitis in dairy sector. Inline to this, understanding the occurrence rate and antimicrobial resistance rate of \u003cem\u003ecoliform bacteria\u003c/em\u003e associated with bovine mastitis is crucial in enhancing therapeutic interventions and preventive measures as the bacteria is endemic in Ethiopia. Therefore, conducting this systematic review and meta-analysis very useful to systematize and analyze existing information regarding to the etiological and resistance rate of coliform bacteria associated with bovine mastitis.This meta-analysis comprising twenty six observational studies which estimated the pooled proportion of bovine mastitis associated \u003cem\u003ecoliform among\u003c/em\u003e the bacterial pathogens causing mastitis in lactating cows in Ethiopia.\u003c/p\u003e \u003cp\u003eThey are typically acquired from the surrounding environment during the process of milking, as coliform organisms contaminate the teat canal and enter the udder when the teat-ends come into contact with an environmental site that is contaminated [Contreras]. Therefore, it is of utmost importance to enhance hygiene practices and minimize exposure of the teat ends to environmental contamination (source: Abegewi).\u003c/p\u003e \u003cp\u003eThe proportion of coliform isolates at the genus level was higher in cases of clinical mastitis (24%) compared to subclinical bovine mastitis (15%), with a study weight of 41.6% and 58.3% respectively. In contrast to our findings, Belayneh et al. (2014) reported that all (100%) coliform isolates were obtained from subclinical mastitis. Boggale et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) also found 1.3% coliform isolates from clinical mastitis and 98.7% coliform isolates from subclinical mastitis. In this current study, the higher prevalence of subclinical mastitis in comparison to the clinical form indicates the magnitude of the problem of subclinical mastitis and the insufficient attention it receives in terms of diagnosis and treatment (Source: Etifu).\u003c/p\u003e \u003cp\u003eAccording to the analysis of proportions of the different types of coliform bacteria isolates found in cases of clinical mastitis, it was observed that \u003cem\u003eEscherichia\u003c/em\u003e was the most prevalent (14%), followed by \u003cem\u003eEnterobacter spp\u003c/em\u003e (9%) and \u003cem\u003eKlebsiella spp\u003c/em\u003e (7%). Upon further analysis of the types of coliform bacteria at the genus level, it was observed that the coliform bacteria isolated from milk samples of mastitis cases were primarily \u003cem\u003eE. coli\u003c/em\u003e (12%), followed by Klebsiella spp (8%) and \u003cem\u003eEnterobacter spp\u003c/em\u003e (6%). Notably, \u003cem\u003eE. coli\u003c/em\u003e stood out as the predominant coliform. This finding is consistent with the studies conducted by Ahmed and Shimamoto [48] in Egypt and Kateete et al. [18] in Kampala-Uganda, where these coliform genera were also isolated, with \u003cem\u003eE. coli\u003c/em\u003e being the most prevalent. Similarly, Ngwa et al. [35] in Adamawa Cameroon reported \u003cem\u003eE. coli\u003c/em\u003e as the predominant coliform among those associated with mastitis. (Source: Abegewi). In opposite of our finding, reported a higher proportion of \u003cem\u003eEnterobacter spp\u003c/em\u003e (13.7%), followed by \u003cem\u003eE.coli\u003c/em\u003e (7.0%), \u003cem\u003eKlebsiella spp\u003c/em\u003e (3.2%). Makolo et al. [43] and Mbuk et al. [49] in Nigeria also reported that Klebsiella spp. as the predominant coliform. The differences in the relative occurrence of coliform bacteria could be due to differences in bacterial load of the various coliforms in the various environmental sources and the nature of the coliforms (Source: Abegewi).\u003c/p\u003e \u003cp\u003eBased on the classification according to regional subgroup, the Somali subgroup exhibited the highest overall proportion of coliform bacteria associated with mastitis, with a reported rate of 53%. This was followed by the Tigray subgroup at 18%, the Amhara subgroup at 11%, the Oromia subgroup at 9%, the SNNPR subgroup at 8%, the AA subgroup at 7%, and finally the Sidama subgroup at 6%. This variation in proportions could potentially be attributed to disparities in awareness levels, treatment methodologies, milking practices, environmental conditions, and hygiene protocols across the observed regions. The variations in management practices among the dairy herds could potentially lead to an upsurge in the exposure and infection pressure on cows, ultimately resulting in heightened infection levels. Additionally, it is important to note that the variation in the prevalence of these pathogens may also be influenced by the number of studies conducted, the sample sizes utilized, and the breeds of animals included within each region (Bitew et al.) In their study, Bitew et al. found that the prevalence of mastitis differed between crossbreed and local breed cows, with crossbreeds exhibiting higher susceptibility compared to local breeds.\u003c/p\u003e \u003cp\u003eThe sub-pooled proportion of coliform isolates linked to mastitis was found to be highest (14%) in articles published after the year 2019.This was followed by the years 2015\u0026ndash;2019, when the percentage was 9%, and the years prior to 2015, when the percentage was 8%. These results imply that the nation's rate of coliform bacterial infection in cows is rising with time. This could be related to the growth of dairy farms, which are frequently run by people who are not professionals in this field and who may not know enough about good hygiene practices, how to milk cows, or the reasons why milk gets contaminated before, during, or after milking. It is worth noting that these coliform bacteria are considered environmental pathogens, and their occurrence may be associated with inadequate management practices in terms of housing and bedding quality (Radostits et al., 2007). (Source: Abera et al).\u003c/p\u003e \u003cp\u003eAn additional factor contributing to the increase in mastitis related to coliforms may be the proliferation of exotic or hybrid breeds over time. The development and persistence of antibiotic resistance traits in pathogenic bacteria are associated with the utilization of antibiotics (13). Generally speaking, owners of herds and experts in animal health may be excessively and improperly using antibiotics, which could result in the emergence of antibiotic resistance. The World Health Organization's (WHO) report on antimicrobial resistance (AMR) reveals that there has been a concerning rises in the resistance of common bacteria in numerous regions across the globe. According to certain projections, the economic repercussions of AMR are expected to reach trillions of dollars in damages by the middle of the twenty-first century [3].\u003c/p\u003e \u003cp\u003eThe overall pooled prevalnce of AMR rate of \u003cem\u003eE.coli\u003c/em\u003e in the listed antibiotics was etimated 43% (95%CI; 34.35%-52.09%). From the given antibiotics, erythromycin (82%) and pencillin (81%) were the higest resistance rate for the treatment of mastitis associated Eshercia spp in lactating coaws. The development of resistance mechanisms in coliform bacteria have evolved rapidly, owing to the presence of selective pressures. Their defense mechanisms against antibiotics involves the production of antibiotic deactivating enzymes such as the several classes of β-lactamases (class A, B, C and class D of β-lactamases) or aminoglycoside modifying enzymeswith diverse activities (adenylation, acetylation or phosphorylation), changes in antibiotic targets such as alteration of penicillin binding proteins (PBPs), reduction of intracellular antibiotic concentration either by limiting the entrance of the antibiotic or facilitating its expulsion and point mutations in specific areas of DNA gyrase (for example genes gyrA and gyrB for resistance mechanism of \u003cem\u003eK. pneumoniae\u003c/em\u003e against fluoroquinolone drugs. However, most coliform bacteria highly suspteblity rate for gentamycin and amoxcillin among the listed antibiotics which means it has lowest resistance rate in the treatment of Eshercia spp like E.coli. Antimicrobial resistance occurs when commensal or disease-causing organisms survive upon exposure to a concentration of the drug that would normally kill or inhibit their growth (kakullis, Nardomnn).\u003c/p\u003e \u003cp\u003eThe majority of bacteria examined in the present study displayed sensitivity towards Streptomycin, Gentamycin, and Norfloxacin. In contrast, a study conducted in Nigeria [ Mbuk) revealed a significant resistance among coliform bacterial isolates towards Streptomycin. This resistance could potentially be attributed to the excessive use of this antibiotic in the treatment of goat diseases within the study region. The observed sensitivity of bacterial isolates towards Streptomycin in this study can potentially be attributed to its limited utilization in mastitis treatment within the study area. Another study conducted in Ethiopia [Haftu] reported varying degrees of resistance among bacteria towards Chloramphenicol, Gentamycin, and Streptomycin. These studies demonstrate the existence of variations in antibiotic sensitivity based on geographical location and the utilization of specific antibiotics (Garcı\u0026acute;a-Rey). The prevalence of antimicrobial resistance has become a global concern, necessitating the implementation of international initiatives and the establishment of monitoring systems to assess resistance occurrence in all countries (Aarestrup, 2004). Overall, this meta-analysis highlights the substantial occurrence of coliform bacteria in bovine mastitis in Ethiopia, with a notably high level of resistance. In Ethiopia, the consumption of raw milk is a common practice throughout the country. Contaminated milk and milk products serve as the primary transmission pathway for certain coliform bacterial strains, such as \u003cem\u003eE. coli\u003c/em\u003e O157: H7, from animals to humans (Fusco). Although the disease caused by \u003cem\u003eE. coli\u003c/em\u003e is of great public health concern in the country, \u003cem\u003eE. coli\u003c/em\u003e O157: H7 has received limited attention in previous studies. Furthermore, dairy farms may function as a reservoir for human pathogenic bacteria that are resistant to antimicrobial agents, particularly strains of \u003cem\u003eE.coli\u003c/em\u003e that produce extended spectrum beta-lactamases. Consequently, the implementation of an extensive ten-point mastitis control plan is crucial. Certain components of this plan should be tailored specifically for Ethiopia, with a focus on raising awareness among farmers and milkers. For instance, the adoption of strategies such as establishing udder health goals, maintaining a clean and dry environment, ensuring animal comfort, maintaining comprehensive records, managing clinical mastitis during lactation, and implementing biosecurity measures are already being implemented by many larger farms.The evaluation of the antimicrobial resistance profile of various bacterial pathogens in bovine mastitis is of utmost importance in assessing the potential risk of disseminating resistant pathogens to humans.\u003c/p\u003e \u003cp\u003eThis systematic review has several limitations, which must be taken into consideration. Firstly, despite the vast quantity of literature that has been systematically reviewed, the Meta analysis depends on arelatively small number of articles, with just small number of studies included for the analysis of antimicrobial resistance.Secondly, the meta-analysis was limited to studies in Ethiopia, even no studies included in some of regions. This may limit the generalizability of the findings. It is important to note that our eligibility criteria were limited to articles published in English, which creates potential language bias. Thirdly, the review was not registerd in any prospective database.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of the current meta-analysis have shown that the overall prevalence of coliform bacteria, the primary cause of bovine mastitis, has been estimated. Additionally, the study has evaluated the antimicrobial resistance profile of these bacteria. It is worth noting that the prevalence of coliform bacteria in bovine mastitis has increased in recent years (14%) compared to previous decades (8%). The highest proportion of coliform bacteria (18%) was found in the Tigray regional state in Ethiopia. Subgroup analysis revealed that among lactating dairy cows in Ethiopia, \u003cem\u003eEscherichia\u003c/em\u003e had the highest pooled proportion, followed by Enterobacter spp and \u003cem\u003eKlebsiella spp\u003c/em\u003e. Furthermore, a sub-analysis based on the level of mastitis showed that the proportion of coliform isolates at the genus level was higher in clinical mastitis (24%) than in subclinical bovine mastitis (15%).The meta-analysis also showed that the overall pooled resistance rate of \u003cem\u003eKlebsiella\u003c/em\u003e for all antimicrobials was 42%, while \u003cem\u003eE.coli\u003c/em\u003e showed a resistance rate of 43% in the treatment of bovine mastitis. Among the given antibiotics, erythromycin and penicillin exhibited the highest resistance rate for the treatment of mastitis associated with coliform bacteria. The information provided in this report can be of great assistance in making well-informed decisions regarding the control and prevention of coliform-associated bovine mastitis in Ethiopia. It emphasizes the importance of integrating veterinarians, pharmacists, and other healthcare professionals to reduce or control the spread of coliforms in dairy cows in Ethiopia.\u003c/p\u003e \u003cp\u003eM. Radostits, K. W. Hinchcliff, S. H. Done, and W. Gr\u0026uml;unberg, Mastitis in Veterinary Medicine, Elsevier Health Sciences, London, UK, 9th edition, 2016\u003c/p\u003e \u003cp\u003eWorld Health Organization, 2020. Global antimicrobial resistance surveillance system (GLASS) report: early implementation 2020.\u003c/p\u003e \u003cp\u003eWorld Health Organization. \u003cem\u003eGLASS|Global Antimicrobial Resistance Surveillance System (GLASS) 2020\u003c/em\u003e; World Health Organization (WHO): Geneva, Switzerland, 2020.\u003c/p\u003e \u003cp\u003eQuinn PJ, Markey BK, Carter ME, Donelly WJ, Leonard FC (2002) Veterinary Microbiology and Microbial Disease. 2nd [Edn.], Blackwell Science Ltd, a Blackwell publishing Company, pp: 465\u0026ndash;475.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003col\u003e\n\u003cli\u003eAbabu, A., Endashaw, D. and Fesseha, H. 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(2010) \u0026lsquo;Study on Bovine Mastitis in Dairy Farms of Bahir Dar and its Environs\u0026rsquo;, (May 2014). doi: 10.3923/javaa.2010.2912.2917.\u003c/li\u003e\n\u003cli\u003eBoggale, K. \u003cem\u003eet al.\u003c/em\u003e (2018) \u0026lsquo;East African Journal of Veterinary and Animal Sciences ( 2018 ) Prevalence of Bovine Mastitis , Risk Factors and major Causative Agents in West Hararghe\u0026rsquo;, 2, pp. 1\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eDereje, K. \u003cem\u003eet al.\u003c/em\u003e (2018) \u0026lsquo;Isolation , Identification and Antimicrobial Susceptibility Test of Mastitis Causing Bacteria at Holeta Agricultural Research Center Dairy Farms\u0026rsquo;, 2(1), pp. 6\u0026ndash;13. doi: 10.11648/j.ijast.20180201.12.\u003c/li\u003e\n\u003cli\u003eEtifu. Melesse* and Tilahun Minyahil (2019) \u0026lsquo;Prevalence of bovine mastitis , risk factors , isolation and anti-bio gram of major pathogens in Mid Rift\u0026rsquo;, 10(January), pp. 14\u0026ndash;23. doi: 10.5897/IJLP2018.0517.\u003c/li\u003e\n\u003cli\u003eFesseha Haben, Mesfin Mathewos, Saliman Aliye, A. W. 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(2012) \u0026lsquo;Prevalence , bacterial causes , and antimicrobial susceptibility profile of mastitis isolates from cows in large-scale dairy farms of Northern Ethiopia\u0026rsquo;, (April). doi: 10.1007/s11250-012-0135-z.\u003c/li\u003e\n\u003cli\u003eHogeveen, H., Steeneveld, W. and Wolf, C. A. (2019) \u0026lsquo;Production Diseases Reduce the Efficiency of Dairy Production: A Review of the Results, Methods, and Approaches Regarding the Economics of Mastitis\u0026rsquo;, \u003cem\u003eAnnual Review of Resource Economics\u003c/em\u003e, 11, pp. 289\u0026ndash;312. doi: 10.1146/annurev-resource-100518-093954.\u003c/li\u003e\n\u003cli\u003eKarmaker, A., Das, P. C. and Iqbal, A. (2020) \u0026lsquo;Quality assessment of different commercial and local milk available in the local markets of selected area of bangladesh\u0026rsquo;, \u003cem\u003eJournal of Advanced Veterinary and Animal Research\u003c/em\u003e, 7(1), pp. 26\u0026ndash;33. doi: 10.5455/JAVAR.2020.G389.\u003c/li\u003e\n\u003cli\u003eKitila, G. and Kebede, B. (2021) \u0026lsquo;Prevalence , aetiology and risk factors of mastitis of dairy cows kept under extensive management system in west Wollega , western Oromia , Ethiopia\u0026rsquo;, pp. 1\u0026ndash;7. doi: 10.1002/vms3.503.\u003c/li\u003e\n\u003cli\u003eMegersa, B. \u003cem\u003eet al.\u003c/em\u003e (2012) \u0026lsquo;Mastitis in Lactating Cows at Hawassa Town : Prevalence , Risk Factors , Major Bacterial Causes and Treatment Response to Routinely Used Antibiotics\u0026rsquo;, 7(2), pp. 86\u0026ndash;91. doi: 10.5829/idosi.aejsr.2012.7.2.6391.\u003c/li\u003e\n\u003cli\u003eMekibib, B., Furgasa, M., Abunna, F., Megersa, B. and Regassa, A. (2010) \u0026lsquo;Bovine Mastitis : Prevalence , Risk Factors and Major Pathogens in Dairy Farms of Holeta\u0026rsquo;, 3(9), pp. 397\u0026ndash;403.\u003c/li\u003e\n\u003cli\u003eMekonnen, H. and Tesfaye, A. (2010) \u0026lsquo;Prevalence and etiology of mastitis and related management factors in market oriented smallholder dairy farms in Adama \u0026rsquo;, pp. 574\u0026ndash;579.\u003c/li\u003e\n\u003cli\u003eMoges et al (2017) \u0026lsquo;Aantimicrobial Susceptibility of Mastitis Pathogens from Smallholder Dairy Herds in and Around Gondar , Ethiopia\u0026rsquo;, (January). doi: 10.3923/javaa.2011.1616.1622.\u003c/li\u003e\n\u003cli\u003ePage, M. J. \u003cem\u003eet al.\u003c/em\u003e (2021) \u0026lsquo;The PRISMA 2020 statement : An updated guideline for reporting systematic reviews Asbj \u0026oslash; rn Hr o\u0026rsquo;, 88(March). doi: 10.1016/j.ijsu.2021.105906.\u003c/li\u003e\n\u003cli\u003ePol, M. and Ruegg, P. L. (2007) \u0026lsquo;Relationship Between Antimicrobial Drug Usage and Antimicrobial Susceptibility of Gram-Positive Mastitis Pathogens\u0026rsquo;, \u003cem\u003eJournal of Dairy Science\u003c/em\u003e. Elsevier, 90(1), pp. 262\u0026ndash;273. doi: 10.3168/jds.S0022-0302(07)72627-9.\u003c/li\u003e\n\u003cli\u003eReta, M. A., Bereda, T. W. and Alemu, A. N. (2016) \u0026lsquo;Bacterial contaminations of raw cow \u0026rsquo; s milk consumed at Jigjiga City of Somali Regional State , Eastern Ethiopia\u0026rsquo;. doi: 10.1186/s40550-016-0027-5.\u003c/li\u003e\n\u003cli\u003eTegegne, D. T. \u003cem\u003eet al.\u003c/em\u003e (2020) \u0026lsquo;Study of Prevalence , Associated Risk Factors and Causative Bacteria of Bovine Mastitis in Ethiopia -\u0026rsquo;, 4(1), pp. 1\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eWebster, D. M. (2022) \u0026lsquo;Research to Guide the Increase of Dairy Products to Address Nutritional Deficiencies\u0026rsquo;, \u003cem\u003eJournal of Innovation in Social Science\u003c/em\u003e, 3(1), pp. 40\u0026ndash;48. Available at: https://www.aurora-pub.com/JISS/article/view/38%0Ahttps://www.aurora-pub.com/JISS/article/download/38/31.\u003c/li\u003e\n\u003cli\u003eWubshet, A. K. \u003cem\u003eet al.\u003c/em\u003e (2017) \u0026lsquo;Incidence of heifer mastitis and identification of major associated pathogens in dairy farms at wolaita soddo town , southern Ethiopia\u0026rsquo;, 5(5), pp. 169\u0026ndash;176. doi: 10.15406/jdvar.2017.05.00156.\u003c/li\u003e\n\u003cli\u003eYohannes.K and and Alemu.B (2018) \u0026lsquo;International Journal of Advanced Research in Biological Sciences Prevalence of Bovine Mastitis in lactating Cows and Associated risk factors in and around Wolayta Soddo , Southern Ethiopia\u0026rsquo;, 5, pp. 60\u0026ndash;69. doi: 10.22192/ijarbs.\u003c/li\u003e\n\u003cli\u003eZenebe, N., Habtamu, T. and Endale, B. (2014) \u0026lsquo;Study on bovine mastitis and associated risk factors in Adigrat , Northern Ethiopia\u0026rsquo;, 8(4), pp. 327\u0026ndash;331. doi: 10.5897/AJMR2013.6483.\u003c/li\u003e\n\u003cli\u003eZhao, X. and Lacasse, P. (2008) \u0026lsquo;Mammary tissue damage during bovine mastitis: causes and control.\u0026rsquo;, \u003cem\u003eJournal of animal science\u003c/em\u003e, 86(13 Suppl), pp. 57\u0026ndash;65. doi: 10.2527/jas.2007-0302.\u003c/li\u003e\n\u003cli\u003e\u0026nbsp;Jones GM, Bailey TL. Understanding the basics of mastitis. Virginia Cooperative Extension. Publication404\u0026ndash;234. 2009.\u0026nbsp;\u0026nbsp;ttps://vtechworks.lib.vt.edu/bitstream/handle/10919/48392/404-233_pdf.pdf?sequence=1\u003c/li\u003e\n\u003cli\u003eMcdougall S, Agnew KE, Cursons R, Hou XX, Compton CRW. Parenteral Treatment of Clinical Mastitis with Tylosin Base or Penethamate Hydriodide in Dairy Cattle. J Dairy Sci [Internet]. 2007;90(2):779\u0026ndash;89. Available from: http://dx.doi.org/10.3168/jds.S0022-0302(07)71562-X\u003c/li\u003e\n\u003cli\u003eCSA: \u003cstrong\u003eCentral statistical authority of Ethiopia: report on livestock and livestock characteristics (private peasant holdings). STATISTICAL BULLETIN 587 II.\u003c/strong\u003e 2020.\u003c/li\u003e\n\u003cli\u003eRadostits, K. W. Hinchcliff, S. H. Done, and W. Gr\u0026uml;unberg, Mastitis in Veterinary Medicine, Elsevier Health Sciences, London, UK, 9th edition, 2016\u003c/li\u003e\n\u003cli\u003eWorld Health Organization, 2020. Global antimicrobial resistance surveillance system (GLASS) report: early implementation 2020.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. \u003cem\u003eGLASS|Global Antimicrobial Resistance Surveillance System (GLASS) 2020\u003c/em\u003e; World Health Organization (WHO): Geneva, Switzerland, 2020.\u003c/li\u003e\n\u003cli\u003eQuinn PJ, Markey BK, Carter ME, Donelly WJ, Leonard FC (2002) Veterinary Microbiology and Microbial Disease. 2nd [Edn.], Blackwell Science Ltd, a Blackwell publishing Company, pp: 465-475.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"university of gondar","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Systematic Review and Meta-Analysis of Coliform Bacteria and Antibiotic Resistance ","lastPublishedDoi":"10.21203/rs.3.rs-4941592/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4941592/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe primary databases employed were Google, Google Scholar, HINARI, Web of Science, and PubMed. The quality assessment was performed using the AMSTAR-2 tool. The pooled proportion, the rate of resistance, and a 95% confidence interval were calculated with a random effects model using \u003cem\u003eR\u003c/em\u003e software version 4.1.3. Funnel plots, and Eggers were used to assess publication bias.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTwenty six articles were included for this meta-analysis. The overall pooled proportion of mastitis associated coliform bacteria was 9% (95% CI: 7-11.65%).Substantial heterogeneity was observed in included studies (\u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;90.6%; \u003csub\u003eP\u003c/sub\u003e\u0026lt;0.01).Among the major coliform bactera, \u003cem\u003eEshercia spp\u003c/em\u003e had the highest pooled prevalence at 12%, followed by \u003cem\u003eEnterobacter spp\u003c/em\u003e at 8%, and \u003cem\u003eKlebsiella spp\u003c/em\u003e at 6%. Sub-analysis by level of mastitis, the proportion of occurrence of coliforms isolates was higher 24% (15\u0026ndash;37%) compare with subclinical bovine mastitis 15% (10\u0026ndash;22%). The subgroup of subgroup analysis of studies under clinical mastitis, \u003cem\u003eEscherichia\u003c/em\u003e isolstes was highest proportion (14%), followed \u003cem\u003eEnterobacter spp\u003c/em\u003e (9%) and \u003cem\u003eKlebsiella spp\u003c/em\u003e (7%) while in subclinical masttis \u003cem\u003eEscherichia\u003c/em\u003e was highest proportion (10%), and followed by \u003cem\u003eKlebsiella spp\u003c/em\u003e (7%) and \u003cem\u003eEnterobacter spp\u003c/em\u003e (5%). In study region, the highest proportion was reported in Somali (53%), followed by Tigray (18%), Amhara (11%), Oromia (9%), SNNPR (8%), AA (7%) and Sidama (6%). Erythromycin (82%) and pencillin (81%) were the higest resistance rate for the treatment of mastitis associated \u003cem\u003eEshercia spp\u003c/em\u003e. The resistance rate of \u003cem\u003eKelbesila spp\u003c/em\u003e for aminoglycoside, sulphonamides, beta-lactm, chloramphenicol and tetracycline was 60%, 49%, 43%, 35% and 22%, respectively. In the present meta-analysis, Escherichia isolates were identified as the most common coliforms in intramammary gland infections. The current investigation supports the claim that cow milk can be considered a significant source of \u003cem\u003eEscherichia spp\u003c/em\u003e. The study found that the emergence of antibiotic resistance in \u003cem\u003eEscherichia spp\u003c/em\u003e could pose a severe risk to consumers in Ethiopia, emphasizing the importance of strict surveillance and the implementation of effective hygiene measures in dairy farms and milk production.\u003c/p\u003e","manuscriptTitle":"Systematic Review and Meta-Analysis of Coliform Bacteria and Antibiotic Resistance in Mastitic Cow Milk in Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-21 16:40:32","doi":"10.21203/rs.3.rs-4941592/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb1b0063-0acf-4cea-8be2-245ab249e721","owner":[],"postedDate":"August 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":36275098,"name":"Animal Science"}],"tags":[],"updatedAt":"2024-08-21T16:40:32+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-21 16:40:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4941592","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4941592","identity":"rs-4941592","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}