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

doi:10.21203/rs.3.rs-4941592/v1

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Systematic Review

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

https://doi.org/10.21203/rs.3.rs-4941592/v1

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Methods

The 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 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 (I² = 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

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?

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 km² 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), τ² (between study variance)and inverse variance index (I²) 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 I² index was estimated to represent low, moderate, and high heterogeneity, if this corresponds to I² values of 25%, 50%, and 75%, respectively. Heterogeneity was deemed to be statistically significant if the I² 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.

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 (I² = 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 (I² = 82%, p < 0.01 for clinical mastitis and I² = 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 (I² = 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 I² = 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 (I² = 93%: τ² = 0.7311; p < 0.01), followed by enterobacter SPPat 8% (95% CI: 4% − 16%) and (I² = 92%: τ² = 0.7816; P < 0.01) and Klebsiella spp at 6% (95% CI : 5% − 8% ) and (I² = 65% : τ² = 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 (I² = 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 (I²$\:\ge\:$89) in each group. The highest study heterogeneity (I²=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	No. 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 I² = 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

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].AbegewiThere 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.

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

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The authors declare no competing interests.

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

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Abstract

Methods

Results

Figures

Introduction

Megersa

Methods

Descrpition of study stetings

Search Strategy

Study eligibility criteria

Inclusion criteria

Exclusion criteria

Definition of outcome variable

Data extraction

Study quality assessment

Data synthesis and statistical analysis

Investigation of heterogeneity

Sub-group sets and bias assesment

Results

Search Results

Overviewof included articles

Meta-analysis, testing heterogeneity and bias assessment

Subgroup analysis

Molecular characteristics and serotype of coliforms

Selection of articles for antibiotic resistance estimation

Antiboitic resistance of mastitis associated coliform isolates

Pooled analysis of the antimicrobial resistanec rate

Discussion

Conclusion

References

Additional Declarations

Supplementary Files

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