Search results for: Yemane Tsehaye

Authors: Hailekiros Tadesse Tekle, Yemane Tsehaye, Fetien Abay

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Barley (Hordeum vulgare L.) is one of the most important cereal crops in the world, grown for the poor farmers in Tigray with low yield production. The purpose of this research was to estimate the performance of 166 barley genotypes against the quantitative traits with detailed analysis of the variance component, heritability, genetic advance, and genetic usefulness parameters. The finding of ANOVA was highly significant variation (p ≤ 0:01) for all the genotypes. We found significant differences in coefficient of variance (CV of 15%) for 5 traits out of the 12 quantitative traits. The topmost broad sense heritability (H2) was recorded for seeds per spike (98.8%), followed by thousand seed weight (96.5%) with 79.16% and 56.25%, respectively, of GAM. The traits with H2 ≥ 60% and GA/GAM ≥ 20% suggested the least influenced by the environment, governed by the additive genes and direct selection for improvement of such beneficial traits for the studied genotypes. Hence, the 20 outstanding recombinant inbred lines (RIL) barley genotypes performing early maturity, high yield, and 1000 seed weight traits simultaneously were the top ranked group barley genotypes out of the 166 genotypes. These are; G5, G25, G33, G118, G36, G123, G28, G34, G14, G10, G3, G13, G11, G32, G8, G39, G23, G30, G37, and G26. They were early in maturity, high TSW and GYP (TSW ≥ 55 g, GYP ≥ 15.22 g/plant, and DTM below 106 days). In general, the 166 genotypes were classified as high (group 1), medium (group 2), and low yield production (group 3) genotypes in terms of yield and yield component trait analysis by clustering; and genotype parameter analysis such as the heritability, genetic advance, and genetic usefulness traits in this investigation.

Keywords: barley, clustering, genetic advance, heritability, usefulness, variability, yield

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Authors: Atsebaha Gebrekidan Kahsay, Tsehaye Asmelash, Enquebaher Kassaye

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Background: Salmonella remains a global public health problem with a significant burden in sub-Saharan African countries. Human restricted cause of typhoid and paratyphoid fever are S. Typhi and S. Paratyphi, whereas S. Enteritidis and S. Typhimurium is the causative agent of invasive nontyphoidal diseases among humans and animals are their reservoir. The antibiotic resistance of Salmonella is another public health threat around the globe. To come up with full information about human and animal salmonellosis, we made a systematic review of the prevalence, serotypes, and antibiotic resistance of Salmonella in Ethiopia. Methods: This systematic review used Google Scholar and PubMed search engines to search articles from Ethiopia that were published in English in peer-reviewed international journals from 2010 to 2022. We used keywords to identify the intended research articles and used a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist to ensure the inclusion and exclusion criteria. Frequencies and percentages were analyzed using Microsoft Excel. Results: Two hundred seven published articles were searched, and 43 were selected for a systematic review, human (28) and animals (15). The prevalence of Salmonella in humans and animals was 434 (5.2%) and 641(10.1%), respectively. Fourteen serotypes were identified from animals, and S. Typhimurium was among the top five. Among the ciprofloxacin-resistant isolates in human studies, 16.7% was the highest, whereas, for ceftriaxone, 100% resistance was reported. Conclusions: The prevalence of Salmonella among diarrheic patients and food handlers (5.2%) was lower than the prevalence in food animals (10.1%). We did not find serotypes of Salmonella in human studies, although fourteen serotypes were included in food-animal studies, and S. Typhimurium was among the top five. Salmonella species from some human studies revealed a non-susceptibility to ceftriaxone. We recommend further study about invasive nontyphoidal Salmonella and predisposing factors among humans and animals in Ethiopia.

Keywords: antibiotic resistance, prevalence, systematic review, serotypes, Salmonella, Ethiopia

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Authors: Yemane Tadesse Gebreslassie, Henok Gidey Gebretnsae

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Nanotechnology has emerged as a highly promising field of research with wide-ranging applications across various scientific disciplines. In recent years, tin oxide has garnered significant attention due to its intriguing properties, particularly when synthesized in the nanoscale range. While numerous physical and chemical methods exist for producing tin oxide nanoparticles, these approaches tend to be costly, energy-intensive, and involve the use of toxic chemicals. Given the growing concerns regarding human health and environmental impact, there has been a shift towards developing cost-effective and environmentally friendly processes for tin oxide nanoparticle synthesis. Green synthesis methods utilizing biological entities such as plant extracts, bacteria, and natural biomolecules have shown promise in successfully producing tin oxide nanoparticles. However, scaling up the production to an industrial level using green synthesis approaches remains challenging due to the complexity of biological substrates, which hinders the elucidation of reaction mechanisms and formation processes. Thus, this review aims to provide an overview of the various sources of biological entities and methodologies employed in the green synthesis of tin oxide nanoparticles, as well as their impact on nanoparticle properties. Furthermore, this research delves into the strides made in comprehending the mechanisms behind the formation of nanoparticles as documented in existing literature. It also sheds light on the array of analytical techniques employed to investigate and elucidate the characteristics of these minuscule particles.

Keywords: nanotechnology, tin oxide, green synthesis, formation mechanisms

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Authors: Tsegay Giday Woldu, Haibin Zhang, Xin Zhang, Yemane Hailu Fissuh

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It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms.

Keywords: conjugate gradient method, global convergence, large scale optimization, sufficient descent property

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

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Authors: Yemane Kahsay Berhe

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The multipurpose cactus pear plant with great potential as a source of food and livestock feed faced a threat from Dactylopius spp in different countries. Specifically, D. coccus is an important pest damaging significant areas in Tigray-Ethiopia. Using pest-resistant cultivars is an important element of an integrated pest management strategy, and studying the mechanisms of resistance is vital. It can be chemical or physical, such as oxalate crystals and other cladode characteristics. Cladode features of six cultivars (three O. ficus-indica, two O. cochenillifera, and one O. robusta) were examined for resistance to D. coccus in a completely randomized design (CRD) with three replications. ‘Rojo Pelón’ (O. ficus-indica), ‘Robusta’ (O. robusta), and ‘Bioplástico’ (O. cochinillifera) are resistant cultivars; and ‘Atlixco’ and ‘Chicomostoc’ (O. ficus-indica) and ‘Nopalea’ (O. cochinillifera) are susceptible. Cultivars showed a significant difference in cladode weight in g, cladode length, cladode width, and cladode thickness in cm, where cladode thickness was higher in ‘Rojo Pelón’ followed by ‘Robusta’. Calcium oxalates number per mm was higher in ‘Bioplástico’ (20.7+2.08) followed by ‘Robusta’ (18.9+2.31) and ‘Rojo Pelón’ (15.9+0.34); and similarly, epidermis thickness found higher in ‘Bioplástico’ (0.21+0.032) and ‘Robusta’ (0.19+0.014), but similar with ‘Rojo Pelón’ (0.18+0.026). However, cuticle thickness didn’t show a difference among cultivars. Cladode thickness, calcium oxalates number, and epidermis thickness had positive correlations with resistance. These results demonstrate that calcium oxalates number and epidermis thickness might positively affect D. coccus resistance in O. ficus-indica. This feeding-barring role and the insect-plant interaction need to be studied.

Keywords: cactus pear, resiatnce, druses, epidermis thickness

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Authors: Tadele Araya, Tsehaye Asmelash, Girmatsion Fiseha

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Background: Hepatitis B virus (HBV), Hepatitis C virus (HCV) and Human Immunodeficiency Virus (HIV) constitute serious healthcare problems worldwide. Blood-borne pathogens HBV, HCV and HIV are commonly associated with infections among substance or Injection Drug Users (IDUs). The objective of this study was to determine the prevalence of HBV, HCV, and HIV infections among substance users in Mekelle Substance users Treatment and Rehabilitation Centers. Methods: A cross-sectional study design was used from Dec 2020 to Sep / 2021 to conduct the study. A total of 600 substance users were included. Data regarding the socio-demographic, clinical and sexual behaviors of the substance users were collected using a structured questionnaire. For laboratory analysis, 5-10 ml of venous blood was taken from the substance users. The laboratory analysis was performed by Enzyme-Linked Immunosorbent Assay (ELISA) at Mekelle University, Department of Medical Microbiology and Immunology Research Laboratory. The Data was analyzed using SPSS and Epi-data. The association of variables with HBV, HCV and HIV infections was determined using multivariate analysis and a P value < 0.05 was considered statistically significant. Result: The overall prevalence rate of HBV, HCV and HIV infections were 10%, 6.6%, and 7.5%, respectively. The mean age of the study participants was 28.12 ± 6.9. A higher prevalence of HBV infection was seen in participants who were users of drug injections and in those who were infected with HIV. HCV was comparatively higher in those who had a previous history of unsafe surgical procedures than their counterparts. Homeless participants were highly exposed to HCV and HIV infections than their counterparts. The HBV/HIV Co-infection prevalence was 3.5%. Those doing unprotected sexual practices [P= 0.03], Injection Drug users [P= 0.03], those who had an HBV-infected person in their family [P=0.02], infected with HIV [P= 0.025] were statistically associated with HBV infection. HCV was significantly associated with Substance users and previous history of unsafe surgical procedures [p=0.03, p=0.04), respectively. HIV was significantly associated with unprotected sexual practices and being homeless [p=0.045, p=0.05) respectively. Conclusion-The highly prevalent viral infection was HBV compared to others. There was a High prevalence of HBV/HIV co-infection. The presence of HBV-infected persons in a family, unprotected sexual practices and sharing of needles for drug injection were the risk factors associated with HBV, HIV, and HCV. Continuous health education and screening of the viral infection coupled with medical and psychological treatment is mandatory for the prevention and control of the infections.

Keywords: hepatitis b virus, hepatitis c virus, HIV, substance users

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Authors: Habtamu Fufa, Yemane Berhane

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Child under nutrition has long-term consequences for intellectual ability, economic productivity, reproductive performance and susceptibility to metabolic and cardiovascular disease. The unacceptably high prevalence of malnutrition in young children of the region has not changed much over the last decades, which could make the achievement of the corresponding Millennium Development Goals very unlikely. Despite the well-documented problems of child malnutrition in Sub-Saharan Africa, there is few systematic review of evidences on determinants of child malnutrition in the region. The current available evidence on determinants of child under nutrition in Sub-Saharan Africa is systematically reviewed. The method used in searching relevant literature was using bio medical databases PUBMED, Google scholar and the website of the World Health Organization on nutrition using the following key words: "Determinants “, "Child Malnutrition", and "Sub- Saharan Africa". The search was limited to articles published in and after 1995 up to date. In all the reviewed articles, the data were analyzed using multivariate regression analysis and or odds ratios for significance of determinants in child malnutrition. Synthesis of 40 published articles from various countries of the region is done and noted that household economic status, maternal education, disease, breastfeeding practices, age and sex of a child, birth interval and residential areas were found to be determinants of child under nutrition. Poverty remains the main factor of malnutrition in Sub-Saharan Africa and poor education of parents aggravates the malnutrition through perpetuation of poor nutrition practices. Male children under five years are the most affected ones. Understanding of these determinants of poor nutritional attainment would provide insights in designing interventions for reducing the high levels of child malnutrition in this region. Large-scale multi-sectoral community-based interventions are urgently needed for a sustainable improvement of child nutritional & health status in Sub-Saharan Africa.

Keywords: child malnutrition, determinants, Sub-Saharan Africa, health status

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Authors: Hanna Gulema, Meaza Demissie, Alemayehu Worku, Tesfaye Assebe Yadeta, Yemane Berhane

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Background: In patriarchal societies, female caregivers decide on food allocation within a family based on prevailing gender and age norms, which may lead to inequality that does not favor young adolescent girls. This study evaluated the effect of a community-based social norm intervention involving female caregivers in West Hararghe, Ethiopia. The intervention was engaging female caregivers along with other adult influential community members to deliberate and act on food allocation social norms in a process referred to as Social Analysis and Action (SAA). Method: We used data from a large quasi-experimental study to compare family eating practices between those who participated in the Social Analyses and Action intervention and those who did not. The respondents were female caregivers in households with young adolescent girls (ages 13 and 14 years). The study’s outcome was the practice of family eating together from the same dish. The difference in difference (DID) analysis with the Mixed effect logistic regression model was used to examine the effect of the intervention. Result: The results showed improved family eating practices in both groups, but the improvement was greater in the intervention group. The DID analysis showed an 11.99 percentage points greater improvement in the intervention arm than in the control arm. The mixed-effect regression produced an adjusted odds ratio of 2.08 (95% CI [1.06–4.09]) after controlling selected covariates, p-value 0.033. Conclusions: The involvement of influential adult community members significantly improves the family practice of eating together in households where adolescent girls are present in our study. The intervention has great potential to minimize household food allocation inequalities and thus improve the nutritional status of young adolescents. Further studies are necessary to evaluate the effectiveness of the intervention in different social norm contexts to formulate policy and guidelines for scale-up.

Keywords: family eating practice, social norm intervention, adolescence girls, caregiver

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

Abstract:

a systematic observation from a defined time of origin up to certain failure or censor is known as survival data. Survival analysis is a major area of interest in biostatistics and biomedical researches. At the heart of understanding, the most scientific and medical research inquiries lie for a causality analysis. Thus, the main concern of this study is to investigate the causal effect of treatment on survival time conditional to the possibly time-varying covariates. The theory of causality often differs from the simple association between the response variable and predictors. A causal estimation is a scientific concept to compare a pragmatic effect between two or more experimental arms. To evaluate an average treatment effect on survival outcome, the estimating equation was adjusted for time-varying covariates under the semi-parametric transformation models. The proposed model intuitively obtained the consistent estimators for unknown parameters and unspecified monotone transformation functions. In this article, the proposed method estimated an unbiased average causal effect of treatment on survival time of interest. The modified estimating equations of semiparametric transformation models have the advantage to include the time-varying effect in the model. Finally, the finite sample performance characteristics of the estimators proved through the simulation and Stanford heart transplant real data. To this end, the average effect of a treatment on survival time estimated after adjusting for biases raised due to the high correlation of the left-truncation and possibly time-varying covariates. The bias in covariates was restored, by estimating density function for left-truncation. Besides, to relax the independence assumption between failure time and truncation time, the model incorporated the left-truncation variable as a covariate. Moreover, the expectation-maximization (EM) algorithm iteratively obtained unknown parameters and unspecified monotone transformation functions. To summarize idea, the ratio of cumulative hazards functions between the treated and untreated experimental group has a sense of the average causal effect for the entire population.

Keywords: a modified estimation equation, causal effect, semiparametric transformation models, survival analysis, time-varying covariate

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Authors: Yemane Tadesse Gebreslassie, Fisseha Guesh Gebremeskel

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Nanotechnology has made remarkable advancements in recent years, revolutionizing various scientific fields, industries, and research institutions through the utilization of metal and metal oxide nanoparticles. Among these nanoparticles, copper oxide nanoparticles (CuO NPs) have garnered significant attention due to their versatile properties and wide-range applications, particularly, as effective antimicrobial and anticancer agents. CuO NPs can be synthesized using different methods, including physical, chemical, and biological approaches. However, conventional chemical and physical approaches are expensive, resource-intensive, and involve the use of hazardous chemicals, which can pose risks to human health and the environment. In contrast, biological synthesis provides a sustainable and cost-effective alternative by eliminating chemical pollutants and allowing for the production of CuO NPs of tailored sizes and shapes. This comprehensive review focused on the green synthesis of CuO NPs using various biological resources, such as plants, microorganisms, and other biological derivatives. Current knowledge and recent trends in green synthesis methods for CuO NPs are discussed, with a specific emphasis on their biomedical applications, particularly in combating cancer and microbial infections. This review highlights the significant potential of CuO NPs in addressing these diseases. By capitalizing on the advantages of biological synthesis, such as environmental safety and the ability to customize nanoparticle characteristics, CuO NPs have emerged as promising therapeutic agents for a wide range of conditions. This review presents compelling findings, demonstrating the remarkable achievements of biologically synthesized CuO NPs as therapeutic agents. Their unique properties and mechanisms enable effective combating against cancer cells and various harmful microbial infections. CuO NPs exhibit potent anticancer activity through diverse mechanisms, including induction of apoptosis, inhibition of angiogenesis, and modulation of signaling pathways. Additionally, their antimicrobial activity manifests through various mechanisms, such as disrupting microbial membranes, generating reactive oxygen species, and interfering with microbial enzymes. This review offers valuable insights into the substantial potential of biologically synthesized CuO NPs as an alternative approach for future therapeutic interventions against cancer and microbial infections.

Keywords: copper oxide nanoparticles, green synthesis, nanotechnology, microbial infection

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Authors: Yemane Tadesse Gebreslassie, Fisseha Guesh Gebremeskel

Abstract:

Nanotechnology has made remarkable advancements in recent years, revolutionizing various scientific fields, industries, and research institutions through the utilization of metal and metal oxide nanoparticles. Among these nanoparticles, copper oxide nanoparticles (CuO NPs) have garnered significant attention due to their versatile properties and wide-range applications, particularly, as effective antimicrobial and anticancer agents. CuO NPs can be synthesized using different methods, including physical, chemical, and biological approaches. However, conventional chemical and physical approaches are expensive, resource-intensive, and involve the use of hazardous chemicals, which can pose risks to human health and the environment. In contrast, biological synthesis provides a sustainable and cost-effective alternative by eliminating chemical pollutants and allowing for the production of CuO NPs of tailored sizes and shapes. This comprehensive review focused on the green synthesis of CuO NPs using various biological resources, such as plants, microorganisms, and other biological derivatives. Current knowledge and recent trends in green synthesis methods for CuO NPs are discussed, with a specific emphasis on their biomedical applications, particularly in combating cancer and microbial infections. This review highlights the significant potential of CuO NPs in addressing these diseases. By capitalizing on the advantages of biological synthesis, such as environmental safety and the ability to customize nanoparticle characteristics, CuO NPs have emerged as promising therapeutic agents for a wide range of conditions. This review presents compelling findings, demonstrating the remarkable achievements of biologically synthesized CuO NPs as therapeutic agents. Their unique properties and mechanisms enable effective combating against cancer cells and various harmful microbial infections. CuO NPs exhibit potent anticancer activity through diverse mechanisms, including induction of apoptosis, inhibition of angiogenesis, and modulation of signaling pathways. Additionally, their antimicrobial activity manifests through various mechanisms, such as disrupting microbial membranes, generating reactive oxygen species, and interfering with microbial enzymes. This review offers valuable insights into the substantial potential of biologically synthesized CuO NPs as an alternative approach for future therapeutic interventions against cancer and microbial infections.

Keywords: biological synthesis, copper oxide nanoparticles, microbial infection, nanotechnology

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Authors: Redie Kidane Ghebrehawariat, Betiel Habte Hadgu, Filmon Berhane Kahsay, Rim Berhane Fisehaye, Samuel Haile Kahsay, Saron Yemane Yosief, Selemawit Mosazghi Gilazghi

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A cross-sectional study was conducted from 22 February to 9 April 2022 on small, medium, and large holder dairy farms to determine the bovine mastitis prevalence and associated risk factors in the Anseba region, Eritrea. A total of 34 dairy farms and 193 dairy cows were randomly selected. Dairy cows were physically examined for any change on the udder and milk; a California mastitis test was performed to check sub-clinical mastitis; a closed-ended semi-structured questionnaire composed of 28 variables/risk factors (21 management risk factors and 7 animal-level risk factors) was used to determine the risk factors responsible for clinical and sub-clinical mastitis in the dairy cows. The overall cow-level prevalence of mastitis was 147 (76.2%). The animal level prevalence rate of clinical and sub-clinical mastitis was found to be 22 (11.4%) and 125 (64.8%), respectively, while herd level prevalence both for clinical and subclinical mastitis was found to be 14 (41.2%) and 26 (76.5%) respectively. Based on the already set P-value, which is <0.05, a number of risk factors were found to have a significant relationship with the occurrence of clinical and sub-clinical mastitis. Generally, animal risk factors such as animal age, parity, injury on the udder or teat, and previous history of mastitis presence of injury on the udder and lactation stage were risk factors with a significant relationship with the occurrence of clinical and sub-clinical mastitis. On the other hand, management risk factors with a significant relationship to the occurrence of clinical and sub-clinical mastitis were herd size, failure to milk mastitic cow, at last, educational level, floor type, failure to use a towel, using one towel for more than one cow and failure to practice mastitis test. From a total of 772 quarters, 280 (36.3%) were found positive for sub-clinical mastitis using the California mastitis test; of these, 70 (9%) were weakly positive, 90 (11.7%) were distinct positive, and 120 (15.5%) were strongly positive. Furthermore, 13 (1.7%) quarters were blocked. Quarter level prevalence was right front 80 (41.5%), left front 64 (33.3%), right hind 69 (35.8%) and left hind 67 (34.7%). The study has shown that mastitis is a major problem for dairy farms and the findings suggested that mastitis is one of the limiting factors in increasing milk production. Subclinical mastitis was found to be a devastating problem, and it occurred in all three breeds of lactating dairy cattle. Therefore, farmers should work hard to avoid the above-mentioned risk factors to minimize the infection of their dairy cattle by mastitis and thereby increase their profit. On the other hand, the Ministry of Agriculture, through the extension unit, should work in close contact with the farmers to increase awareness of the economic importance of the disease and associated risk factors.

Keywords: mastitis, prevalence, dairy cattle, Anseba, Eritrea

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