Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14

Search results for: Zelalem Temesgen

14 Innovative In-Service Training Approach to Strengthen Health Care Human Resources and Scale-Up Detection of Mycobacterium tuberculosis

Authors: Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Yewondwossen Tadesse, Susan Lehman, Zelalem Temesgen

Abstract:

In-service health trainings in Sub-Saharan Africa are mostly content-centered with higher disconnection with the real practice in the facility. This study intended to evaluate in-service training approach aimed to strengthen health care human resources. A combined web-based and face-to-face training was designed and piloted in Ethiopia with the diagnosis of tuberculosis. During the first part, which lasted 43 days, trainees accessed web-based material and read without leaving their work; while the second part comprised a one-day hands-on evaluation. Trainee’s competency was measured using multiple-choice questions, written-assignments, exercises and hands-on evaluation. Of 108 participants invited, 81 (75%) attended the course and 71 (88%) of them successfully completed. Of those completed, 73 (90%) scored a grade from A to C. The approach was effective to transfer knowledge and turn it into practical skills. In-service health training should transform from a passive one-time-event to a continuous behavioral change of participants and improvements on their actual work.

Keywords: Ethiopia, health care, Mycobacterium tuberculosis, training

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13 Using Machine Learning to Enhance Win Ratio for College Ice Hockey Teams

Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

Abstract:

Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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12 Plasticity in Matrix Dominated Metal-Matrix Composite with One Active Slip Based Dislocation

Authors: Temesgen Takele Kasa

Abstract:

The main aim of this paper is to suggest one active slip based continuum dislocation approach to matrix dominated MMC plasticity analysis. The approach centered the free energy principles through the continuum behavior of dislocations combined with small strain continuum kinematics. The analytical derivation of this method includes the formulation of one active slip system, the thermodynamic approach of dislocations, determination of free energy, and evolution of dislocations. In addition zero and non-zero energy dissipation analysis of dislocation evolution is also formulated by using varational energy minimization method. In general, this work shows its capability to analyze the plasticity of matrix dominated MMC with inclusions. The proposed method is also found to be capable of handling plasticity of MMC.

Keywords: active slip, continuum dislocation, distortion, dominated, energy dissipation, matrix dominated, plasticity

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11 Characterization of the Physical Properties of Sheep Wool Fiber in Amhara National Regional State

Authors: Erkihun Zelalem

Abstract:

Ethiopian’s sheep population, estimated to be 25.5 million heads, is found widely distributed across the diverse agro-ecological zones of the country. In the past, there were many projects that done to improve production of meat, milk and productivity of sheep breed. However, no significance research has been done so far on production of wool fiber in Ethiopia which could be taken as a potential fiber next to cotton. The measurement of the sheep wool fiber physical properties is critically important, technical, commercial and certification point of view. A total of 24 sheep from different breeds (Menz, Tikur, Farta and Washera) were used in this study. Samples of fiber were analyzed using standard measurements for wool fiber length (WFL), mean fiber diameter (MFD), coefficient of variation of wool fiber diameter (FDCV), breaking strength, elongation, crimp, cleanness and moisture content. Based on the result all parameters shows that there is a great potential of getting of wool fiber from the skin of sheep and according to the standards of its property and grading system based on wool fiber fineness is medium to course. These types of fibers can be making carpets, blankets, rugs, coverings and other products.

Keywords: Fiber, Fineness, Carpet, Fleece, Raw Wool

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10 Multi-Spectral Deep Learning Models for Forest Fire Detection

Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

Abstract:

Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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9 Examining Ethiopian Banking Industry in Relation to Factors Affecting Profitability: From 2008 to 2012

Authors: Zelalem Zerihun

Abstract:

In this study, attempts were made to assess the bank-specific, industry-specific, and macro-economic factors affecting bank profitability. Data were collected from ten commercial banks in Ethiopia, covering the period of 2008-2012. A mixed method research approach was adopted for this research. Documentary analysis and in-depth interview were also used to substantiate the data. The study found out that capital strength, income diversification, bank size and gross domestic product are statistically significant and they have a positive relationship with banks’ profitability. However, operational efficiency and asset quality have a negative relationship with banks’ profitability. The relationship for liquidity risk, concentration and inflation were found to be statistically insignificant. The study revealed that focusing and reengineering the banks in light of the key internal drivers could enhance the profitability as well as the performance of the commercial banks in Ethiopia. In addition to this, the study suggests that banks in Ethiopia should not only be concerned about internal structures but also they must consider both the internal environment and the macro-economic environment in designing strategies to improve their profit or their performance.

Keywords: Ethiopian banking industry, macro-economic factors, documentary analysis, capital strength, income diversification

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8 Seroprevalence of Bovine Brucellosis and its Public Health Significance in Selected Sites of Central High Land of Ethiopia

Authors: Temesgen Kassa Getahun, Gezahegn Mamo, Beksisa Urge

Abstract:

A cross-sectional study was conducted from December 2019 to May 2020 with the aim of determining the seroprevalence of brucellosis in dairy cows and their owners in the central highland of Oromia, Ethiopia. A total of 352 blood samples from dairy cattle, 149 from animal owners, and 17 from farm workers were collected and initially screened using the Rose Bengal Plate test and confirmed by the Complement Fixation test. Overall seroprevalence was 0.6% (95% CI: 0.0016–0.0209) in bovines and 1.2% (95% CI: 0.0032–0.0427) in humans. Market-based stock replacement (OR=16.55, p=0.002), breeding by artificial insemination (OR=7.58, p=0.05), and parturition pen (OR = 11.511, p=0.027) were found to be significantly associated with the seropositivity for Brucella infection in dairy cattle. Human housing (OR=1.8, p=0.002), contact with an aborted fetus (OR=21.19, p=0.017), drinking raw milk from non-aborted (OR=24.99, p=0.012), aborted (OR=5.72, p=0.019) and retained fetal membrane (OR=4.22, p=0.029) cows had a significant influence on human brucellosis. A structured interview question was administered to 284 respondents. Accordingly, most respondents had no knowledge of brucellosis (93.3%), and in contrast, 90% of them consumed raw milk. In conclusion, the present seroprevalence study revealed that brucellosis was low among dairy cattle and exposed individuals in the study areas. However, since there were no control strategies implemented in the study areas, there is a potential risk of transmission of brucellosis in dairy cattle and the exposed human population in the study areas. Implementation of a test and slaughter strategy with compensation to farmers is recommended, while in the case of human brucellosis, continuous social training and implementing one health approach framework must be applied.

Keywords: abortion, bovine brucellosis, human brucellosis, risk factors, seroprevalence

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7 Petrogenesis of the Neoproterozoic Rocks of Megele Area, Asosa, Western Ethiopia

Authors: Temesgen Oljira, Olugbenga Akindeji Okunlola, Akinade Shadrach Olatunji, Dereje Ayalew, Bekele Ayele Bedada

Abstract:

The Western Ethiopian Shield (WES) is underlain by volcano-sedimentary terranes, gneissic terranes, and ophiolitic rocks intruded by different granitoid bodies. For the past few years, Neoproterozoic rocks of the Megele area in the western part of the WES have been explored. Understanding the geology of the area and assessing the mineralized area's economic potential requires petrological, geochemical, and geological characterization of the Neoproterozoic granitoids and associated metavolcanic rocks. Thus, the geological, geochemical, and petrogenetic features of Neoproterozoic granitoids and associated metavolcanic rocks were elucidated using a combination of field mapping, petrological, and geochemical study. The Megele area is part of a low-grade volcano-sedimentary zone that has been intruded by mafic (dolerite dyke) and granitoid intrusions (granodiorite, diorite, granite gneiss). The granodiorite, associated diorite, and granite gneiss are calc-alkaline, peraluminous to slightly metaluminous, S-type granitoids formed in volcanic arc subduction (VAG) to syn-collisional (syn-COLD) tectonic setting by fractionation of LREE-enriched, HREE-depleted basaltic magma with considerable crustal input. While the metabasalt is sub-alkaline (tholeiitic), metaluminous bodies are generated at the mid-oceanic ridge tectonic setting by partially melting HREE-depleted and LREE-enriched basaltic magma. The reworking of sediment-loaded crustal blocks at depth in a subduction zone resulted in the production of S-type granitoids. This basaltic magma was supplied from an LREE-enriched, HREE-depleted mantle.

Keywords: fractional crystallization, geochemistry, Megele, petrogenesis, s-type granite

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6 Unsupervised Part-of-Speech Tagging for Amharic Using K-Means Clustering

Authors: Zelalem Fantahun

Abstract:

Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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5 Antecedents and Impacts of Human Capital Flight in the Sub-Saharan Africa with Specific Reference to the Higher Education Sector: Conceptual Model

Authors: Zelalem B. Gurmessa, Ignatius W. Ferreira, Henry F. Wissink

Abstract:

The aim of this paper is to critically examine the factors contributing to academic brain drain in the Sub-Saharan Africa with specific reference to the higher education sector. Africa in general and Sub-Saharan African (SSA) countries, in particular, are experiencing an exodus of highly trained, qualified and competent human resources to other developing and developed countries thereby threatening the overall development of the relevant regions and impeding both public and private service delivery systems in the nation states. The region is currently in a dire situation in terms of health care services, education, science, and technology. The contribution of SSA countries to Science, Technology and Innovation is relatively minimal owing to the migration of skilled professionals due to both push and pull factors. The phenomenon calls for both international and trans-boundary, regional, national and institutional interventions to curb the exodus. Based on secondary data and the review of the literature, the article conceptualizes the antecedents and impacts of human capital flight or brain drain in the SSA countries from a higher education perspective. To this end, the article explores the magnitude, causes, and impacts of brain drain in the region. Despite the lack of consistent data on the magnitude of academic brain drain in the region, a critical analysis of the existing sources shows that pay disparity between developing and developed countries, the lack of enabling working conditions at source countries, fear of security due to political turmoil or unrest, the availability of green pastures and opportunity for development in the receiving countries were identified as major factors contributing to academic brain drain in the region. This hampers the socio-economic, technological and political development of the region. The paper also recommends that further research can be undertaken on the magnitude, causes, characteristics and impact of brain drain on the sustainability and competitiveness of SSA higher education institutions in the region.

Keywords: brain drain, higher education, sub-Saharan Africa, sustainable development

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4 Population Pharmacokinetics of Levofloxacin and Moxifloxacin, and the Probability of Target Attainment in Ethiopian Patients with Multi-Drug Resistant Tuberculosis

Authors: Temesgen Sidamo, Prakruti S. Rao, Eleni Akllilu, Workineh Shibeshi, Yumi Park, Yong-Soon Cho, Jae-Gook Shin, Scott K. Heysell, Stellah G. Mpagama, Ephrem Engidawork

Abstract:

The fluoroquinolones (FQs) are used off-label for the treatment of multidrug-resistant tuberculosis (MDR-TB), and for evaluation in shortening the duration of drug-susceptible TB in recently prioritized regimens. Within the class, levofloxacin (LFX) and moxifloxacin (MXF) play a substantial role in ensuring success in treatment outcomes. However, sub-therapeutic plasma concentrations of either LFX or MXF may drive unfavorable treatment outcomes. To the best of our knowledge, the pharmacokinetics of LFX and MXF in Ethiopian patients with MDR-TB have not yet been investigated. Therefore, the aim of this study was to develop a population pharmacokinetic (PopPK) model of levofloxacin (LFX) and moxifloxacin (MXF) and assess the percent probability of target attainment (PTA) as defined by the ratio of the area under the plasma concentration-time curve over 24-h (AUC0-24) and the in vitro minimum inhibitory concentration (MIC) (AUC0-24/MIC) in Ethiopian MDR-TB patients. Steady-state plasma was collected from 39 MDR-TB patients enrolled in the programmatic treatment course and the drug concentrations were determined using optimized liquid chromatography-tandem mass spectrometry. In addition, the in vitro MIC of the patients' pretreatment clinical isolates was determined. PopPK and simulations were run at various doses, and PK parameters were estimated. The effect of covariates on the PK parameters and the PTA for maximum mycobacterial kill and resistance prevention was also investigated. LFX and MXF both fit in a one-compartment model with adjustments. The apparent volume of distribution (V) and clearance (CL) of LFX were influenced by serum creatinine (Scr), whereas the absorption constant (Ka) and V of MXF were influenced by Scr and BMI, respectively. The PTA for LFX maximal mycobacterial kill at the critical MIC of 0.5 mg/L was 29%, 62%, and 95% with the simulated 750 mg, 1000 mg, and 1500 mg doses, respectively, whereas the PTA for resistance prevention at 1500 mg was only 4.8%, with none of the lower doses achieving this target. At the critical MIC of 0.25 mg/L, there was no difference in the PTA (94.4%) for maximum bacterial kill among the simulated doses of MXF (600 mg, 800 mg, and 1000 mg), but the PTA for resistance prevention improved proportionately with dose. Standard LFX and MXF doses may not provide adequate drug exposure. LFX PopPK is more predictable for maximum mycobacterial kill, whereas MXF's resistance prevention target increases with dose. Scr and BMI are likely to be important covariates in dose optimization or therapeutic drug monitoring (TDM) studies in Ethiopian patients.

Keywords: population PK, PTA, moxifloxacin, levofloxacin, MDR-TB patients, ethiopia

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3 Area Exclosure as a Government Strategy to Restore Woody Plant Species Diversity: Case Study in Southern Ethiopia

Authors: Tsegaw Abebe, Temesgen Abebe

Abstract:

Land degradation is one of a serious environmental challenge in Ethiopia and is one of the major underlying causes for declining agricultural productivity. The Ethiopia government realized the significance of environmental restoration specifically on deforested and degraded land after the 1973 and 1984/85 major famines that struck the country. Among the various conservation strategies, the establishment of area exclosures have been regarded as an effective response to halt and reverse the problems of land degradation. There are limited studies in Ethiopia dealing how the conversion of free grazing lands and degraded lands by closures increase biomass accumulation. However, these studies are not sufficient to conclude about the strength of area closures to restore degraded vegetations at the diverse agro-ecological condition. The overall objective of this study was, therefore, to assess and evaluate the usefulness of area closure technique in enhancing rehabilitation of degraded ecosystem and thereby increase the natural capital in the study site (southern Ethiopia). Woody plant species were collected from area exclosure for eight year and adjacent degraded land with similar landscape positions using systematic sampling plot design technique. Woody species diversity was determined by Shannon diversity. Comparative assessment result of woody plant species analysis showed that the density of woody species in the exclosure and degraded site were 778 and 222 individuals per hectare, respectively. A total of 16 woody species, representing 12 families were recorded in the study site. Out of the 12 families, all were recorded in the exclosure while 5 were recorded in the degraded site. Out of the 16 species, 15 were recorded in the exclosure while six were in the degraded site. A total of 10 species were recorded in the exclosure, which were absent in the degraded site. Similarly, one species was recorded in the degraded site which was not present in the exclosure. The results showed that protecting of degraded site from human and animal disturbances promotes woody plant species regenerations and productivity Apart from increasing woody plant species, the local communities have benefited from the exclosure in the form of both products (grass harvesting) and services (ecological). Due to this reason the local communities have positive attitudes and contribute a lot for the success of enclosures in the study site. The present study clearly showed that area closure interventions should be oriented towards managing and improving the productivity of the degraded land, in such a way that both the need for conservation of biodiversity and environmental sustainability, and the demands of the local people for biomass resources can be achieved.

Keywords: degraded land, exclosure, land restoration, woody vegetation

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2 In vivo Wound Healing Activity and Phytochemical Screening of the Crude Extract and Various Fractions of Kalanchoe petitiana A. Rich (Crassulaceae) Leaves in Mice

Authors: Awol Mekonnen, Temesgen Sidamo, Epherm Engdawork, Kaleab Asresb

Abstract:

Ethnopharmacological Relevance: The leaves of Kalanchoe petitiana A. Rich (Crassulaceae) are used in Ethiopian folk medicine for treatment of evil eye, fractured surface for bone setting and several skin disorders including for the treatment of sores, boils, and malignant wounds. Aim of the Study: In order to scientifically prove the claimed utilization of the plant, the effects of the extracts and the fractions were investigated using in vivo excision, incision and dead space wound models. Materials and Method: Mice were used for wound healing study, while rats and rabbit were used for skin irritation test. For studying healing activity, 80% methanolic extract and the fractions were formulated in strength of 5% and 10%, either as ointment (hydroalcoholic extract, aqueous and methanol fractions) or gel (chloroform fraction). Oral administration of the crude extract was used for dead space model. Negative controls were treated either with simple ointment or sodium carboxyl methyl cellulose xerogel, while positive controls were treated with nitrofurazone (0.2 w/v) skin ointment. Negative controls for dead space model were treated with 1% carboxy methyl cellulose. Parameters, including rate of wound contraction, period of complete epithelializtion, hydroxyproline contents and skin breaking strength were evaluated. Results: Significant wound healing activity was observed with ointment formulated from the crude extract at both 5% and 10% concentration (p<0.01) compared to controls in both excision and incision models. In dead space model, 600 mg/kg (p<0.01), but not 300 mg/kg, significantly increased hydroxyproline content. Fractions showed variable effect, with the chloroform fraction lacking any significant effect. Both 5% and 10% formulations of the aqueous and methanolic fractions significantly increased wound contraction, decreased epithelializtion time and increased hydroxyproline content in excision wound model (p<0.05) as compared to controls. These fractions were also endowed with higher skin breaking strength in incision wound model (p<0.01). Conclusions: The present study provided evidence that the leaves of Kalanchoe petitiana A. Rich possess remarkable wound healing activities supporting the folkloric assertion of the plant. Fractionation revealed that polar or semi-polar compound may play vital role, as both aqueous and methanolic fractions were endowed with wound healing activity.

Keywords: wound healing, Kalanchoae petitiana, excision wound, incision wound, dead space model

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1 Reducing Road Traffic Accident: Rapid Evidence Synthesis for Low and Middle Income Countries

Authors: Tesfaye Dagne, Dagmawit Solomon, Firmaye Bogale, Yosef Gebreyohannes, Samson Mideksa, Mamuye Hadis, Desalegn Ararso, Ermias Woldie, Tsegaye Getachew, Sabit Ababor, Zelalem Kebede

Abstract:

Globally, road traffic accident (RTA) is causing millions of deaths and injuries every year. It is one of the leading causes of death among people of all age groups and the problem is worse among young reproductive age group. Moreover the problem is increasing with an increasing number of vehicles. The majority of the problem happen in low and middle income countries (LMIC), even if the number of vehicles in these countries is low compared to their population. So, the objective of this paper is to summarize the best available evidence on interventions that can reduce road traffic accidents in low and middle income countries (LMIC). Method: A rapid evidence synthesis approach adapted from the SURE Rapid Response Service was applied to search, appraise and summarize the best available evidence on effective intervention in reducing road traffic injury. To answer the question under review, we searched for relevant studies from databases including PubMed, the Cochrane Library, TRANSPORT, Health system evidence, Epistemonikos, and SUPPORT summary. The following key terms were used for searching: Road traffic accident, RTA, Injury, Reduc*, Prevent*, Minimiz*, “Low and middle-income country”, LMIC. We found 18 articles through a search of different databases mentioned above. After screening for the titles and abstracts of the articles, four of them which satisfy the inclusion criteria were included in the final review. Then we appraised and graded the methodological quality of systematic reviews that are deemed to be highly relevant using AMSTAR. Finding: The identified interventions to reduce road traffic accidents were legislation and enforcement, public awareness/education, speed control/ rumble strips, road improvement, mandatory motorcycle helmet, graduated driver license, street lighting. Legislation and Enforcement: Legislation focusing on mandatory motorcycle helmet usage, banning cellular phone usage when driving, seat belt laws, decreasing the legal blood alcohol content (BAC) level from 0.06 g/L to 0.02 g/L bring the best result where enforcement is there. Public Awareness/Education: focusing on seat belt use, child restraint use, educational training in health centers and schools/universities, and public awareness with media through the distribution of videos, posters/souvenirs, and pamphlets are effective in the short run. Speed Control: through traffic calming bumps, or speed bumps, rumbled strips are effective in reducing accidents and fatality. Mandatory Motorcycle Helmet: is associated with reduction in mortality. Graduated driver’s license (GDL): reduce road traffic injury by 19%. Street lighting: is a low-cost intervention which may reduce road traffic accidents.

Keywords: evidence synthesis, injury, rapid review, reducing, road traffic accident

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