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Districts of Ethiopia
Region District or Woredas Zone Remarks Afar Region Argobba Special Woreda -- Independent district/woredas Afar Region Afambo Zone 1 (Awsi Rasu) Afar Region Asayita Zone 1 (Awsi Rasu) Afar Region Chifra Zone 1 (Awsi Rasu) Afar Region Dubti Zone 1 (Awsi Rasu) Afar Region Elidar Zone 1 (Awsi Rasu) Afar Region Kori Zone 1 (Awsi Rasu) Afar Region Mille Zone 1 (Awsi Rasu) Afar Region Abala Zone 2 (Kilbet Rasu) Afar Region Afdera Zone 2 (Kilbet Rasu) Afar Region Berhale Zone 2 (Kilbet Rasu) Afar Region Dallol Zone 2 (Kilbet Rasu) Afar Region Erebti Zone 2 (Kilbet Rasu) Afar Region Koneba Zone 2 (Kilbet Rasu) Afar Region Megale Zone 2 (Kilbet Rasu) Afar Region Amibara Zone 3 (Gabi Rasu) Afar Region Awash Fentale Zone 3 (Gabi Rasu) Afar Region Bure Mudaytu Zone 3 (Gabi Rasu) Afar Region Dulecha Zone 3 (Gabi Rasu) Afar Region Gewane Zone 3 (Gabi Rasu) Afar Region Aura Zone 4 (Fantena Rasu) Afar Region Ewa Zone 4 (Fantena Rasu) Afar Region Gulina Zone 4 (Fantena Rasu) Afar Region Teru Zone 4 (Fantena Rasu) Afar Region Yalo Zone 4 (Fantena Rasu) Afar Region Dalifage (formerly known as Artuma) Zone 5 (Hari Rasu) Afar Region Dewe Zone 5 (Hari Rasu) Afar Region Hadele Ele (formerly known as Fursi) Zone 5 (Hari Rasu) Afar Region Simurobi Gele'alo Zone 5 (Hari Rasu) Afar Region Telalak Zone 5 (Hari Rasu) Amhara Region Achefer -- Defunct district/woredas Amhara Region Angolalla Terana Asagirt -- Defunct district/woredas Amhara Region Artuma Fursina Jile -- Defunct district/woredas Amhara Region Banja -- Defunct district/woredas Amhara Region Belessa -- -
Ethiopia: 2015 HRF Projects Map (As of 31 December 2015)
Ethiopia: 2015 HRF projects map (as of 31 December 2015) Countrywide intervention ERITREA Legend UNICEF - Nutrition - $999,753 Concern☃ - VSF-G ☈ ! Refugee camp WFP - Nutrition (CSB) - $1.5m National capital Shimelba Red Sea SUDAN Regional intervention International boundary Hitsa!ts Dalul UNICEF - Health - $1.0m ! !Hitsats ! ! Undetermined boundary ! ! SCI Tigray, Afar, Amhara, Oromia, Kelete Berahile ☃☉ May-Ayni Kola ! Somali, Gambella, SNPR & NRC - ☉ Ts!elemti Temben Awelallo Lake IRC - ★ ! ☄ ! ♫ Tanqua ! SUDAN ! ! ! Dire Dawa Adi Harush ! Enderta Abergele ! Ab Ala Afdera Project woredas Tselemt ! NRC - Debark GAA - ☇ ! WFP (UNHAS) - Coordination ☈ Abergele! Erebti ☋☉ Plan Int. - ACF - ☃ Dabat Sahla ☃Megale Bidu and Support Service - $740,703 Janamora Wegera! Clusters/Activities ! Ziquala Somali region Sekota ! ! Concern - SCI Teru ! Agriculture CRS - Agriculture/Seed - $2,5m ☃ ☃ Kurri ! Dehana ! ☋ ! Gaz Alamata ! Elidar GAA - ☋ Amhara,Ormia and SNNP regions ! ☃☉ Gonder Zuria Gibla ! Gulf of ! Education Plan Int. - Ebenat Kobo SCI☃☉ ☃ ! Gidan ☄ Lasta ! Aden CARE - Lay Guba ! Ewa ! ☃ ! Meket Lafto Gayint ! Food security & livelihood WV - ☃ Dubti ☈ ☉ ! Tach Habru Chifra SCI - ☃ Delanta ! ! - Tigray Region, Eastern Zone, Kelete Awelall, ! Gayint IMC - ☃ Health ☉ Simada Southern Zone, Alamata and Enderta woredas ! ! Mile DJIBOUTI ☊ Mekdela ! Bati Enbise SCI- Nutrition ! Argoba ☃☉ WV - ☃ Sar Midir Legambo ☃ ! Oxfam GB - Enarj ! ☉ ! ! Ayisha Non Food Items - Amhara region, North Gonder (Gonder Zuria), Enawga ! Antsokiya Dalfagi ! ! ! Concern -
Midterm Survey Protocol
Protocol for L10K Midterm Survey The Last 10 Kilometers Project JSI Research & Training Institute, Inc. Addis Ababa, Ethiopia October 2010 Contents Introduction ........................................................................................................................................................ 2 The Last Ten Kilometers Project ............................................................................................................ 3 Objective one activities cover all the L10K woredas: .......................................................................... 4 Activities for objectives two, three and four in selected woredas ...................................................... 5 The purpose of the midterm survey ....................................................................................................... 6 The midterm survey design ...................................................................................................................... 7 Annex 1: List of L10K woredas by region, implementation strategy, and implementing phase ......... 10 Annex 2: Maps.................................................................................................................................................. 11 Annex 3: Research questions with their corresponding study design ...................................................... 14 Annex 4: Baseline survey methodology ........................................................................................................ 15 Annex 5: L10K midterm survey -
Assessment and Prioritization of Major Camel Diseases in Selected Areas of Afar Regional State, Samara, Ethiopia
Middle East Journal of Applied Science & Technology (MEJAST) (Peer Reviewed International Journal) Volume 3, Issue 1, Pages 23-32, January-March 2020 Assessment and Prioritization of Major Camel Diseases in Selected Areas of Afar Regional State, Samara, Ethiopia Wossene Negash1*, Nuru Seid1 & Fikru Gizaw1 1College of Veterinary Medicine, Samara University, P.O. Box, 132, Samara, Ethiopia. 1*Email: [email protected] Article Received: 11 December 2019 Article Accepted: 07 February 2020 Article Published: 17 March 2020 ABSTRACT A cross sectional study was carried out from January to July 2014 GC in an attempt to assess and prioritize major camel diseases and identify risk factors in the selected areas of Afar region. Camel owners’ interview and retrospective data analysis were the study methods employed. Relevant collected data were organized, filtered and fed into Microsoft Excel sheet and further analyzed using SPSS statistical tools at P< 0.05. Descriptive statistics was carried to determine frequencies of camel diseases camel. Based on descriptive statistics, the study identified and prioritized 16 camel diseases. Chi-Square analysis was computed to measure the degree of association between disease occurrence and risk factors (age, sex, study area and season). Binomial and multinomial logistic regression analyzes were computed at P<0.05 to measure the significance of associated risk factors on disease occurrence. Statistically significant variations (P<0.05) were observed for sex, seasons, age, and study sites on the occurrence of disease with exception kebeles (P>0.05). Though the study duly has revealed numerous diseases of the camel, the actual existence (laboratory based confirmation) and epidemiology of each disease still demands further investigative studies. -
Analysis of Five-Year Trend of Malaria at Bichena Primary Hospital, Amhara Region, Ethiopia
Hindawi Journal of Parasitology Research Volume 2021, Article ID 6699373, 6 pages https://doi.org/10.1155/2021/6699373 Research Article Analysis of Five-Year Trend of Malaria at Bichena Primary Hospital, Amhara Region, Ethiopia Awoke Minwuyelet1 and Yibeltal Aschale 2 1Bichena Primary Hospital, Amhara Region, Ethiopia 2Department of Medical Laboratory Sciences, College of Health Sciences, Debre Markos University, Debre Markos, Ethiopia Correspondence should be addressed to Yibeltal Aschale; [email protected] Received 24 November 2020; Revised 1 January 2021; Accepted 18 January 2021; Published 29 January 2021 Academic Editor: Bernard Marchand Copyright © 2021 Awoke Minwuyelet and Yibeltal Aschale. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Malaria is a life-threating infectious diseases caused by protozoan parasite of the genus Plasmodium. The WHO African region bears the largest burden of malaria morbidity and mortality every year. Prevention and control activity of malaria in Ethiopia is implemented as guided by a national strategic plan to decrease malaria burden. This study is aimed at assessing the five-year trend of malaria at Bichena Primary Hospital. Method. A retrospective study was conducted at Bichena Primary Hospital to assess the five-year (2015-2019) trend of malaria by reviewing blood film reports from a laboratory logbook. Result.Inafive-year period, 9182 blood films were requested for malaria diagnosis of whom 53.8% were males and 41% were in the age group 15-29. The overall prevalence of malaria was 9.28% (n = 852), P. -
Food Supply Prospects - 2009
FOOD SUPPLY PROSPECTS - 2009 Disaster Management and Food Security Sector (DMFSS) Ministry of Agriculture and Rural Development (MoARD) Addis Ababa Ethiopia February 10, 2009 TABLE OF CONTENTS Pages LIST OF GLOSSARY OF LOCAL NAMES 2 ACRONYMS 3 EXECUTIVE SUMMARY 5 - 8 INTRODUCTION 9 - 12 REGIONAL SUMMARY 1. SOMALI 13 - 17 2. AMHARA 18 – 22 3. SNNPR 23 – 28 4. OROMIYA 29 – 32 5. TIGRAY 33 – 36 6. AFAR 37 – 40 7. BENSHANGUL GUMUZ 41 – 42 8. GAMBELLA 43 - 44 9. DIRE DAWA ADMINISTRATIVE COUNSEL 44 – 46 10. HARARI 47 - 48 ANNEX – 1 NEEDY POPULATION AND FOOD REQUIREMENT BY WOREDA 2 Glossary Azmera Rains from early March to early June (Tigray) Belg Short rainy season from February/March to June/July (National) Birkads cemented water reservoir Chat Mildly narcotic shrub grown as cash crop Dega Highlands (altitude>2500 meters) Deyr Short rains from October to November (Somali Region) Ellas Traditional deep wells Enset False Banana Plant Gena Belg season during February to May (Borena and Guji zones) Gu Main rains from March to June ( Somali Region) Haga Dry season from mid July to end of September (Southern zone of of Somali ) Hagaya Short rains from October to November (Borena/Bale) Jilal Long dry season from January to March ( Somali Region) Karan Rains from mid-July to September in the Northern zones of Somali region ( Jijiga and Shinile zones) Karma Main rains fro July to September (Afar) Kolla Lowlands (altitude <1500meters) Meher/Kiremt Main rainy season from June to September in crop dependent areas Sugum Short rains ( not more than 5 days -
Research Article Assessment of Major Animal Health Problems and Their Impact on Beef Cattle Production in Doba District of West Harerghe Zone, Ethiopia
Hindawi Veterinary Medicine International Volume 2021, Article ID 5533398, 5 pages https://doi.org/10.1155/2021/5533398 Research Article Assessment of Major Animal Health Problems and Their Impact on Beef Cattle Production in Doba District of West Harerghe Zone, Ethiopia Umer Seid Geletu ,1 Ahmedin Abdureman Musa,1 Sisay Lemma Waqe,1 Munera Ahmednur Usmael,2 Yesihak Yusuf Mummed,3 Fufa Dawo Bari,4 and Abdulmuen Mohammed Ibrahim5 1College of Agriculture, Department Animal Science, Oda Bultum University, P.O. Box 226, Chiro, Ethiopia 2Oromia Bureau Livestock and Fishery Resources, West Hararghe Zone, Chiro Wereda, P.O. Box 226, Chiro, Ethiopia 3School of Animal Science and Randge Land, Haramaya University, Dire Dawa, Ethiopia 4Department of Microbiology, Immunology and Veterinary Public Health, College of Veterinary Medicine and Agriculture, Addis Ababa University, P.O. Box 34, Bishoftu, Addis Ababa, Ethiopia 5Office of Research Affairs, Haramaya University, Dire Dawa, Ethiopia Correspondence should be addressed to Umer Seid Geletu; [email protected] Received 7 February 2021; Accepted 5 August 2021; Published 24 August 2021 Academic Editor: Carlos Alberto Hussni Copyright © 2021 Umer Seid Geletu et al. (is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (e aim of the current study was to assess the major animal health problems and their impact on beef cattle production in Doba district of West Harerghe Zone, Ethiopia. (e study area was purposively selected, and a simple random sampling method was used to selected households’ fatteners from each kebele and interviewed using structured questionnaires. -
Protecting Land Tenure Security of Women in Ethiopia: Evidence from the Land Investment for Transformation Program
PROTECTING LAND TENURE SECURITY OF WOMEN IN ETHIOPIA: EVIDENCE FROM THE LAND INVESTMENT FOR TRANSFORMATION PROGRAM Workwoha Mekonen, Ziade Hailu, John Leckie, and Gladys Savolainen Land Investment for Transformation Programme (LIFT) (DAI Global) This research paper was created with funding and technical support of the Research Consortium on Women’s Land Rights, an initiative of Resource Equity. The Research Consortium on Women’s Land Rights is a community of learning and practice that works to increase the quantity and strengthen the quality of research on interventions to advance women’s land and resource rights. Among other things, the Consortium commissions new research that promotes innovations in practice and addresses gaps in evidence on what works to improve women’s land rights. Learn more about the Research Consortium on Women’s Land Rights by visiting https://consortium.resourceequity.org/ This paper assesses the effectiveness of a specific land tenure intervention to improve the lives of women, by asking new questions of available project data sets. ABSTRACT The purpose of this research is to investigate threats to women’s land rights and explore the effectiveness of land certification interventions using evidence from the Land Investment for Transformation (LIFT) program in Ethiopia. More specifically, the study aims to provide evidence on the extent that LIFT contributed to women’s tenure security. The research used a mixed method approach that integrated quantitative and qualitative data. Quantitative information was analyzed from the profiles of more than seven million parcels to understand how the program had incorporated gender interests into the Second Level Land Certification (SLLC) process. -
ETHIOPIA - National Hot Spot Map 31 May 2010
ETHIOPIA - National Hot Spot Map 31 May 2010 R Legend Eritrea E Tigray R egion !ª D 450 ho uses burned do wn d ue to th e re ce nt International Boundary !ª !ª Ahferom Sudan Tahtay Erob fire incid ent in Keft a hum era woreda. I nhabitan ts Laelay Ahferom !ª Regional Boundary > Mereb Leke " !ª S are repo rted to be lef t out o f sh elter; UNI CEF !ª Adiyabo Adiyabo Gulomekeda W W W 7 Dalul E !Ò Laelay togethe r w ith the regiona l g ove rnm ent is Zonal Boundary North Western A Kafta Humera Maychew Eastern !ª sup portin g the victim s with provision o f wate r Measle Cas es Woreda Boundary Central and oth er imm ediate n eeds Measles co ntinues to b e re ported > Western Berahle with new four cases in Arada Zone 2 Lakes WBN BN Tsel emt !A !ª A! Sub-city,Ad dis Ababa ; and one Addi Arekay> W b Afa r Region N b Afdera Military Operation BeyedaB Ab Ala ! case in Ahfe rom woreda, Tig ray > > bb The re a re d isplaced pe ople from fo ur A Debark > > b o N W b B N Abergele Erebtoi B N W Southern keb eles of Mille and also five kebeles B N Janam ora Moegale Bidu Dabat Wag HiomraW B of Da llol woreda s (400 0 persons) a ff ected Hot Spot Areas AWD C ases N N N > N > B B W Sahl a B W > B N W Raya A zebo due to flo oding from Awash rive r an d ru n Since t he beg in nin g of th e year, Wegera B N No Data/No Humanitarian Concern > Ziquala Sekota B a total of 967 cases of AWD w ith East bb BN > Teru > off fro m Tigray highlands, respective ly. -
73-84 Association of Arabica Coffee Quality Attributes with Selected So
East African Journal of Sciences (2015) Volume 9 (2) 73-84 Association of Arabica Coffee Quality Attributes with Selected Soil Chemical Properties Adugnaw Mintesnot1*, Nigussie Dechassa2,and Ali Mohammed1 1Jimma University, Department of Horticulture, P. O. Box 307, Jimma, Ethiopia 2Haramaya University, Department of Plant Sciences, P. O. Box 138, Dire Dawa, Ethiopia Abstract: Coffee (Coffea arabica L.) bean quality attributes differ based on the origin of the produce. Several agro-ecological conditions influence coffee bean quality attributes. Soil chemical properties may be some of the factors affecting the quality attributes. However, no study has so far been conducted to elucidate the association of coffee bean qualities with soil chemical properties in both major and minor coffee growing regions of Ethiopia. Thus, this research was conducted with the objective of establishing association of chemical soil properties with coffee cup quality attributes. Coffee beans as well as soil samples from which the beans originated were subjected to chemical analysis. The coffee beans and the corresponding soil samples originated from large scale coffee plantations (Bebeka, Gemadro and Goma), districts from southwestern major coffee growing region (Gore, Jimma, Lemkefa), West (Gimbi), East (Badano, Chiro, Darolebu, Habro and Melkabelo), South (Yirgacheffe) and northwestern minor coffee growing districts (Ankasha, Bure, Mecha and Jabi). The soil samples were collected from the depth of 0 - 50 cm near the coffee trunks and samples of ripe coffee cherries were picked up from the trees during the 2010/11 harvest season. Selected chemical properties of the soil, namely, available potassium, cation exchange capacity, exchangeable acidity, exchangeable bases, available micronutrients, available phosphorus, total nitrogen, soil pH, electrical conductivity, and percent organic carbon were determined from 53 soil samples in Jimma University soil laboratory and Wolkitie Soil Testing and Soil Fertility Improvement Centre using the established procedures. -
Floristic Composition and Carbon Pools Along Altitudinal Gradient: the Case of Gara–Muktar Forest, West Hararghe Zone, Eastern Ethiopia
Forestry Research and Engineering: International Journal Research Article Open Access Floristic composition and carbon pools along altitudinal gradient: the case of gara–muktar forest, west hararghe zone, eastern Ethiopia Abstract Volume 4 Issue 1 - 2020 Forests play vital role in combating climate change through carbon sequestration in the Asaminew Wodajo,1 Mehari A Tesfaye,2 atmosphere and serving as a carbon sink in the form of carbon pool systems of forest 3 ecosystems. The species composition and carbon stock in the different carbon pools Muktar Mohammed 1Bonga Agricultural Research Centre, Ethiopia, and analysis of the influence of the environmental gradients were studied by systematic 2Central Ethiopia Environment and Forest Research, Ethiopia sampling method collecting data in thirty-six quadrant plots of 20x20m each distributed 3Oda Bultum Universities, Ethiopia along transect lines. Diameter at breast ≥5cm and total height measured for each tree in the main plot. Above and below ground biomass was estimated using allometric equation, Correspondence: Mehari Alebachew Tesfaye, Central Ethiopia while the litter carbon was estimated by taking 50% of dry biomass as carbon. Soil sample Environment and Forest Research Centre box 30708, Addis was collected using auguring method and analyzed following Walkley-Black method, Ababa, Ethiopia, Tele +251911356756, while bulk density was performed using core sampling method. The data was analyzed Email was performed using one way ANOVA of R software. The carbon stocks in aboveground, belowground, litter biomass and soil organic carbon showed distinct variation along Received: November 27, 2020 | Published: February 28, 2020 environmental gradients. The aboveground and below ground carbon stock was showed a decreasing trend along with increasing altitude, while soil organic carbon and liter carbon showed increasing trend along with increasing in altitude. -
Ethiopia Bellmon Analysis 2015/16 and Reassessment of Crop
Ethiopia Bellmon Analysis 2015/16 And Reassessment Of Crop Production and Marketing For 2014/15 October 2015 Final Report Ethiopia: Bellmon Analysis - 2014/15 i Table of Contents Acknowledgements ................................................................................................................................................ iii Table of Acronyms ................................................................................................................................................. iii Executive Summary ............................................................................................................................................... iv Introduction ................................................................................................................................................................ 9 Methodology .................................................................................................................................................. 10 Economic Background ......................................................................................................................................... 11 Poverty ............................................................................................................................................................. 14 Wage Labor ..................................................................................................................................................... 15 Agriculture Sector Overview ............................................................................................................................