Identity and Opportunity
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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 -- -
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 -
Full Length Research Article DEVELOPMENT RESEARCH
Available online at http://www.journalijdr.com International Journal of DEVELOPMENT RESEARCH ISSN: 2230-9926 International Journal of Development Research Vol. 07, Issue, 01, pp.11119-11130, January, 2017 Full Length Research Article DETERMINANTS OF RURAL HOUSEHOLDS’ VULNERABILITY TO POVERTY IN CHENCHA AND ABAYA DISTRICTS, SOUTHERN ETHIOPIA *Fassil Eshetu Abebe Department of Economics, College of Business and Economics, Arba Minch University ARTICLE INFO ABSTRACT Article History: This study primarily aimed to examine the determinants of rural households’ vulnerability to Received 27th October, 2016 poverty and to profile the households according to their level of vulnerability using Feasible Received in revised form Generalized Least Square (FGLS) and Logistic Regression analysis with the help of data collected 28th November, 2016 from a sample of 500 households in two Woredas. The general poverty line of the study area was Accepted 14th December, 2016 determined to be Birr 248 per month per adult equivalent and 29.8 percent of the population in the th Published online 30 January, 2017 study areas were found to be poor. The projected consumption percapita after the three step FGLS estimation revealed that, the incidence of vulnerability to poverty in the area was 34.2 percent and Key Words: therefore, vulnerability was more spread in the study areas than ex post poverty. Using the two Poverty, Vulnerability, vulnerability thresholds, observed poverty rate (0.298) and vulnerability of 0.5, about 28.6%, Feasible Generalized Least Square, 5.6% and 65.8% of households were highly vulnerable, low vulnerable and not vulnerable Logit Model and Ethiopia. respectively. Most importantly, from the total poor households about 81.75%, 3.25% and 15% were highly vulnerable, low vulnerable and not vulnerable respectively. -
Land Use Patterns and Its Implication for Climate Change: the Case of Gamo Gofa, Southern Ethiopia
Defaru Debebe. et al., IJSRR 2013, 2(3), 155-173 Research article Available online www.ijsrr.org ISSN: 2279–0543 International Journal of Scientific Research and Reviews Land Use Patterns and its Implication for Climate Change: The Case of Gamo Gofa, Southern Ethiopia Defaru Debebe* and Tuma Ayele Arba Minch University P.O.Box 21, Arba Minch, Ethiopia ABSTRACT Land is one of three major factors of production in classical economics (along with labor and capital) and an essential input for housing and crop production. Land use is the backbone of agriculture and it provides substantial economic and social benefits. Assessing past-to present land use patterns associated with the crop production helps to understand which climatic effects might arise due to expanding crop cultivation. This study was conducted to evaluate the land use pattern and its implication for climate change in Gamo Gofa, Southern Ethiopia. For evaluation, correlation and time series trend analysis were used. Results revealed that a significant reduction in cultivable land, which was converted into cropland and might increase deforestation and greenhouse gas emission, in turn induce climate change. The correlation between cropland and fertile (cultivable) land (r=0.22674) in 2005 improved to (r=0.75734) in 2012 indicating major shift of fertile land to cropland in seven years interval. On other side, twelve years (1987-1999 and 2000-2011) average maximum temperature difference in Gamo Gafa was increased 0.425oC with standard deviation 0.331. It is statistically significant (t =1.284, alpha=0.10) at 10% level of error. Moreover, the spatial differences in climate change are likely to imply a heterogeneous pattern of land use responses. -
The Case of Sasakawa Global 2000 Ethiopia in Gumer Woreda By
Addis Ababa University School of Graduate Studies College of Business and Economics Department of Public Administration and Development Management Assessing the role of Development partners on agricultural extension delivery: The case of Sasakawa Global 2000 Ethiopia in Gumer woreda By: Temesgen Tamrat Advisor: Mulugeta Abebe (PH.D) A thesis submitted to the School of Graduate Studies of Addis Ababa University in partial fulfillment of the requirements for the Degree of Masters in Public Management and Policy (MPMP) Specialized In Development Management June, 2017 Addis Ababa, Ethiopia Addis Ababa University School of Graduate Studies College of Business and Economics Department of Public Administration and Development Management This is to certify that the thesis prepared by Temesgen Tamrat Yohans entitled “Assessing the role of Development partners on agricultural extension delivery: The case of Sasakawa Global 2000 Ethiopia in Gumer woreda”, which is submitted in partial fulfillment of the requirements for the Degree of Public Management and Policy (MPMP), complies with the regulations of the University and meets the accepted standards with respect to standards to originality and quality. Approved by Board of Examiners: Mulugeta Abebe (PhD) ___________________ _______________ Advisor Signature Date Elias Berhanu (PhD) ___________________ _________________ Internal Examiner Signature Date Flimon Handaro (PhD) ___________________ _______________ External Examiner Signature Date Declaration Student ID: GSE/0632/06 I declare that this research report on ‘Assessing the role of Development partners on agricultural extension delivery:The case of Sasakawa Global 2000 Ethiopia in Gumer woreda’ is my own original work with assistances and guidance from my advisor and not submitted before for any institution and any purpose. -
Hygienic Practice Among Milk and Cottage Cheese Handlers in Districts of Gamo and Gofa Zone, Southern Ethiopia
Research Article Volume 12:2, 2021 Journal of Veterinary Science & Technology ISSN: 2157-7579 Open Access Knowledge; Hygienic Practice among Milk and Cottage Cheese Handlers in Districts of Gamo and Gofa Zone, Southern Ethiopia Edget Alembo* Department of Animal Science, Arba Minch University, Arba Minch, Ethiopia Abstract A cross-sectional questionnaire survey was conducted in Arba Minch Zuria and Demba Gofa districts of Gamo and Gofa Zone of the Southern nation nationalities and people’s regional state with the objectives of assessing knowledge of hygienic practice of milk and cheese handlers in both study area. For this a total of 102 farmers who involved in milking, collecting and retailing of milk were included in the study area. Data obtained from questionnaire survey were analyzed by descriptive statistics and Chi –square test, using the Statistical package for social science (SPSS Version 17). The participants of this study were woman of different age group and 27(52.9%) of participants in Arba Minch Zuria and 32(64.7%) in Demba Gofa were >36 years old. The majority of participants 21(41.2%) and 22(43.1%) were educated up to grade 1-8 in Arba Minch Zuria and Demba Gofa, respectively. This had an impact on hygienic practice of milking and milk handling. The difference in hygienic handling, training obtained and cheese making practice among the study areas were statistically significant (p<0.05). There was also a statistically significant difference in hand washing and utensil as well as manner of washing between the two study areas (p<0.01). Finally this study revealed that there were no variation in Antibiotic usage and Practice of treating sick animal in both study area (p>0.05) with significant difference in Prognosis, Level of skin infection and Selling practice among study participants in both study areas (p<0.05). -
Awareness of Community on Fishery and Aquaculture Production in Central Ethiopia
Alemu A. J Aquac Fisheries 2021, 5: 039 DOI: 10.24966/AAF-5523/100039 HSOA Journal of Aquaculture & Fisheries Research Article The domestic fishery of Africa involvement is projected to be Awareness of Community about 2.1 million tons of fish per year; it epitomizes 24% of the total world fish production from inland water bodies. The inland water on Fishery and Aquaculture body of Ethiopia is enclosed about 7,400 km2 of the lakes and about 7,000 km a total length of the rivers [2]. Further, 180 fish species were Production in Central Ethiopia harbored in these water bodies [3]. In Ethiopia, fish comes exclusively from inland water bodies with lakes, rivers, streams, reservoirs and substantial wetlands that are of great socio-economic, ecological and Tena Alemu * scientific importance [4,5]. Department of Animal Production and Technology, Wolkite University, Wol- kite, Ethiopia Ethiopia being a land locked country its fisheries is entirely based on inland water bodies, lakes, reservoirs and rivers. Fish production potential of the country is estimated to be 51,400 tonnes per annum [6]. Fishing has been the main source of protein supply for many Abstract people particularly for those who are residing in the locality of major water bodies like Lake Tana, Ziway, Awassa, Chamo, Baro River, etc The study was conducted in three different districts Gumer, [5]. Ethiopia is capable with numerous water bodies that cover a high Enemornaener and Cheha Woreda on awareness and perception of community on fishery and aquaculture production. In those diversity of aquatic wildlife. Reservoir fishery plays an important study areas majority of the people had the limitation of knowledge role in the economy of the country and the livelihoods of the people on production, consumption, and use of fish and aquaculture living adjacent to those reservoirs. -
World Vision Etiopia
FOOD SECURITY MONITORING REPORT OF NOVEMBER 1999 WORLD VISION ETIOPIA FOOD SECURITY MONITORING REPORT OF NOVEMBER 1999 Grants division February 2000 Addis Ababa FOOD SECURITY MONITORING REPORT OF NOVEMBER 1999 TABLE OF CONTENTS I. EXECUTIVE SUMMARY.............................................................................................................................6 II. SURVEY RESULT CLASSIFICATION AND INTERPRETATION ..............................................................7 III. TIGRAY REGIONAL STATE.........................................................................................................................8 3.1. ATSBI WOMBERTA AND TSEDA AMBA WOREDAS (KILTE AWLAELO ADP) ....................................................8 3.1.1. Back Ground ........................................................................................................................................8 3.1.2. Crop and Livestock Assessment.............................................................................................................8 3.1.3. Market Performance .............................................................................................................................8 3.1.4. Socio-Economic Conditions ..................................................................................................................9 3.1.5. Anthropometric Measurements..............................................................................................................9 IV. AMHARA REGIONAL STATE......................................................................................................................9 -
Army Worm Infestation in SNNP and Oromia Regions As of 24 May
Army worm infestation in SNNP and Oromia Regions As of 24 May, some 8,368 hectares of belg cropland was reportedly destroyed by army worms in Wolayita zone of SNNPR - an area that suffered from late onset of the 2013 belg rains and subsequent heavy rains that damaged belg crops. The damage caused by the army worms will further reduce the expected harvest this season. Similar incidents were also reported from Boricha, Bona Zuria, Dara, Dale, Hawassa Zuria and Loko Abaya woredas of Sidama zone; Loma and Mareka woredas of Dawro zone (SNNPR), as well as from drought prone areas of East and West Hararge zones of Oromia Region; and quickly spreading to neighbouring areas. In Boricha woreda, for example, more than 655 hectares of belg cropland was destroyed in the course of one week, this is indicative of the speed that damage is being caused. Immediate distribution of spraying containers and chemicals to the farmers is required to prevent further loss of belg crops. For more information, contact: [email protected] Health Update The number of meningitis cases has gradually declined since the outbreak was declared in January. To date, 1,371 cases were reported from 24 woredas in five zones of SNNP and Oromia Regions. The Government, with support from health partners, is conducting a reactive vaccination in the affected areas, with 1, 678,220 people vaccinated so far. Next week, the number of people vaccinated during the Addis Ababa City Administration meningitis vaccination campaign, conducted from 20 to 26 May, will be released. Meanwhile, the number of kebeles reporting cases of Yellow Fever in South Ari, Benatsemay and Selmago woredas of South Omo zone, SNNPR, increased. -
Alaba Pilot Learning Site Diagnosis and Program Design
ALABA PILOT LEARNING SITE DIAGNOSIS AND PROGRAM DESIGN July 15, 2005 1 Table of Contents 1. INTRODUCTION................................................................................................................................. 5 2. FARMING SYSTEMS, CROP AND LIVESTOCK PRIORITIES ......................................................... 6 2.1 Description of Alaba Woreda ............................................................................................... 6 2.2 Priority farming systems..................................................................................................... 11 2.3 Priority crop commodities...................................................................................................13 2.4 Priority livestock commodities............................................................................................ 18 2.5 Natural Resources Conservation....................................................................................... 19 3. INSTITUTIONS ................................................................................................................................. 21 3.1 Marketing ........................................................................................................................... 21 3.2 Input supply........................................................................................................................ 22 3.3 Rural finance..................................................................................................................... -
Social and Environmental Risk Factors for Trachoma: a Mixed Methods Approach in the Kembata Zone of Southern Ethiopia
Social and Environmental Risk Factors for Trachoma: A Mixed Methods Approach in the Kembata Zone of Southern Ethiopia by Candace Vinke B.Sc., University of Calgary, 2005 A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of MASTER OF ARTS in the Department of Geography Candace Vinke, 2010 University of Victoria All rights reserved. This thesis may not be reproduced in whole or in part, by photocopy or other means, without the permission of the author. ii Supervisory Committee Social and Environmental Risk Factors for Trachoma: A Mixed Methods Approach in the Kembata Zone of Southern Ethiopia by Candace Vinke Bachelor of Science, University of Calgary, 2005 Supervisory Committee Dr. Stephen Lonergan, Supervisor (Department of Geography) Dr. Denise Cloutier-Fisher, Departmental Member (Department of Geography) Dr. Eric Roth, Outside Member (Department of Anthropology) iii Dr. Stephen Lonergan, Supervisor (Department of Geography) Dr. Denise Cloutier-Fisher, Departmental Member (Department of Geography) Dr. Eric Roth, Outside Member (Department of Anthropology) Abstract Trachoma is a major public health concern throughout Ethiopia and other parts of the developing world. Control efforts have largely focused on the antibiotic treatment (A) and surgery (S) components of the World Health Organizations (WHO) SAFE strategy. Although S and A efforts have had a positive impact, this approach may not be sustainable. Consequently, this study focuses on the latter two primary prevention components; facial cleanliness (F) and environmental improvement (E). A geographical approach is employed to gain a better understanding of how culture, economics, environment and behaviour are interacting to determine disease risk in the Kembata Zone of Southern Ethiopia. -
Census Data/Projections, 1999 & 2000
Census data/Projections, 1999 & 2000 Jan - June and July - December Relief Bens., Supplementary Feeding Bens. TIGRAY Zone 1994 census 1999 beneficiaries - May '99 2000 beneficiaries - Jan 2000 July - Dec 2000 Bens Zone ID/prior Wereda Total Pop. 1999 Pop. 1999 Bens. 1999 bens % 2000 Pop. 2000 Bens 2000 bens Bens. Sup. July - Dec Bens July - Dec Bens ity Estimate of Pop. Estimate % of Pop. Feeding % of pop 1 ASEGEDE TSIMBELA 96,115 111,424 114,766 1 KAFTA HUMERA 48,690 56,445 58,138 1 LAELAY ADIYABO 79,832 92,547 5,590 6% 95,324 7,800 8% 11,300 12% Western 1 MEDEBAY ZANA 97,237 112,724 116,106 2,100 2% 4,180 4% 1 TAHTAY ADIYABO 80,934 93,825 6,420 7% 96,639 18,300 19% 24,047 25% 1 TAHTAY KORARO 83,492 96,790 99,694 2,800 3% 2,800 3% 1 TSEGEDE 59,846 69,378 71,459 1 TSILEMTI 97,630 113,180 37,990 34% 116,575 43,000 37% 15,050 46,074 40% 1 WELKAIT 90,186 104,550 107,687 Sub Total 733,962 850,863 50,000 6% 876,389 74,000 8% 15,050 88,401 10% *2 ABERGELE 58,373 67,670 11,480 17% 69,700 52,200 75% 18,270 67,430 97% *2 ADWA 109,203 126,596 9,940 8% 130,394 39,600 30% 13,860 58,600 45% 2 DEGUA TEMBEN 89,037 103,218 7,360 7% 106,315 34,000 32% 11,900 44,000 41% Central 2 ENTICHO 131,168 152,060 22,850 15% 156,621 82,300 53% 28,805 92,300 59% 2 KOLA TEMBEN 113,712 131,823 12,040 9% 135,778 62,700 46% 21,945 67,700 50% 2 LAELAY MAYCHEW 90,123 104,477 3,840 4% 107,612 19,600 18% 6,860 22,941 21% 2 MEREB LEHE 78,094 90,532 14,900 16% 93,248 57,500 62% 20,125 75,158 81% *2 NAEDER ADET 84,942 98,471 15,000 15% 101,425 40,800 40% 14,280 62,803 62% 2