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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 -- -
Study on Prevalence of Bovine Trypanosomosis and Apparent Density of Tsetse Fly in Borecha Woreda, South-Western Ethiopia
Open Access Austin Journal of Veterinary Science & Animal Husbandry Research Article Study on Prevalence of Bovine Trypanosomosis and Apparent Density of Tsetse Fly in Borecha Woreda, South-Western Ethiopia Shewangizaw G and Takele S* National Institute for Control and Eradication of Tsetse Abstract Fly and Trypanosomosis, Ethiopia Background: Animal trypanosomiasis is an economically significant disease *Corresponding author: Samson Takele, National that affects the livestock industry in Ethiopia. However, national estimates of the Institute for Control and Eradication of Tsetse Fly and disease prevalence in livestock and tsetse flies are lacking, therefore a cross- Trypanosomosis, Bedele Center, PO-Box 19917, Ethiopia sectional study aimed at determining the prevalence of bovine trypanosomosis and assessing the apparent density of tsetse flies was conducted from November Received: December 04, 2020; Accepted: December to December 2019 in Borecha Woreda, South-Western Ethiopia. 28, 2020; Published: January 04, 2021 Methodology: Blood samples collected from 384 randomly selected cattle and subjected to parasitological and hematological analysis. The Packed Cell Volume (PCV) value of each animal was also measured using a hematocrit reader. Standard isolation and identification procedures were performed to identify trypanosome isolates. Baited different types of traps were used for the vector survey. Results: A total of 278 tsetse flies were collected. Only one species, namely, G. Tachnoides, was recorded from the area. The overall prevalence of trypanosomes was 5.5%. The most common trypanosome species identified were Trypanosoma congolense (57.1%). The prevalence of trypanosomes infection was not statistically significant (p>0.05) between Sex and Age groups. However, a statistically significant difference (p<0.05) was observed in the prevalence of trypanosomes with different body-conditioned animals with higher infection rates being recorded in poorly conditioned animals (16.6%). -
The Role of Indigenous Healing Practices in Environmental Protection Among the Maccaa Oromo of Ilu Abbaa Bora and Jimma Zones, Ethiopia
Available online at www.sserr.ro Social Sciences and Education Research Review (4) 1 30-53 (2017) ISSN 2393–1264 ISSN–L 2392–9863 THE ROLE OF INDIGENOUS HEALING PRACTICES IN ENVIRONMENTAL PROTECTION AMONG THE MACCAA OROMO OF ILU ABBAA BORA AND JIMMA ZONES, ETHIOPIA Milkessa Edae TUFA1 , Fesseha Mulu GEBREMARIAM2 1Department of Oromo Folklore and Literature, Jimma University, Ethiopia E-mail: [email protected] 2Department of Governance and Development Studies, Jimma University, Ethiopia E-mails: [email protected] or [email protected] Abstract This article mainly attempted to explore the role of utilizing indigenous medicines in environmental protection among the Maccaa Oromo of Jimma and Iluu Abba bora zone, south-western Ethiopia. To this end, 4 separate interviews with 4 interviewees, 2 focus group discussions with 17 participants, and non- participant field observation were conducted to generate significant and reliable data. Besides, the researchers employed secondary data to make the study more significant and complete. The findings of the study show that since the source of medicines is the environment, the community protects their environment unless the society wouldn’t accessed the natural medicines they need. The study also reveals that most of these folk medicines used by the Maccaa Oromos are from 30 plants. This further indicates the society protects the natural environment to get the plants they use for medication. Thus, folk healing practices are crucial on the one hand to treat illnesses, and to protect the ecosystem on the other hand. However, these societal knowledge is undermined as well as they are being replaced by western (scientific) knowledge, modern medicines. -
1 the Microeconomics of Household Collection of Wild
The Microeconomics of Household Collection of Wild Coffee in Ethiopia: Some Policy Implications for In-situ Conservation of Coffea arabica Genetic Diversity1 Degnet Abebaw2 and Detlef Virchow3 Abstract World-wide cultivated arabica coffee is a native plant to Ethiopian highlands. Its wild populations can still be found in the fragmented montane rainforests of the country. To halt degradation and loss of the forest coffee genetic resources, the Ethiopian Government has established in-situ conservation areas in the south and southwestern montane rain forest regions of the country. However, there are several thousands of people who have been and still are dependent on the wild coffee populations from these forests for direct consumption and/or market sales. Thus, policy makers need to consider the needs and economic options of the local people in the periphery, so as to create a win-win relationship between conservation and local agricultural development. This paper substantiates the interface between the forest coffee genetic resources and the local agriculture by exploring the economic importance to farm families of wild coffee from the Geba-Dogi forest coffee conservation area, Southwest Ethiopia. A random sample of 121 farm families was used in this empirical study. Descripitive results demonstrate the very different resource use behavior of the population and the diversity of the (local) people living in the periphery in terms of socioeconomic interests, skills, culture, demographic history, resource use behavior and wealth. Probit regression indicates that household collection of wild coffee from the protected site is positively and significantly associated with family size, ownership of adjacent farm plot, and male- headship of the household. -
Addis Ababa University, School of Graduate Studies, Environmental Science Program
ADDIS ABABA UNIVERSITY, SCHOOL OF GRADUATE STUDIES, ENVIRONMENTAL SCIENCE PROGRAM THE IMPACT OF RESETTLEMENT ON WOODLAND VEGETATION: THE CASE OF CHEWAKA RESETTLEMENT AREA, SOUTHWESTERN ETHIOPIA BERHANU GENETI MORODA ENVIRONMENTAL SCIENCE PROGRAM MAY 2007 ADDIS ABABA, ETHIOPIA II ADDIS ABABA UNIVERSITY, SCHOOL OF GRADUATE STUDIES, ENVIRONMENTAL SCIENCE PROGRAM THE IMPACT OF RESETTLEMENT ON WOODLAND VEGETATION: THE CASE OF CHEWAKA RESETTLEMENT AREA, SOUTHWESTERN ETHIOPIA BY BERHANU GENETI MORODA file:///C|/Users/3020/Desktop/enviromental%20science/Berhanu%20Geneti%20Moroda.pdf.txt[6/1/2018 9:16:33 AM] THESIS SUBMITTED TO SCHOOL OF GRADUATE STUDIES OF ADDIS ABABA UNIVERSITY, IN PARTIAL FULFILLMENT OF MASTERS DEGREE IN ENVIRONMENTAL SCIENCE MAY 2007 ADDIS ABABA, ETHIOPIA III ADDIS ABABA UNIVERSITY, SCHOOL OF GRADUATE STUDIES, ENVIRONMENTAL SCIENCE PROGRAM THE IMPACT OF RESETTLEMENT ON WOODLAND VEGETATION: THE CASE OF CHEWAKA RESETTLEMENT AREA, SOUTHWESTEN ETHIOPIA BY BERHANU GENETI MORODA SCIENCE FACULTY APPROVED BY EXAMINING BOARD: Signature Dr Tadesse Woldemariam ______________ (Advisor) Dr Mulugeta Lemenih ________________ (Advisor) Dr Mekuria Argaw _________________ (Internal examiner) Dr Feyera Senbeta _________________ (External examiner) I ACKNOWLEDGEMENTS This study would have not been possible with out the contribution of different organizations and individuals. First of all I am grateful to my employer, the Office of Gambella National Park that granted me study leave to continue my study at Addis Ababa University. I am also indebted to Addis Ababa University for offering me the scholarship. The Central Statistics Agency and Federal Meteorological Agency provided relevant information of the area. My advisors Dr Tadesse Woldemariam (Addis Ababa University) and Dr Mulugeta Lemenih (Hawassa University, Wondo Genet College of Forestry and Natural Resources) have been advising and sharing their invaluable time and ideas for which I am highly grateful. -
Nature of Damage and Infestation of Dominant Foliage Herbivore of Soybean at Jimma-Iluababora, Ethiopia
Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol.10, No.7, 2020 Nature of Damage and Infestation of Dominant Foliage Herbivore of Soybean at Jimma-Iluababora, Ethiopia Sisay Kidanu Ethiopian Institute of Agricultural Research, Jimma Research Center, P. O. Box 192, Jimma, Ethiopia Abstract Leaf herbivore insects are among the most serious pests of soybean in Ethiopia. A survey was conducted on 90 farms in three main soybean growing districts in Jimma and Iluababora zones of Ethiopia. The objectives were to assess the socio demographic information of the farmers, to identify farmers’ pest management practices and to study the importance and infestation of dominant leaf herbivore insect pests of soybean. The statistical analysis showed there is highly significant (p<0001) difference among studied districts in area coverage of soybean production and the majority of the farmers (81.1%) produce soybean below a hectare. Farmers were using different pest management methods to reduce damage caused by leaf phaga insect pests which concentrated on cultural method. Crop rotation was one of the main farming systems practiced by 80% at Tiroafeta and 96.7 and 100 % at Chewaka and Darimu districts. About 16.7% farmers of Tiroafeta were not practiced any management practices for pest management where as only 3.3 % of them practiced manually hand picking method at Chewaka. At Darimu district, all surveyed farmers did not get any access to crop protection training, but at Tiroafeta and Chewaka only 3.3 % of them got training opportunity provided by research center. The study revealed that the mean infestation level of green clover worm was 29.8 % at Tiroafeta district and 47 and 50.4 % at Chewaka and Darimu. -
Health Action in Crises Update
Issue 32: June 2004 HEALTH ACTION IN CRISES MONTHLY REPORT ISSUE 32: June 2004 DISCLAIMER: The following is a non-exhaustive selection of health-related events and WHO actions undertaken during the stated period in specific countries in which populations are experiencing crisis conditions. This has been compiled by WHO/Health Action in Crises (HAC/HQ) in Geneva, in consultation with relevant Country and Regional Offices. If you are a WHO staff member and wish to contribute to this update, please write [email protected]. For a list of acronyms, please see the last page of this update. AFRO West Africa Sub-Region Contact: Dr K.E. Siamevi, [email protected] Cameroon Events WHO Interventions A cholera outbreak that began in January WHO met with the MoH, members of the donor community, 2004 has started again with the onset of NGOs and international agencies to decide on a common the rainy season in the Littoral and West strategy to combat the outbreak. WHO contributed drugs and regions. The Ministry of Health (MoH) supplies, case management guidelines, and chlorine. reported 2,924 cases and 46 deaths as of 9 Specific technical support, comprising an epidemiologist and a June. Since then, the number has risen to social mobilization expert, have been provided by the WHO 4,032 cases and 65 deaths. Regional Office for Africa. A water and sanitation engineer The MoH is working with other Ministries provided by the French Government joined this team. to carry out control measures. Physicians WHO/HAC/HQ is providing funds for emergency medicines, have been sent from the capital to Douala, and Médecins sans Frontières has engaged in drilling wells and at the centre of the outbreak, to support chlorinating water supplies. -
Oromiya 4 Zone Code Wereda Code Town Code West
REGION - OROMIYA 4 ZONE CODE WEREDA CODE TOWN CODE WEST WELEGA 01 MENE SIBU 01 MENDI 1 NEJO 02 NEJO 1 WERE JIRU 2 GORI 3 GIMBI 03 HOMA 1 LALO ASABI 04 ENANGO 1 DENIGORO 2 KILTU KARA 05 KILTU KARA 1 BOJI DIRMEJ 06 BILA 2 AYIRA GULISO 07 GULISO 1 AYIRA 2 JARSO 08 GEBA DEFINO 1 KONDALA 09 GEBA DEFNO 1 BOJI CHEKORSA 10 CHEKORSA 1 BABO GAMBEL 11 DEBEKA 1 YUBDO 12 YUBDO 1 GENJI 13 GENJI 1 HARU 14 GUYU 1 NOLE KABA 15 BUBE 1 BEGI 16 BEGI 1 KOBER 2 GIMBI /TOWN/ 17 GIMBE 1 SEYO NOLE 18 DEBESO 1 EAST WELEGA 02 LIMU 01 GELILA 1 IBANTU 02 HINDE 1 GIDA KIREMU 03 GIDA AYANA 1 KIREMU 2 GUTEN 3 HORO LIMU 04 BONIYA BUSHE 05 BILO 1 WAYU TUKA 06 GEBA JIMATA 1 GUDEYA BILA 07 JERE 1 BILA 2 GOBU SEYO 08 ANO 1 OROMIYA (Cont'd) ZONE CODE WEREDA CODE TOWN CODE EAST WELEGA 02 SIBU SIRE 09 SIRE 1 DIGA 10 ARJO GUDETU 1 IFA 2 SASIGA 11 GALO 1 LEKA DULECHA 12 GETEMA 1 GUTO GIDA 13 DIGA 1 JIMA ARJO 14 ARJO 1 NUNU KUMBA 15 NUNU 1 WAMA HAGELO 16 NEKEMTE /TOWN/ 17 NEKEMTE 1 ILU ABA BORA 03 DARIMU 01 DUPA 1 ALGE SACHI 02 ALGE 1 SUPE 2 CHORA 03 KUMBABE 1 DEGA 04 DEGA 1 DABO HANA 05 KONE 1 GECHI 06 GECHI 1 BORECHA 07 YANFU 1 DEDESA 08 DENBI 1 YAYU 09 YAYU 1 METU ZURIYA 10 ALE 11 GORE 1 BURE 12 BURE 01 1 SIBU 2 NONO SELE 13 BIRBIRSA 1 OROMIYA (Cont'd) ZONE CODE WEREDA CODE TOWN CODE ILU ABA BORA 03 BICHO 14 BICHO 1 BILO NOPHA 15 NOPA 1 HURUMU 16 HURUMU 1 DIDU 17 LALO 1 MAKO 18 MAKO 1 HUKA /HALU/ 19 HUKA 01 1 METU TOWN 20 METU 1 BEDELE TOWN 21 BEDELE 1 BEDELE ZURIYA 22 - 1 CHEWAKA 23 ILU HARERE 1 DORENI 24 JIMA 04 LIMU SEKA 01 ANTAGO 1 LIMU KOSA 02 LIMU GENET 1 AMBUYE 2 BABU -
Ethiopia Census 2007
Table 1 : POPULATION SIZE OF REGIONS BY SEX AND PLACE OF RESIDENCE: 2007 Urban + Rural Urban Rural Sex No. % No. % No. % COUNTRY TOTAL * Both Sexes 73,918,505 100.00 11,956,170 100.00 61,962,335 100.00 Male 37,296,657 50.46 5,942,170 49.70 31,354,487 50.60 Female 36,621,848 49.54 6,014,000 50.30 30,607,848 49.40 TIGRAY Region Both Sexes 4,314,456 100.00 842,723 100.00 3,471,733 100.00 Male 2,124,853 49.25 398,072 47.24 1,726,781 49.74 Female 2,189,603 50.75 444,651 52.76 1,744,952 50.26 AFFAR Region * Both Sexes 1,411,092 100.00 188,973 100.00 1,222,119 100.00 Male 786,338 55.73 100,915 53.40 685,423 56.08 Female 624,754 44.27 88,058 46.60 536,696 43.92 AMHARA Region Both Sexes 17,214,056 100.00 2,112,220 100.00 15,101,836 100.00 Male 8,636,875 50.17 1,024,136 48.49 7,612,739 50.41 Female 8,577,181 49.83 1,088,084 51.51 7,489,097 49.59 ORORMIYA Region Both Sexes 27,158,471 100.00 3,370,040 100.00 23,788,431 100.00 Male 13,676,159 50.36 1,705,316 50.60 11,970,843 50.32 Female 13,482,312 49.64 1,664,724 49.40 11,817,588 49.68 SOMALI Region * Both Sexes 4,439,147 100.00 621,210 100.00 3,817,937 100.00 Male 2,468,784 55.61 339,343 54.63 2,129,441 55.77 Female 1,970,363 44.39 281,867 45.37 1,688,496 44.23 BENISHANGUL-GUMUZ Region Both Sexes 670,847 100.00 97,965 100.00 572,882 100.00 Male 340,378 50.74 49,784 50.82 290,594 50.72 Female 330,469 49.26 48,181 49.18 282,288 49.28 SNNP Region Both Sexes 15,042,531 100.00 1,545,710 100.00 13,496,821 100.00 Male 7,482,051 49.74 797,796 51.61 6,684,255 49.52 Female 7,560,480 50.26 747,914 48.39 6,812,566 -
Project Implementation Manual Final Draft
THE NATIONAL REGIONAL GOVERNMENT OF OROMIA OROMIA ENVIRONMENT, FOREST AND CLIMATE CHNAGE AUTHORITY Oromia National Regional State Forested Landscape Program (Project ID P156475) Project Implementation Manual Final Draft (2017-2022) Addis Ababa, Ethiopia April 25, 2017 i Abbreviations and Acronyms A/R Afforestation/Reforestation AD Activity Data AF Additional Finance AGP Agricultural Growth Program AWP&B Annual Work Plan and Budget BioCF BioCarbon Fund BMERP Bale Mountains Eco-region REDD+ Project BoANR Bureau of Agriculture and Natural Resource BoFEC Bureaus of Finance and Economic Cooperation BoLFD Bureau of Livetsock and Fishery Development BoRLAU Bureau of Rural Land Adminsitration and Use BoWME Bureau of Water, Minerals and Energy BSM Benefit Sharing Mechanism CBO Community Based Organization CPO Cooperative Promotion Office CQS Selection Based Consultants’ Qualifications CRGE Climate Resilient Green Economy DA Development Agent EIO Ethiopian Institute of Ombudsman EMA Ethiopian Mapping Agency ER Emissions Reductions ERPA Emissions Reductions Purchase Agreement ESMF Environmental and Social Management Framework FA Force Account FAO Food and Agriculture Organization of the United Nations FREL Forest Reference Emission Level FRL Forest Reference Level GHG Greenhouse GIS Geographic Information System GoE Government of Ethiopia GRM Grievance Redress Mechanism ii GTP Growth and Transformation Plan IBRD International Bank of Reconstruction and Development ICB International Competitive Bidding ICS Improved Cook Stoves IDA International Development -
Challenges and Opportunities of Soybean Marketing in Chewaka District, Ethiopia
Asian Journal of Economics, Business and Accounting 17(1): 13-22, 2020; Article no.AJEBA.56572 ISSN: 2456-639X Challenges and Opportunities of Soybean Marketing in Chewaka District, Ethiopia Kumilachew Achamyelh1 and Mesfin Hailemariam2* 1Ethiopian Institute of Agricultural Research, Jimma Agricultural Research Center, Department of Agricultural Economics Division, P.O. Box 192, Jimma, Ethiopia. 2Ethiopian Institute of Agricultural Research, Jimma Agricultural Research Center, Department of Field Crop Division, Pulse Breeding Division, P.O. Box, 192 Jimma, Ethiopia. Authors’ contributions This work was carried out in collaboration between both authors. Author KA developed the outline and carried out the major parts of the literature performed the experiments. Author MH had a literature revised and add key section of results and discussion parts. Both authors read and approved the final manuscript. Article Information DOI: 10.9734/AJEBA/2020/v17i130250 Editor(s): (1) Chun-Chien Kuo, National Taipei University of Business, Taiwan. Reviewers: (1) Hasnizam Shaari, Universiti Utara Malaysia, Malaysia. (2) Md. Hayder Khan Sujan, Sher-e-Bangla Agricultural University, Bangladesh. (3) S. Mohammad Shameer, Potti Sreeramulu Telugu University, India. Complete Peer review History: http://www.sdiarticle4.com/review-history/56572 Received 18 April 2020 Accepted 24 June 2020 Method Article Published 20 August 2020 ABSTRACT The pricing system for soybean is complex because it involves interactions between the markets for soybean grain, soybean meal and soybean oil. The study was undertaken with the objective of identifying and describing the constraints, challenges and opportunities of soybean production and productivity and its impact on the livelihoods of smallholder producer farmers in the area. A multi- stage random sampling techniques were employed to select a total of 153 farmers from four Kebeles. -
National Wash Program Selected Woredas and Small Towns
National WaSH Program Selected Woredas and Small Towns 1. Oromiya Region No Oromiya Woredas No Oromiya Woredas 41 Dugda 83 Ana Sora No Oromiya Woredas 42 Liban Chukala 84 Seba Boru 1 Digalu Tijo 43 Lume 85 Uraga 2 Gololcha 44 Bora 86 Odo Shakkiso 3 Jeju 45 Gudeya Bila 87 Liban 4 Limu Bilbilo 46 Guto Gida 88 Fentale 5 Tiyo 47 Sasiga 89 Babile 6 Zuway Dugda 48 Sibu Sire 90 Chinaksen 7 Adaba 49 Wayu Tuka 91 Qumbi 8 Gedeb Asasa 50 Seyo Nole 92 Guba Korcha 9 Agarfa 51 Nedjo 93 Chiro 10 Dawe Serer 52 Haru 94 Chewaka 11 Dinsho 53 Dale Sedi 95 Hurum 12 Gindhir 54 Dale Wabera 96 Darimu 13 Goro 55 Gawo Kebe 97 Dedo 14 Rayitu 56 Lalo Kile 98 Sokoru 15 Sinana 57 Seyo 99 Seka Chokorsa 16 Bedeno 58 Yubdo 100 Limu Seka 17 Gorogutu 59 Ayira 101 Ilu 18 Girawa 60 Guliso 102 Sodo Dachi 19 Kurfa Chale 61 Sude 103 Weliso 20 Kombolcha 62 Doddota 104 Ameya 21 Haromaya 63 Inkolo Wabe 105 Seden Soddo 22 Kersa 64 Robe 106 Nonno 23 Fedis 65 Lege Hidha 107 Dera 24 Boke 66 Sewena 108 Girar Jarso 25 Darulabu 67 G/Dhamole 109 Yaya Gulele 26 Doba 68 Siraro 110 Kuyu 27 Oda Bultum 69 Arsi Negele 111 Wuchale 28 Tulo 70 Kofele 112 Sululta 29 Hawi Gudina 71 Shashemene 113 Mulo 30 Burqa Dimtu 72 Kokosa 114 Sebeta Hawas 31 Becho 73 Akaki 115 Wolmera 32 Bedele 74 Teltale 116 Berek 33 Bilo Nopha 75 Dhas 117 Dendi 34 Didu 76 Yabello 118 Meta Robi 35 Metu 77 Arero 119 Abuna Ginde Beret 36 Yayu 78 Bule Hora 120 Ambo 37 Dorani 79 Gelana 121 Ilu Gelan 38 Adea 80 Moyale 122 Jibat 39 Adama 81 Hambela Wamana 123 Mida Kegn 40 AT/Jido Kombolcha 82 Kercha 124 Toke Kutaye National WaSH