Scaling up Impacts from the Grassroots in Kenya, Malawi, Mozambique and Senegal
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Inequality of Child Mortality Among Ethnic Groups in Sub-Saharan Africa M
Special Theme ±Inequalities in Health Inequality of child mortality among ethnic groups in sub-Saharan Africa M. Brockerhoff1 & P. Hewett2 Accounts by journalists of wars in several countries of sub-Saharan Africa in the 1990s have raised concern that ethnic cleavages and overlapping religious and racial affiliations may widen the inequalities in health and survival among ethnic groups throughout the region, particularly among children. Paradoxically, there has been no systematic examination of ethnic inequality in child survival chances across countries in the region. This paper uses survey data collected in the 1990s in 11 countries (Central African Republic, Coà te d'Ivoire, Ghana, Kenya, Mali, Namibia, Niger, Rwanda, Senegal, Uganda, and Zambia) to examine whether ethnic inequality in child mortality has been present and spreading in sub-Saharan Africa since the 1980s. The focus was on one or two groups in each country which may have experienced distinct child health and survival chances, compared to the rest of the national population, as a result of their geographical location. The factors examined to explain potential child survival inequalities among ethnic groups included residence in the largest city, household economic conditions, educational attainment and nutritional status of the mothers, use of modern maternal and child health services including immunization, and patterns of fertility and migration. The results show remarkable consistency. In all 11 countries there were significant differentials between ethnic groups in the odds of dying during infancy or before the age of 5 years. Multivariate analysis shows that ethnic child mortality differences are closely linked with economic inequality in many countries, and perhaps with differential use of child health services in countries of the Sahel region. -
East and Central Africa 19
Most countries have based their long-term planning (‘vision’) documents on harnessing science, technology and innovation to development. Kevin Urama, Mammo Muchie and Remy Twingiyimana A schoolboy studies at home using a book illuminated by a single electric LED lightbulb in July 2015. Customers pay for the solar panel that powers their LED lighting through regular instalments to M-Kopa, a Nairobi-based provider of solar-lighting systems. Payment is made using a mobile-phone money-transfer service. Photo: © Waldo Swiegers/Bloomberg via Getty Images 498 East and Central Africa 19 . East and Central Africa Burundi, Cameroon, Central African Republic, Chad, Comoros, Congo (Republic of), Djibouti, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Kenya, Rwanda, Somalia, South Sudan, Uganda Kevin Urama, Mammo Muchie and Remy Twiringiyimana Chapter 19 INTRODUCTION which invest in these technologies to take a growing share of the global oil market. This highlights the need for oil-producing Mixed economic fortunes African countries to invest in science and technology (S&T) to Most of the 16 East and Central African countries covered maintain their own competitiveness in the global market. in the present chapter are classified by the World Bank as being low-income economies. The exceptions are Half the region is ‘fragile and conflict-affected’ Cameroon, the Republic of Congo, Djibouti and the newest Other development challenges for the region include civil strife, member, South Sudan, which joined its three neighbours religious militancy and the persistence of killer diseases such in the lower middle-income category after being promoted as malaria and HIV, which sorely tax national health systems from low-income status in 2014. -
Assessing the Quality of Care in Family Planning, Antenatal, and Sick Child Services at Health Facilities in Kenya, Namibia, and Senegal
ASSESSING THE QUALITY OF CARE IN FaMILY PLANNING, ANTENATAL, AND SICK CHILD SERVICES AT HEALTH FACILITIES IN KENYA, NAMIBIA, AND SENEGAL DHS ANALYTICAL STUDIES 44 SEPTEMBER 2014 This publication was produced for review by the United States Agency for International Development. It was prepared by Wenjuan Wang, Mai Do, John Hembling, and Paul Ametepi. DHS Analytical Studies No. 44 Assessing the Quality of Care in Family Planning, Antenatal, and Sick Child Services at Health Facilities in Kenya, Namibia, and Senegal Wenjuan Wang Mai Do John Hembling Paul Ametepi ICF International Rockville, Maryland, USA September 2014 Corresponding author: Wenjuan Wang, International Health and Development, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; telephone: +1 301-572-0398: fax: +1 301-572-0950; email: [email protected] Acknowledgment: The authors would like to thank Sohail Agha for reviewing this report and providing invaluable comments. Editor: Bryant Robey Document Production: Natalie La Roche This study was carried out with support provided by the United States Agency for International Development (USAID) through The DHS Program (#AID-OAA-C-13-00095). The views expressed are those of the author and do not necessarily reflect the views of USAID or the United States Government. The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate population, health, and nutrition programs. For additional information about the DHS Program contact: DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA; phone: 301-407-6500, fax: 301-407-6501, email: [email protected], Internet: www.dhsprogram.com. -
Mozambique-And-Malawi-Regional
FOR OFFICIAL USE ONLY Report No: PAD3035 Public Disclosure Authorized INTERNATIONAL DEVELOPMENT ASSOCIATION PROJECT APPRAISAL DOCUMENT ON A PROPOSED IDA GRANT IN THE AMOUNT OF SDR 30.6 MILLION (US$42.0 MILLION EQUIVALENT) AND A PROPOSED GRANT Public Disclosure Authorized IN THE AMOUNT OF US$24.0 MILLION EQUIVALENT FROM THE NORWAY’S SUPPORT TO THE REGIONAL POWER INFRASTRUCTURE PROJECTS IN SOUTHERN AFRICA SINGLE DONOR TRUST FUND TO THE REPUBLIC OF MOZAMBIQUE AND A PROPOSED IDA CREDIT IN THE AMOUNT OF SDR 11.0 MILLION (US$15.0 MILLION EQUIVALENT) Public Disclosure Authorized TO THE REPUBLIC OF MALAWI FOR THE MOZAMBIQUE - MALAWI REGIONAL INTERCONNECTOR PROJECT August 26, 2019 Energy and Extractives Global Practice Africa Region Public Disclosure Authorized This document has a restricted distribution and may be used by recipients only in the performance of their official duties. Its contents may not otherwise be disclosed without World Bank authorization. CURRENCY EQUIVALENTS (Exchange Rate Effective {July 31, 2019}) New Mozambican Metical (MZN) and Currency Unit = Malawian Kwacha (MWK) US$1 = MZN 61.3499 US$1 MWK 744.9788 US$1 = SDR 0.72705065 FISCAL YEAR Government of the Republic of Mozambique: January 1 - December 31 Government of the Republic of Malawi: July 1 – June 30 Regional Vice President: Hafez M. H. Ghanem Regional Integration Director: Deborah L. Wetzel Country Directors: Mark R. Lundell, Bella Bird Senior Global Practice Director: Riccardo Puliti Practice Manager: Sudeshna Ghosh Banerjee Task Team Leaders: Dhruva Sahai, Zayra -
African Dialects
African Dialects • Adangme (Ghana ) • Afrikaans (Southern Africa ) • Akan: Asante (Ashanti) dialect (Ghana ) • Akan: Fante dialect (Ghana ) • Akan: Twi (Akwapem) dialect (Ghana ) • Amharic (Amarigna; Amarinya) (Ethiopia ) • Awing (Cameroon ) • Bakuba (Busoong, Kuba, Bushong) (Congo ) • Bambara (Mali; Senegal; Burkina ) • Bamoun (Cameroons ) • Bargu (Bariba) (Benin; Nigeria; Togo ) • Bassa (Gbasa) (Liberia ) • ici-Bemba (Wemba) (Congo; Zambia ) • Berba (Benin ) • Bihari: Mauritian Bhojpuri dialect - Latin Script (Mauritius ) • Bobo (Bwamou) (Burkina ) • Bulu (Boulou) (Cameroons ) • Chirpon-Lete-Anum (Cherepong; Guan) (Ghana ) • Ciokwe (Chokwe) (Angola; Congo ) • Creole, Indian Ocean: Mauritian dialect (Mauritius ) • Creole, Indian Ocean: Seychelles dialect (Kreol) (Seychelles ) • Dagbani (Dagbane; Dagomba) (Ghana; Togo ) • Diola (Jola) (Upper West Africa ) • Diola (Jola): Fogny (Jóola Fóoñi) dialect (The Gambia; Guinea; Senegal ) • Duala (Douala) (Cameroons ) • Dyula (Jula) (Burkina ) • Efik (Nigeria ) • Ekoi: Ejagham dialect (Cameroons; Nigeria ) • Ewe (Benin; Ghana; Togo ) • Ewe: Ge (Mina) dialect (Benin; Togo ) • Ewe: Watyi (Ouatchi, Waci) dialect (Benin; Togo ) • Ewondo (Cameroons ) • Fang (Equitorial Guinea ) • Fõ (Fon; Dahoméen) (Benin ) • Frafra (Ghana ) • Ful (Fula; Fulani; Fulfulde; Peul; Toucouleur) (West Africa ) • Ful: Torado dialect (Senegal ) • Gã: Accra dialect (Ghana; Togo ) • Gambai (Ngambai; Ngambaye) (Chad ) • olu-Ganda (Luganda) (Uganda ) • Gbaya (Baya) (Central African Republic; Cameroons; Congo ) • Gben (Ben) (Togo -
2020 09 30 USG Southern Africa Fact Sheet #3
Fact Sheet #3 Fiscal Year (FY) 2020 Southern Africa – Regional Disasters SEPTEMBER 30, 2020 SITUATION AT A GLANCE 10.5 765,000 5.4 1.7 320,000 MILLION MILLION MILLION Estimated Food- Estimated Confirmed Estimated Food-Insecure Estimated Severely Estimated Number Insecure Population in COVID-19 Cases in Population in Rural Food-Insecure of IDPs in Southern Africa Southern Africa Zimbabwe Population in Malawi Cabo Delgado IPC – Sept. 2020 WHO – Sept. 30, 2020 ZimVAC – Sept. 2020 IPC – Sept. 2020 WFP – Sept. 2020 Increasing prevalence of droughts, flooding, and other climatic shocks has decreased food production in Southern Africa, extending the agricultural lean season and exacerbating existing humanitarian needs. The COVID-19 pandemic and related containment measures have worsened food insecurity and disrupted livelihoods for urban and rural households. USG partners delivered life-saving food, health, nutrition, protection, shelter, and WASH assistance to vulnerable populations in eight Southern African countries during FY 2020. TOTAL U.S. GOVERNMENT HUMANITARIAN FUNDING USAID/BHA1,2 $202,836,889 For the Southern Africa Response in FY 2020 State/PRM3 $19,681,453 For complete funding breakdown with partners, see detailed chart on page 6 Total $222,518,3424 1USAID’s Bureau for Humanitarian Assistance (USAID/BHA) 2 Total USAID/BHA funding includes non-food humanitarian assistance from the former Office of U.S. Foreign Disaster Assistance (USAID/OFDA) and emergency food assistance from the former Office of Food for Peace (USAID/FFP). 3 U.S. Department of State’s Bureau of Population, Refugees, and Migration (State/PRM) 4 This total includes approximately $30,914,447 in supplemental funding through USAID/BHA and State/PRM for COVID-19 preparedness and response activities. -
MALAWI Sub-Saharan Africa
Country Profile MALAWI Abc Region: Sub-Saharan Africa 2020 EPI Country Rank (out of 180) GDP [PPP 2011$ billions] 21.1 112 GDP per capita [$] 1,163 2020 EPI Score [0=worst, 100=best] Population [millions] 18.1 38.3 Urbanization [%] 17.43 Country Scorecard Issue Categories Rank [/180] Environmental Health 134 26.5 Air Quality 87 39.6 Sanitation & Drinking Water 163 12.0 Heavy Metals 130 37.4 Waste Management 133 0.0 Ecosystem Vitality 83 46.2 Biodiversity & Habitat 23 84.2 Ecosystem Services 147 22.8 Fisheries 0 0.0 Climate Change 144 34.2 Pollution Emissions 104 53.1 Agriculture 87 39.0 Water Resources 134 0.0 Regional Average World Average epi.yale.edu Page 1 of 3 Country Profile MALAWI Abc Region: Sub-Saharan Africa 10-Year Regional Regional Rank EPI Score Change Rank Average Environmental Performance Index 112 38.3 -2.6 7 33.2 Environmental Health 134 26.5 +2.8 11 22.7 Air Quality 87 39.6 +1.2 4 28.0 Household solid fuels 162 9.3 +2.8 34 16.1 PM 2.5 exposure 33 61.2 +0.7 2 35.9 Ozone exposure 84 43.5 -7.0 10 36.4 Sanitation & Drinking Water 163 12 +4.6 29 15.9 Unsafe sanitation 163 12 +4.6 29 16.7 Unsafe drinking water 162 12 +4.6 28 15.4 Heavy Metals / Lead exposure 130 37.4 +5.6 26 41.4 Waste Management / Controlled solid waste 133 0 –- 21 5.7 Ecosystem Vitality 83 46.2 -6.2 10 40.2 Biodiversity & Habitat 23 84.2 –- 6 58.6 Terrestrial biomes (nat'l) 1 100 –- 1 69.0 Terrestrial biomes (global) 1 100 –- 1 71.3 Marine protected areas 0 0 –- 37 14.5 Protected Areas Representativeness Index 54 41.1 +4.4 9 30.4 Species Habitat Index 37 92.8 -
Lessons Learned from Power-Sharing in Africa
8/2008 Lessons Learned from Power-Sharing in Africa Håvard Strand, Centre for the Study of Civil War (CSCW) Scott Gates, Centre for the Study of Civil War (CSCW) Several power-sharing agreements have been reached in Africa over the last decades. This project has compared the experiences of various forms of power-sharing in five countries, Bu- rundi, Kenya, Liberia, Nigeria, and Sierra Leone. The cases differ significantly both with regard to the implementation of power-sharing and the rationale for adopting such institutions. Our conclusions is that power-sharing institutions have proven themselves useful in some countries and less so in others. The most positive experiences have been in the peace processes of Sierra Leone and Liberia, where power-sharing played a vital role in securing peace. There are less clear support for power-sharing institutions with regard to good governance. Introduction tions. Inclusive institutions work towards inte- This project describes power-sharing efforts in grating as many voices as possible into the deci- five conflict-prone and ill-governed African sion-making body, whereas exclusive institutions countries: Burundi, Kenya, Liberia, Nigeria, and create autonomous political spheres. Sierra Leone. While these five countries are The rationale for inclusive institutions as- unique in many important ways, some overar- sumes that exclusion is a key to violent conflict, ching conclusions can nevertheless be drawn and is therefore very focused on not excluding from these studies. Our studies support the any relevant group. The inclusive answer is to conclusion that power-sharing can be a useful provide some guarantees to all parties, so that remedy under certain conditions. -
The Populat Kenya
£ 4 World Population Year THE POPULAT KENYA - UGANDA - TANZANIA CI.CR.E.D. Senes THE POPULATION OF KENYA- UGANDA - TANZANIA SIMEON OMINDE Professor of Geography and Head of Department, University of Nairobi 1974 World Population Year C.I.C.R.E.D Series This study was initiated and financed by C.I.C.R.E.D. (Committee for International Coordination of National Research in Demography) to coincide with 1974 World Population Year. © Simeon Ominde © C.I.C.R.E.D. First published 1975 Printed in Kenya by Kenya Litho Ltd., P.O. Box 40775, Changamwe Road, Nairobi. CONTENTS Page PREFACE ¡v Chapter 1 The Area and Estimates of Population Growth 1 Chapter 2 Components of Population Growth 11 Chapter 3 Migration 40 Chapter 4 Population Composition 59 Chapter 5 Population Distribution 73 Chapter 6 Urbanization 88 Chapter 7 Labour Force 97 Chapter 8 Population Projection 105 Chapter 9 Population Growth and Socio-Economic Development 115 Conclusion 123 PREFACE This monograph presents the population situation in the area covered by Tanzania, Uganda and Kenya. The material has been prepared at the request of CICRED, as part of its contribution to the objectives of the World Population Year, 1974. In common with other developing countries of Africa, the East African countries are becoming acutely aware of the importance of rapid population growth and its significance to the attainment of development objectives. It has become increasingly clear that with the current rates of growth and the limited resources, the burden of socio-economic development programmes has become more serious. The search for alternative strategies to development must therefore focus attention on the impact of accelerating growth rate which leads to retardation of the rate of economic and social development. -
History, External Influence and Political Volatility in the Central African Republic (CAR)
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Journal for the Advancement of Developing Economies Economics Department 2014 History, External Influence and oliticalP Volatility in the Central African Republic (CAR) Henry Kam Kah University of Buea, Cameroon Follow this and additional works at: https://digitalcommons.unl.edu/jade Part of the Econometrics Commons, Growth and Development Commons, International Economics Commons, Political Economy Commons, Public Economics Commons, and the Regional Economics Commons Kam Kah, Henry, "History, External Influence and oliticalP Volatility in the Central African Republic (CAR)" (2014). Journal for the Advancement of Developing Economies. 5. https://digitalcommons.unl.edu/jade/5 This Article is brought to you for free and open access by the Economics Department at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Journal for the Advancement of Developing Economies by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Journal for the Advancement of Developing Economies 2014 Volume 3 Issue 1 ISSN:2161-8216 History, External Influence and Political Volatility in the Central African Republic (CAR) Henry Kam Kah University of Buea, Cameroon ABSTRACT This paper examines the complex involvement of neighbors and other states in the leadership or political crisis in the CAR through a content analysis. It further discusses the repercussions of this on the unity and leadership of the country. The CAR has, for a long time, been embroiled in a crisis that has impeded the unity of the country. It is a failed state in Africa to say the least, and the involvement of neighboring and other states in the crisis in one way or the other has compounded the multifarious problems of this country. -
The Charcoal Grey Market in Kenya, Uganda and South Sudan (2021)
COMMODITY REPORT BLACK GOLD The charcoal grey market in Kenya, Uganda and South Sudan SIMONE HAYSOM I MICHAEL McLAGGAN JULIUS KAKA I LUCY MODI I KEN OPALA MARCH 2021 BLACK GOLD The charcoal grey market in Kenya, Uganda and South Sudan ww Simone Haysom I Michael McLaggan Julius Kaka I Lucy Modi I Ken Opala March 2021 ACKNOWLEDGEMENTS The authors would like to thank everyone who gave their time to be interviewed for this study. They would like to extend particular thanks to Dr Catherine Nabukalu, at the University of Pennsylvania, and Bryan Adkins, at UNEP, for playing an invaluable role in correcting our misperceptions and deepening our analysis. We would also like to thank Nhial Tiitmamer, at the Sudd Institute, for providing us with additional interviews and information from South Sudan at short notice. Finally, we thank Alex Goodwin for excel- lent editing. Interviews were conducted in South Sudan, Uganda and Kenya between February 2020 and November 2020. ABOUT THE AUTHORS Simone Haysom is a senior analyst at the Global Initiative Against Transnational Organized Crime (GI-TOC), with expertise in urban development, corruption and organized crime, and over a decade of experience conducting qualitative fieldwork in challenging environments. She is currently an associate of the Oceanic Humanities for the Global South research project based at the University of the Witwatersrand in Johannesburg. Ken Opala is the GI-TOC analyst for Kenya. He previously worked at Nation Media Group as deputy investigative editor and as editor-in-chief at the Nairobi Law Monthly. He has won several journalistic awards in his career. -
Country Codes ISO 3166
COUNTRY CODES - ISO 3166-1 ISO 3166-1 encoding list of the countries which are assigned official codes It is listed in alphabetical order by the country's English short name used by the ISO 3166/MA. Numeric English short name Alpha-2 code Alpha-3 code code Afghanistan AF AFG 4 Åland Islands AX ALA 248 Albania AL ALB 8 Algeria DZ DZA 12 American Samoa AS ASM 16 Andorra AD AND 20 Angola AO AGO 24 Anguilla AI AIA 660 Antarctica AQ ATA 10 Antigua and Barbuda AG ATG 28 Argentina AR ARG 32 Armenia AM ARM 51 Aruba AW ABW 533 Australia AU AUS 36 Austria AT AUT 40 Azerbaijan AZ AZE 31 Bahamas BS BHS 44 Bahrain BH BHR 48 Bangladesh BD BGD 50 Barbados BB BRB 52 Belarus BY BLR 112 Belgium BE BEL 56 Belize BZ BLZ 84 Benin BJ BEN 204 Bermuda BM BMU 60 Bhutan BT BTN 64 Bolivia (Plurinational State of) BO BOL 68 Bonaire, Sint Eustatius and Saba BQ BES 535 Bosnia and Herzegovina BA BIH 70 Botswana BW BWA 72 Bouvet Island BV BVT 74 Brazil BR BRA 76 British Indian Ocean Territory IO IOT 86 Brunei Darussalam BN BRN 96 Bulgaria BG BGR 100 Burkina Faso BF BFA 854 Burundi BI BDI 108 Cabo Verde CV CPV 132 Cambodia KH KHM 116 Cameroon CM CMR 120 Canada CA CAN 124 1500 Don Mills Road, Suite 800 Toronto, Ontario M3B 3K4 Telephone: 416 510 8039 Toll Free: 1 800 567 7084 www.gs1ca.org Numeric English short name Alpha-2 code Alpha-3 code code Cayman Islands KY CYM 136 Central African Republic CF CAF 140 Chad TD TCD 148 Chile CL CHL 152 China CN CHN 156 Christmas Island CX CXR 162 Cocos (Keeling) Islands CC CCK 166 Colombia CO COL 170 Comoros KM COM 174 Congo CG COG