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Mozambique Zambia South Africa Zimbabwe Tanzania

UNITED NATIONS MOZAMBIQUE Geospatial 30°E 35°E 40°E L a k UNITED REPUBLIC OF 10°S e 10°S Chinsali M a l a w TANZANIA Palma i Mocimboa da Praia R ovuma Mueda ^! Lua Mecula pu la ZAMBIA L a Quissanga k e NIASSA N Metangula y CABO DELGADO a Chiconono DEM. REP. OF s a Ancuabe Pemba THE CONGO Lichinga Montepuez Marrupa Chipata MALAWI Maúa Lilongwe Namuno Namapa a ^! gw n Mandimba Memba a io u Vila úr L L Mecubúri Nacala Kabwe Gamito Cuamba Vila Ribáué MecontaMonapo Mossuril Fingoè FurancungoCoutinho ^! Nampula 15°S Vila ^! 15°S Lago de NAMPULA TETE Junqueiro ^! Lusaka ZumboCahora Bassa Murrupula Mogincual K Nametil o afu ezi Namarrói Erego e b Mágoè Tete GiléL am i Z Moatize Milange g Angoche Lugela o Z n l a h m a bez e i ZAMBEZIA Vila n azoe Changara da Moma n M a Lake Chemba Morrumbala Maganja Bindura Guro h Kariba Pebane C Namacurra e Chinhoyi Harare Vila Quelimane u ^! Fontes iq Marondera Mopeia Marromeu b am Inhaminga Velha oz P M úngu Chinde Be ni n è SOFALA t of ManicaChimoio o o o o o o o o o o o o o o o gh ZIMBABWE o Bi Mutare Sussundenga Dondo Gweru Masvingo Beira I NDI A N Bulawayo Chibabava 20°S 20°S Espungabera Nova OCE A N Mambone Gwanda MANICA e Sav Inhassôro Vilanculos Chicualacuala Mabote Mapai INHAMBANE Lim Massinga p o p GAZA o Morrumbene Homoíne Massingir Panda ^! National capital SOUTH Inhambane Administrative capital Polokwane Guijá Inharrime Town, village o Chibuto Major airport Magude MaciaManjacazeQuissico International boundary AFRICA Administrative boundary MAPUTO Xai-Xai 25°S Nelspruit Main road 25°S Moamba Manhiça Railway Pretoria MatolaMaputo ^! ^! 0 100 200km Mbabane^!Namaacha Boane 0 50 100mi !\ Bela Johannesburg Lobamba Vista ESWATINI Map No. 3706 Rev. 7 The boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations. Jul 2020 30°E 35°E 40°E.

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2.4 Mozambique Railway Assessment Railways Overview
2.4 Mozambique Railway Assessment Railways Overview Page 1 Page 2 The Mozambique Ports and Railways Administration (CFM) was created in 1931. The railway system was developed in order to be connected with the three main ports of Maputo, Beira and Nacala, mainly to provide a fast, safe and efficient transit transportation service for mineral and agriculture exports from South Africa, Zimbabwe and Malawi, and for some national traffic from landlocked provinces. The main railway network is about 2,500 km long, distributed in three systems in the South, Central and North, each with 1,067 mm (3’6”) gauge (cape gauge) that is compatible with neighbouring railways networks. The railway system was designed mainly for goods transportation, i.e. there are little passenger rail services in the country. On the other hand, there is no direct rail connection between the three systems inside Mozambique territory; connections are however available via neighbouring countries. The railways were severely targeted by acts of war after the independence of Mozambique in 1975, first by Rhodesian forces prior to Zimbabwe’s independence in 1980, and then during the civil war in Mozambique which lasted until the nineties. These acts of war inflicted major damages on railway lines and bridges, and on locomotives and wagons that consequently disrupted traffic. Recent extensive infrastructure rehabilitation and locomotive and rolling stock renewal programmes undertaken across all three networks, combined with some strategic management concessions, have brought railways back to adequate operational conditions and to be reliable transportation services. Plans exist to augment the capacity of the current railway system and to build new lines to serve the growing mineral market, which mainly consists of coal from the Tete province.
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THE RISE, CONSOLIDATION AND DISINTEGRATION OF DLAMINI POWER IN SWAZILAND BETWEEN 1820 AND 1889. A study in the relationship of foreign affairs to internal political development. Philip Lewis Bonner. ProQuest Number: 11010329 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a com plete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. uest ProQuest 11010329 Published by ProQuest LLC(2018). Copyright of the Dissertation is held by the Author. All rights reserved. This work is protected against unauthorized copying under Title 17, United States C ode Microform Edition © ProQuest LLC. ProQuest LLC. 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106- 1346 ABSTRACT The Swazi kingdom grew out of the pressures associated with competition for trade and for the rich resources of Shiselweni. While centred on this area it acquired some of its characteristic features - notably a regimental system, and the dominance of a Dlamini aristocracy. Around 1815 the Swazi came under pressure from the South, and were forced to colonise the land lying north of the Lusutfu. Here they remained for some years a nation under arms, as they plundered local peoples, and were themselves swept about by the currents of the Mfecane. In time a more settled administration emerged, as the aristocracy spread out from the royal centres at Ezulwini, and this process accelerated under Mswati as he subdued recalcitrant chiefdoms, and restructured the regiments.
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Analisys of Incentives and Disincentives for Cotton In
ANALYSIS OF INCENTIVES AND DISINCENTIVES FOR COTTON IN MOZAMBIQUE OCTOBER 2012 This technical note is a product of the Monitoring African Food and Agricultural Policies project (MAFAP). It is a technical document intended primarily for internal use as background for the eventual MAFAP Country Report. This technical note may be updated as new data becomes available. MAFAP is implemented by the Food and Agriculture Organization of the United Nations (FAO) in collaboration with the Organisation for Economic Co-operation and Development (OECD) and national partners in participating countries. It is financially supported by the Bill and Melinda Gates Foundation, the United States Agency for International Development (USAID), and FAO. The analysis presented in this document is the result of the partnerships established in the context of the MAFAP project with governments of participating countries and a variety of national institutions. For more information: www.fao.org/mafap Suggested citation: Dias P., 2012. Analysis of incentives and disincentives for cotton in Mozambique. Technical notes series, MAFAP, FAO, Rome. © FAO 2013 FAO encourages the use, reproduction and dissemination of material in this information product. Except where otherwise indicated, material may be copied, downloaded and printed for private study, research and teaching purposes, or for use in non-commercial products or services, provided that appropriate acknowledgement of FAO as the source and copyright holder is given and that FAO’s endorsement of users’ views, products or services is not implied in any way. All requests for translation and adaptation rights, and for resale and other commercial use rights should be made via www.fao.org/contact-us/licence-request or addressed to [email protected].
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AFRICA 40 20 Dublin 0 20 Minsk 40 60 IRE. U.K. Amsterdam Berlin London Warsaw BELARUS RUSSIA NETH. KAZAKHSTAN Brussels GERMANY POLAND Kiev BEL. LUX. Prague N o r t h CZ. REP. UKRAINE Vol Aral SLOV. ga Sea Paris Bratislava Rostov A t l a n t i c Vienna MOL. Chisinau SWITZ. Bern AUS. Budapest Tashkent HUNG. Sea of FRANCE SLO. ROM. Odesa Azov Ljubljana CRO. Belgrade 40 O c e a n Milan Zagreb Bucharest UZBEKISTAN Marseilles BOS. & Danube AND. HER. SER.& Black Sea GEO. Caspian ITALYSarajevo MONT. Sofia Tbilisi Sea Ponta BULG. TURKMENISTAN PORTUGAL Barcelona Corsica Istanbul AZER. Delgada Rome Skopje ARM. Baku Ashgabat AZORES Madrid Tirana MACE. Ankara Yerevan (PORTUGAL) Lisbon Naples ALB. SPAIN Sardinia GREECE . Mashhad Izmir TURKEY Tabriz- Adana Algiers Tunis Sicily Athens Tehran Strait of Gibraltar Oran Aleppo AFG. MADEIRA ISLANDS Constantine Valletta Nicosia (PORTUGAL) Rabat SYRIA IRAQ Fès MALTA LEB. Esfahan- Casablanca CYPRUS Damascus ¸ Funchal TUNISIA Mediterranean Sea Beirut IRAN MOROCCO Baghdad Jerusalem Amman - CANARY ISLANDS Marrakech Tripoli Banghazi- - Alexandria ISRAEL Shiraz (SPAIN) Bandar Cairo JORDAN Kuwait - KUWAIT 'Abbas Al Jizah- Persian Las Palmas Nile Laayoune A L G E R I A Manama Gulf (El Aaiún) Abu BAHR. Dhabi Western L I B Y A EGYPT Riyadh Doha Muscat Medina Sahara QATAR U.A.E Al Jawf Aswan- Tropic of OMAN Cancer Admin. SAUDI boundary Jiddah 20 Nouadhibou ARABIA 20 Mecca MAURITANIA S A H A R A Port Red Sudan Sea CAPE VERDE Nouakchott Nile Tombouctou N I G E R Praia Agadez Omdurman ERITREA YEMEN Dakar MALI Arabian SENEGAL Khartoum Asmara Sanaa Banjul er CHAD Nig Niamey Zinder Sea Bamako BURKINA Lac'Assal Gulf of THE GAMBIA S U D A N Blue FASO (lowest point in Socotra N'Djamena Africa, -155 m) Djibouti Aden Bissau Kano (YEMEN) Ouagadougou Nile DJIBOUTI GUINEA-BISSAU GUINEA Nile Conakry BENIN E Y NIGERIA L Hargeysa GHANA White Addis L Freetown Abuja Moundou A CÔTE Volta Ababa TOGO Ogbomoso V SIERRA LEONE D'IVOIRE ue Prov.
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Research Risk factors associated with sexual violence towards girls in Swaziland Matthew J Breiding,a Avid Reza,b Jama Gulaid,c Curtis Blanton,b James A Mercy,a Linda L Dahlberg,a Nonhlanhla Dlaminid & Sapna Bamrahe Objective To explore risk factors for sexual violence in childhood in a nationally representative sample of females aged 13 to 24 years in Swaziland. Methods During a household survey respondents were asked to report any experiences of sexual violence before the age of 18 years. The association between childhood sexual violence and several potential demographic and social risk factors was explored through bivariate and multivariate logistic regression. Findings Participants totalled 1244. Compared with respondents who had been close to their biological mothers as children, those who had not been close to her had higher odds of having experienced sexual violence (crude odds ratio, COR: 1.89; 95% CI: 1.14–3.14), as did those who had had no relationship with her at all (COR: 1.93; 95% CI: 1.34–2.80). In addition, greater odds of childhood sexual violence were noted among respondents who were not attending school at the time of the survey (COR: 2.26; 95% CI: 1.70–3.01); who were emotionally abused as children (COR: 2.04; 95% CI: 1.50–2.79); and who knew of another child who had been sexually assaulted (COR: 1.77; 95% CI: 1.31–2.40) or was having sex with a teacher (COR: 2.07; 95% CI: 1.59–2.69). Childhood sexual violence was positively associated with the number of people the respondent had lived with at any one time (COR: 1.03; 95% CI: 1.01–1.06).
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Operation Update Report Southern Africa: Drought (Food Insecurity) Emergency appeal n°: MDR63003 GLIDE n°: __ Operation update n° 3: 15 February 2021 Timeframe covered by this update: September 2020 – December 2020 Operation start date: 11 December 2019 Operation timeframe and end date: 17 months, 31 May 2021 Funding requirements: CHF 7.4 million DREF amount initially allocated: CHF 768,800 N° of people targeted: Botswana: 7,750 - Eswatini: 25,000 - Lesotho: 23,000 - Namibia: 18,000 Total: 73,750 people (14,750 households) Red Cross Red Crescent Movement partners currently actively involved in the operation: American Red Cross, British Red Cross; Canadian Red Cross; Finnish Red Cross; Netherlands Red Cross; Spanish Red Cross; Swedish Red Cross Other partner organizations actively involved in the operation: Governments of Botswana, Eswatini, Lesotho and Namibia; Government of Japan. Swedish International Development Cooperation Agency (Sida), United States Agency for International Development (USAID); World Food Programme (WFP); Food and Agricultural Organisation (FAO); GIZ; and UNICEF. <Please click here for the budget and here for the contacts> Summary: This operation update reflects the current situation and information available since the last operation update published in September 2020. The operation timeframe will be extended by one month to end on 31 May 2021 to allow for a final evaluation to be completed. Simultaneously, as needs persist and the funding gap in 2020 allowed to reach less than half of the targeted people in many places, extending the operation further beyond May is being discussed. Following discussions with the National Societies and estimates of needs and possible activities, a new operation update may be published to extend the timeframe or the Emergency Appeal may be revised should a change of activities be foreseen.
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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.
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Cyclone Kenneth Cholera Modeled Maps
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