In 2016, OCHA merged its offices in Johannesburg and Nairobi into the OCHA Regional Office for Southern and Eastern Africa (ROSEA), covering 25 countries.
Comprising the Horn of Africa and the Great Lakes, eastern Africa is a region in which emergencies tend to be large scale, resulting in significant displacement and other needs. For this reason, OCHA maintains country presences in Burundi, DRC, Eritrea, Ethiopia, Kenya, Somalia, South Sudan and Sudan. The southern Africa region has fewer protracted humanitarian crises, but is prone to drought and floods. For this reason, OCHA does not have country offices in the region. In both regions the 2015-2016 El Nino weather phenomenon continues to have a significant humanitarian impact.
For those countries where OCHA does not have a presence, it is essential that OCHA can deploy from the regional hub swiftly and effectively in times of emergency, and to otherwise ensure preparedness for potential crises. OCHA works closely with local authorities and partners to bolster national disaster preparedness in these countries and supports response.
Whether we’re mobilizing relief money or raising awareness of forgotten crises, it’s our mandate to keep world attention focused on humanitarian issues. For this reason, we produce and release timely regional reporting and analytical products to strengthen the humanitarian case and highlight the needs of the most vulnerable in the region. OCHA ROSEA also provides a platform for the analysis of cross-border issues of humanitarian concern, such as facilitating multi-country preparedness and planning consultations. OCHA ROSEA also works to strengthen collaboration on emergency preparedness and response with regional bodies, such as the Intergovernmental Authority on Development (IGAD) in eastern Africa and the Southern Africa Development Community (SADC) in southern Africa.
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Use the tabs to browse the different risk indexes for the region. 1 is low risk (lighter) and 10 is high risk (darker). Click the map to filter the statistics for selected countries. The risk indexes are from the INFORM risk assessment. INFORM is a global, open-source risk assessment for humanitarian crises and disasters. It can support decisions about prevention, preparedness and response.
Updated November 19, 2018
| Dataset date: Sep 24, 2026
This dataset updates: Every three months
Aggregated data on food insecure population in Kenya, Ethiopia, Uganda, Sudan, South Sudan, Rwanda, Burundi, Djibouti and Somalia from Dec 2010 to Jan 2015
Updated November 8, 2018
| Dataset date: Oct 22, 2018
This dataset updates: Every year
Malawi administrative level 0 (country), 1 (region), 2 (district or city council), and 3 (traditional authority area) boundary polygon and line shapefiles and KMZ files and gazetteer.
P-codes are based on the NSO Admin 3 code system.
Some humanitarian actors are using an alternative 28-unit administrative level 2 (district) structure instead of the endorsed 32-unit structure. A lookup table is provided.
These shapefiles are suitable for database or ArcGIS linkage to the Malawi administrative level 0-3 population statistics tables.
Updated November 7, 2018
| Dataset date: Sep 4, 2018
This dataset updates: Every year
Uganda administrative level 0 (country), 1 (district), 2 (county, city council, or municipality), or 3 (sub-district) boundaries.
Please see caveats.
The administrative level 0 and 1 shapefiles are suitable for database or GIS linkage to the Uganda administrative level 0-1 population statistics population statistics tables.
Updated November 6, 2018
| Dataset date: Sep 28, 2018
This dataset updates: Every year
Madagascar administrative level 0 (country), 1 (region), 2 (district), 3 (commune), and 4 (fokontany) population statistics and gazetteer
These CSV tables are suitable for database or GIS linkage to the Madagascar administrative level 0 - 4 boundaries shapefiles.
Updated October 16, 2018
| Dataset date: Sep 5, 2018
This dataset updates: Every year
Uganda administrative level 0 (country) and 1 (district) population statistics and gazetteer.
ALERT: please see caveats
These population statistics tables are suitable for database or GIS linkage to the administrative level 0 and 1 boundaries available at Uganda administrative level 0-3 boundaries.
Updated October 2, 2018
| Dataset date: Sep 27, 2018
This dataset updates: Every year
The Admin boundary shapefiles for Rwanda since 2006. The shapefile was created in 2006 and updated by the 2012 Census mapping.
It was updated again on 17 Oct 2017.
These administrative level 0-3 shapefiles are suitable for database or GIS linkage to the Rwanda administrative level 0-3 population statistics tables.
02 October 2018 update:
Administrative level 1 (province) P-codes corrected at all levels.
27 September 2018 update:
Administrative level 0 (country) feature attributes corrected at all levels.
19 October 2018 update:
to Administrative levels 0 - 3:
Standardized P-codes, based on the pre-existing numeric codes added
Lake Kivu extent removed
Corrections made to two administrative level 1 names in the administrative level 3 (sector) shapefile
21 September 2018 update:
Administrative level 4 P-coded
Updated September 21, 2018
| Dataset date: Sep 21, 2018
This dataset updates: Every year
Rwanda administrative level 0 (country), 1 (province), 2 (district), and 3 (sector) population statistics (with urban / rural disaggregation)
These CSV tables are suitable for database or GIS linkage to the administrative level 0-3 shapefiles available at https://data.humdata.org/dataset/rwanda-administrative-boundaries-level-1-4 on HDX.
Updated September 21, 2018
| Dataset date: Aug 30, 2018
This dataset updates: Every year
Angola administrative level 0 (country), 1 (province), 2 (municipality | city council) and 3 (commune) boundary polygon, line, and point shapefiles, KMZ files, live services, and geodatabase; and gazetteer
Processed by ITOS 2018 09 07
ITOS live services anticipated shortly.
The administrative level 0-2 shapefiles are suitable for database or ArcGIS linkage to the population statistics tables.
Updated September 20, 2018
| Dataset date: Aug 31, 2018
This dataset updates: Every year
Zimbabwe administrative level 0 (country), 1 (province), 2 (district) and 3 (ward) boundary polygon, line, and point shapefiles, KMZ files, geodatabase, and live services, and gazetteer.
Processed by ITOS 2018 09 17.
ITOS live service deployment anticipated shortly.
These shapefiles are suitable for linkage by P-code to the Zimbabwe administrative levels 0 - 2 population statistics CSV population statistics tables.
Updated September 18, 2018
| Dataset date: Aug 31, 2018
This dataset updates: Every year
Zimbabwe administrative levels 0 (country), 1 (province), 2 (district) population statistics, source document, and levels 0 - 3 (ward) gazetteer
These CSV tables are suitable for linkage by P-code to the Zimbabwe administrative levels 0-3 boundaries shapefiles.
Updated September 5, 2018
| Dataset date: Dec 1, 2007-Dec 31, 2019
This dataset updates: Every year
Mozambique administrative level 0 (country), 1 (province), 2 (district) and 3 (posto) boundary polygons and gazetteer. The administrative level 0-2 shapefiles are suitable for database or ArcGIS linkage to the population statistics tables (excluding Census 2017 preliminary population per district )
Updated September 4, 2018
| Dataset date: Dec 31, 2007-Dec 31, 2019
This dataset updates: Every year
Mozambique INE population projections with gender at District(Admin 2), Province (Admin 1) and Country (Admin 0) level for 2007 and 2018 to 2020.
INE Census 2017 preliminary results with gender and households at Province (Admin 1) and Country (Admin 0) level with GIS shapefile linkage joins ; and District (Admin 2) level with no join.
These CSV tables are suitable for database or GIS linkage to the administrative level 0-2 shapefiles.
Updated August 16, 2018
| Dataset date: Jan 1, 2012
This dataset updates: Every year
Polling station locations
Abstract: This data comes from http://vote.iebc.or.ke
Use the _sphericalmercator versions with TileMill, will be much faster. Otherwise, you're probably fine with the unprojected versions.
There are simple endpoints for requesting json encoded data. download.py iterates, caches, and builds the output
Instructions: Polling station location Shapefile can be downloaded from https://github.com/mikelmaron/kenya-election-data/tree/master/output
