OCHA has mobilized and coordinated humanitarian efforts in Somalia since 1999. The humanitarian crisis in Somalia remains significant and OCHA aims to ensure a well-coordinated, effective and principled inter-agency humanitarian response. By providing a coherent approach to humanitarian action in Somalia, OCHA helps to avoid duplication of aid response and maximizes resources.
Access to parts of Somalia remains a key challenge due to insecurity. Despite this, OCHA Somalia continues to evolve to reflect the humanitarian and operating landscape in Somalia and has offices in Mogadishu and seven larger towns throughout the country, and an office in Nairobi, Kenya.
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13 October 2021
| Dataset date: June 30, 2020-June 30, 2020
This dataset updates: As needed
This dataset contains the data used by the Humanitarian Country Team in Somalia to monitor the evolution of the drought and flood situation in Somalia. The data covers the following topics:
Internal displacement by cause (drought related, conflict/insecurity, other cause)
River levels in the Shabelle and Juba rivers
Water prices by Region
Cumulative annual rainfall
Disease burden (acute watery diarrhea (AWD)/cholera, bloody diarrhea and measles)
Monthly response monitoring by region for the following indicators:
CCCM: Number of people benefiting from site improvement projects
EDUCATION: Number of children with access to safe drinking water
FOOD SECURITY: Number of people reached through activities geared towards improving access to food and safety nets
HEALTH: Number of medical consultations
NUTRITION: Number of acute malnutrition admissions
PROTECTION: Number of girls and boys, women and men participating in community-based psycho-social activities
SHELTER: Number of people in need of emergency assistance receiving appropriate NFIs through in-kind distribution, vouchers or cash
WASH: Number of people reached with access to sustainable safe water services
The sources for the data are as follows: IDP data (PRMN/UNHCR); Rainfall and Rivers (SWALIM); Diseases (Health Cluster/WHO); Monthly Response (Humanitarian Clusters), Water Prices (FAO)
30 September 2021
| Dataset date: June 06, 2014-October 17, 2021
This dataset updates: Every year
Summary: Somalia Regional Boundaries - Polygon - SHP
Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
Abstract: Somalia has 2 levels of administrative Boundaries CODs: Admin level 1 = Region; Admin Level 2 = District. There are multiple pcode formats in this shapefile (Region_AdminLevel1),REG_CODE is used by humanitarian partners in Somalia and was developed by the United National Development Programme (1998).HRpcodes are duplicates of REG_CODE and can be used to link to products derived from HR.info such as the assessment registry. Regional-boundaries_polygon is the earlier registered dataset.
21 August 2020
| Dataset date: August 14, 2019-August 14, 2019
This dataset updates: Every year
The United Nations Population Fund (UNFPA) partnered with donors and UN agencies and took up the lead role to support the Somali authorities in undertaking the Population Estimation Survey (PESS) for Somalia in October 2013- March 2014.
REFERENCE YEAR: 2014
PESS gathered basic critical information on the Somalis living in urban, rural and nomadic areas (interviewed at water points during the peak of the long, dry season), and in settlements for internally displaced persons. One standard questionnaire was used in selected enumeration areas or pre-identified areas. Data was collected in three main phases: cartographic field mapping, household listing in the sampled areas, and the interviewing of households using the standard questionnaire.
PESS report by UNFPA had only the population estimate at regional level (Admin level 1). With the demand to get this data disaggregated to district level to enhance assessment and in particular assessments of people in food insecure by FAO-FSNAU, the district data was interpolated using FSNAU livelihood information embedded in the 2005 UNDP district level population data