Somalia

Data Grid Completeness
Affected People
3 Datasets
100% 
Coordination & Context
5 Datasets
80%  20% 
Food Security & Nutrition
3 Datasets
100% 
Geography & Infrastructure
4 Datasets
50%  50% 
Health & Education
2 Datasets
50%  50% 
Population & Socio-economy
2 Datasets
50%  50% 
What is Data Grid Completeness?
Data Grid Completeness defines a set of core data that are essential for preparedness and emergency response. For select countries, the HDX Team and trusted partners evaluate datasets available on HDX and add those meeting the definition of a core data category to the Data Grid Completeness board above. Please help us improve this feature by sending your feedback to hdx@un.org.
Legend:
Presence, freshness, and quality of dataset
  • Dataset fully matches criteria and is up-to-date
  • Dataset partially matches criteria and/or is not up-to-date
  • No dataset found matching the criteria
  • Time Period of the Dataset [?]: January 01, 2020-August 20, 2021 ... More
    Modified [?]: 31 August 2021
    Dataset Added on HDX [?]: 11 November 2020
    Covid-19 cumulative recoveries in Africa, per country, per day from the beginning of the pandemic. Source : national governments.
    300+ Downloads
    This dataset updates: As needed
    This dataset is part of the data series [?]: HERA - Africa - Covid-19
  • Time Period of the Dataset [?]: January 01, 2020-August 20, 2021 ... More
    Modified [?]: 31 August 2021
    Dataset Added on HDX [?]: 12 November 2020
    Covid-19 death cases in Africa, per country, per day from the beginning of the pandemic. Source : national governments.
    500+ Downloads
    This dataset updates: As needed
    This dataset is part of the data series [?]: HERA - Africa - Covid-19
  • Time Period of the Dataset [?]: January 01, 2020-August 20, 2021 ... More
    Modified [?]: 31 August 2021
    Dataset Added on HDX [?]: 12 November 2020
    Covid-19 cumulative deaths in Africa, per country, per day from the beginning of the pandemic. Source : national governments.
    400+ Downloads
    This dataset updates: As needed
    This dataset is part of the data series [?]: HERA - Africa - Covid-19
  • Time Period of the Dataset [?]: January 01, 2020-August 20, 2021 ... More
    Modified [?]: 31 August 2021
    Dataset Added on HDX [?]: 11 November 2020
    Covid-19 infected cases in Africa, per country, per day from the beginning of the pandemic. Source : national governments.
    600+ Downloads
    This dataset updates: As needed
    This dataset is part of the data series [?]: HERA - Africa - Covid-19
  • Time Period of the Dataset [?]: January 01, 2020-August 20, 2021 ... More
    Modified [?]: 31 August 2021
    Dataset Added on HDX [?]: 11 November 2020
    Covid-19 cumulative cases in Africa, per country, per day from the beginning of the pandemic. Source : national governments.
    300+ Downloads
    This dataset updates: As needed
    This dataset is part of the data series [?]: HERA - Africa - Covid-19
  • Time Period of the Dataset [?]: January 01, 2020-August 20, 2021 ... More
    Modified [?]: 31 August 2021
    Confirmed [?]: 27 September 2021
    Dataset Added on HDX [?]: 19 May 2020
    Daily Covid-19 cases in african countries : daily infections, recoveries and deaths and cumulative cases of infections, recoveries and deaths since the beginning of the pandemic.
    1100+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: January 01, 1990-August 15, 2021 ... More
    Modified [?]: 22 August 2021
    Dataset Added on HDX [?]: 15 April 2015
    This no longer updated dataset contains Global Food Prices data from the World Food Programme covering foods such as maize, rice, beans, fish, and sugar for 76 countries and some 1,500 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
    10000+ Downloads
    This dataset updates: Never
  • Time Period of the Dataset [?]: January 01, 2020-March 29, 2024 ... More
    Modified [?]: 22 July 2021
    Dataset Added on HDX [?]: 25 June 2020
    The data shows key figures on Education in Emergencies (EiE) at country level and as reported by country clusters
    400+ Downloads
    This dataset updates: Every year
  • Time Period of the Dataset [?]: June 23, 2021-June 23, 2021 ... More
    Modified [?]: 15 July 2021
    Dataset Added on HDX [?]: 15 July 2021
    The data provides information on location of schools and number of students enrolled in Somalia.
    100+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: March 01, 2020-December 31, 2020 ... More
    Modified [?]: 15 April 2021
    Dataset Added on HDX [?]: 15 April 2021
    Under the leadership of UNDP and DCO, an inter-agency task team developed the UN framework for the immediate socio-economic response to COVID-19 (adopted in April 2020) to govern its response over 12 to 18 months. To measure the UN’s support to the socio-economic response and recovery, UN entities developed a simple monitoring framework with 18 programmatic indicators (endorsed by the UNSDG in July 2020). Lead entities – based on their mandate and comparative advantage – were nominated to lead the development of methodological notes for each indicator and lead the collection of data at the country level. These lead entities reported through the Office of the Resident Coordinators the collective UN results on a quarterly basis through UN Info. All 2020 data was reported by March 2021. This is the UN development system’s first comprehensive attempt at measuring its collective programming contribution and results. These programmatic indicators enabled the UN system to monitor the progress and achievements of UNCT’s collective actions in socio-economic response. In support of the Secretary-General’s call for a "… single, consolidated dashboard to provide up-to-date visibility on [COVID-19] activities and progress across all pillars” all data was published in real time on the COVID-19 data portal, hosted by DCO. The data is disaggregated by geography (rural/urban), sex, age group and at-risk populations -- to measure system-wide results on the socio-economic response to the pandemic, in order to ensure UNDS accountability and transparency for results.
    300+ Downloads
    This dataset updates: Every three months
  • Time Period of the Dataset [?]: January 01, 2018-December 31, 2018 ... More
    Modified [?]: 10 April 2021
    Dataset Added on HDX [?]: 11 April 2021
    The UNHCR Livelihoods Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation). The process for developing the indicators began in 2015 with a review of existing tools and approaches. Consultations were held with governments, the private sector, field-based staff and civil society partners to devise a set of common, standardized measures rooted in global good practices. Since 2017, a data collection (survey) has been rolled out globally, and the participating operations conducted a household surveys to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline and endline data from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact. More info is available on the official website: https://lis.unhcr.org
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Livelihoods Programme Monitoring Beneficiary Survey
  • Time Period of the Dataset [?]: January 01, 2019-December 31, 2019 ... More
    Modified [?]: 10 April 2021
    Dataset Added on HDX [?]: 11 April 2021
    The UNHCR Livelihoods Monitoring Framework takes a program-based approach to monitoring, with the aim of tracking both outputs and the impact of UNHCR dollars spent on programming (either via partners or through direct implementation). The process for developing the indicators began in 2015 with a review of existing tools and approaches. Consultations were held with governments, the private sector, field-based staff and civil society partners to devise a set of common, standardized measures rooted in global good practices. Since 2017, a data collection (survey) has been rolled out globally, and the participating operations conducted a household surveys to a sample of beneficiaries of each livelihoods project implemented by UNHCR and its partner. The dataset consists of baseline and endline data from the same sample beneficiaries, in order to compare before and after the project implementation and thus to measure the impact. More info is available on the official website: https://lis.unhcr.org
    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Livelihoods Programme Monitoring Beneficiary Survey
  • Time Period of the Dataset [?]: May 05, 2020-May 05, 2020 ... More
    Modified [?]: 6 April 2021
    Dataset Added on HDX [?]: 6 April 2021
    This data was developed as part of the Modelling Exposure Through Earth Observation Routines (METEOR) project and is a Level 1, or a global-quality exposure data set. Minimal country-specific data was collected. The data is intended for CAT modeling and loss estimation. Repurposing this data for any reason other than assessing risk is not recommended. The data presents the estimated number of buildings, building area, and rebuilding value at a 15-arcsecond grid resolution (approximately 500 meters at the equator). This data set is in point shapefile format where the points represent the centroids of the 15-arcsecond grid. The results were created through a process of spreading the number of buildings to the 15-arcsecond level by a statistical assessment of moderate resolution EO data, which is described in more detail in the dasymetric mapping lineage processing step. The estimated building count at any given area is a result of statistical processes and should not be mistaken as a building count. The structural classes of buildings used for risk assessment are estimated given the building wall, floor, and roof material classes surveyed through 2002 Population and Housing Census - Volume 1. Analytical report. Additionally, the data is provided in Open Exposure Data (OED) import format, as a pair of CSV files. One CSV file contains the location details, and the other is an "account" file that is filled with default information to satisfy OED format requirements. The OED input files are set to use "All perils" (i.e. "AA1"). All required OED account-related fields are populated with "1" by default (such as PortNumber, AccNumber, PolNumber). If you find this data useful please provide feedback via our questionnaire; it should take only a few minutes: https://forms.gle/DQjhE89CRegNKB3X8 Please see the METEOR project page for information about the METEOR Project: http://meteor-project.org/ Please see the METEOR map portal for interactive maps: https://maps.meteor-project.org/ For more information about the Open Exposure Data (OED) standard, please see https://github.com/OasisLMF/OpenDataStandards
    30+ Downloads
    This dataset updates: Never
    This dataset is part of the data series [?]: Global Earthquake Model Foundation - Level 1 Exposure Data
  • Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More
    Modified [?]: 6 March 2021
    Dataset Added on HDX [?]: 17 August 2020
    COVID-19 Situation and Response Dashboard for Annual 2020
    100+ Downloads
    This dataset updates: Never
  • Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More
    Modified [?]: 6 March 2021
    Dataset Added on HDX [?]: 11 December 2019
    UNICEF Eastern and Southern Africa Risks and Hazards- situation and response
    100+ Downloads
    This dataset updates: Never
  • Time Period of the Dataset [?]: July 29, 2020-September 27, 2020 ... More
    Modified [?]: 4 March 2021
    Dataset Added on HDX [?]: 5 August 2020
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
    80+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: November 20, 2020-November 20, 2020 ... More
    Modified [?]: 4 March 2021
    Dataset Added on HDX [?]: 20 November 2020
    Data on access constraints, aid workers security, % of affected CERF and CBPF projects combined with the status of Polio vaccination in the HRP countries.
    400+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: July 29, 2020-September 27, 2020 ... More
    Modified [?]: 1 January 2021
    Dataset Added on HDX [?]: 5 August 2020
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
    60+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: December 31, 2019-December 31, 2019 ... More
    Modified [?]: 30 October 2020
    Dataset Added on HDX [?]: 15 October 2019
    UNICEF Eastern and Southern Africa Risks and Hazards- situation
    100+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: October 31, 2020-October 31, 2020 ... More
    Modified [?]: 30 October 2020
    Dataset Added on HDX [?]: 3 March 2020
    Eastern and Southern Africa Risk Analysis based on Inform, FEWSNET, OCHA, UNICEF and others
    200+ Downloads
    This dataset updates: Every six months
  • Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 12 September 2020
    Dataset Added on HDX [?]: 20 July 2017
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App. The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively): - Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020. - Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019) -Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019). -Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets. -Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020. -Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019). Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645
    200+ Downloads
    This dataset updates: Every year
    This dataset is part of the data series [?]: World Pop - Population Counts
  • Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More
    Modified [?]: 4 September 2020
    Dataset Added on HDX [?]: 26 May 2020
    The new and emerging access constraints that people are currently experiencing because of the COVID-19 outbreak.
    400+ Downloads
    This dataset updates: As needed
  • Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More
    Modified [?]: 2 September 2020
    Dataset Added on HDX [?]: 22 July 2020
    This dataset contains scores for humanitarian access constraints into country, constraints within country, impacts the constraints have led to as well as the mitigation strategies in place to limit the impact. The scores have the following interpretations: 0 = NA, 1 = No or open, 2 = partially open/closed, 3 = Yes or closed
    100+ Downloads
    This dataset updates: Every two weeks
  • Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 22 June 2020
    Dataset Added on HDX [?]: 24 November 2020
    WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator) -Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method. -Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
    100+ Downloads
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Population Density
  • Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More
    Modified [?]: 6 May 2020
    Confirmed [?]: 6 May 2020
    Dataset Added on HDX [?]: 6 May 2020
    This data contains the number of people in need, internally displaced persons (IDPs), returnees and refugees for 25 countries.
    500+ Downloads
    This dataset updates: Every year