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
Updated
15 February 2022
| Dataset date: January 01, 2017-December 31, 2021
This page provides the data published in the Education in Danger Monthly News Brief.
All data contains incidents identified in open sources. Categorized by country and with link to the relevant Monthly News Brief (where possible).
Updated
10 February 2022
| Dataset date: December 31, 2019-September 23, 2020
The Database of Government Actions on COVID-19 in Developing Countries collates and tracks national policies and actions in response to the pandemic, with a focus on developing countries.
The database provides information for 20 Global South countries – plus 6 Global North countries for reference – that Dalberg staff are either based in or know well. The database content is drawn from publicly available information combined, crucially, with on-the-ground knowledge of Dalberg staff.
The database contains a comprehensive set of 100 non-pharmaceutical interventions – organized in a framework intended to make it easy to observe common variations between countries in the scope and extent of major interventions. Interventions we are tracking include:
• Health-related: strengthening of healthcare systems, detection and isolation of actual / possible cases, quarantines
• Policy-related: government coordination and legal authorization, public communications and education, movement restrictions
• Distancing and hygiene: social distancing measures, movement restrictions, decontamination of physical spaces
• Economic measures: economic and social measures, logistics / supply chains and security.
We hope the database will be a useful resource for several groups of users: (i) governments and policymakers looking for a quick guide to actions taken by different countries—including a range of low- and middle-income countries, (ii) policy analysts and researchers studying the data to identify patterns of actions taken and compare the effectiveness of different interventions in curbing the pandemic, and (iii) media and others seeking to quickly access facts about the actions taken by governments in the countries covered in the database.
Comments on the data can be submitted to covid.database.comments@dalberg.com
Questions can be submitted to covid.database.questions@dalberg.comwww.dalberg.com
Updated
14 January 2022
| Dataset date: September 21, 2020-September 21, 2020
This data contains aggregated weighted statistics at the regional level by gender for the 2020 Survey on Gender Equality At Home as well as the country and regional level for the 2021 wave. The Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality. Researchers and nonprofits interested in access to survey microdata can apply at:
https://dataforgood.facebook.com/dfg/tools/survey-on-gender-equality-at-home
Updated
Live
| Dataset date: January 01, 2020-December 31, 2020
This dataset contains the following administrative boundaries: ADM0, ADM1, ADM2.
Produced and maintained since 2017, the geoBoundaries Global Database of Political Administrative Boundaries Database www.geoboundaries.org is an open license, standardized resource of boundaries (i.e., state, county) for every country in the world.
Updated
31 December 2021
| Dataset date: July 01, 2021-August 16, 2022
West and Central Africa Administrative boundaries, administrative level 0 to 2. Notice: The boundaries and names shown and the designations used on these shapefiles do not imply official endorsement or acceptance by the United Nations.
West and Central Africa settlements with administrative capitals
Updated
16 December 2021
| Dataset date: November 17, 2021-August 16, 2022
This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100 m grid cells) with national coverage for Nigeria, along with estimates of the number of people belonging to various age-sex groups. Version 2.0 is an update to the previous version 1.2 gridded population estimates and is based on more recent and detailed settlement information and a different regional boundary definition. These model-based population estimates most likely represent the time period around 2019, corresponding to the period when the satellite imagery was processed to generate building footprints. Populations are mapped only into areas where residential settlements are predicted.
These data were produced by the WorldPop Research Group at the University of Southampton in collaboration with the National Population Commission of Nigeria. This work was part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3 ) programme with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network (CIESIN), a center within the Columbia Climate School at Columbia University, and the Flowminder Foundation. Statistical modelling was led by Chris Jochem and Doug Leasure additional support and oversight from Attila Lazar and Andy Tatem. Chris Lloyd provided the residential building classification. The microcensus data were originally collected by eHealth Africa and Oak Ridge National Laboratory with support from the Bill and Melinda Gates Foundation. The WorldPop grou and GRID3 partners are acknowledged for their project support.
RELEASE CONTENT
NGA_population_v2_0_gridded.zip
NGA_population_v2_0_admin.zip
NGA_population_v2_0_sql.sql
NGA_population_v2_0_mastergrid.tif
NGA_population_v2_0_tiles.zip
NGA_population_v2_0_agesex.zip
LICENSE
These data (1-6) may be redistributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Recommended citations
WorldPop and National Population Commission of Nigeria. 2021. Bottom-up gridded population estimates for Nigeria, version 2.0. WorldPop, University of Southampton. doi: 10.5258/SOTON/WP00729.
For further details, please, read NGA_population_v2_0_README.pdf
Updated
15 December 2021
| Dataset date: October 13, 2021-October 13, 2021
We use an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook.
Details on the underlying data and the construction of the index are provided in the “Facebook Social Connectedness Index - Data Notes.pdf” file. Please also see https://dataforgood.fb.com/ as well as the associated research paper “Social Connectedness: Measurement, Determinants and Effects,” published in the Journal of Economic Perspectives (https://www.aeaweb.org/articles?id=10.1257/jep.32.3.259).
Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html. Future versions will update IDs to be compatible with the newest GADM version.
Updated
14 December 2021
| Dataset date: October 07, 2021-October 15, 2022
This table contains subnational multidimensional poverty data from the data tables published by the Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. The global Multidimensional Poverty Index (MPI) measures multidimensional poverty in over 100 developing countries, using internationally comparable datasets and is updated annually. The measure captures the severe deprivations that each person faces at the same time using information from 10 indicators, which are grouped into three equally weighted dimensions: health, education, and living standards. The global MPI 2021 methodology is detailed in Alkire, Kanagaratnam & Suppa (2021).
Updated
Live
| Dataset date: January 01, 2019-August 16, 2022
Live list of active aid activities for Nigeria shared via the International Aid Transparency Initiative (IATI). Includes both humanitarian and development activities. More information on each activity (including financial data) is available from http://www.d-portal.org
Updated
24 November 2021
| Dataset date: November 01, 2021-August 16, 2022
Designated institutions to provide learning spaces and learning environments for the teaching of students. This data has been extracted from GRID3 Nigeria site
Updated
23 November 2021
| Dataset date: May 20, 2019-May 20, 2019
VERSION 1.5. The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Nigeria: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).
There is also a tiled version of this dataset that may be easier to use if you are interested in many countries.
Updated
17 November 2021
| Dataset date: September 11, 2020-September 11, 2020
Administrative level 3 boundaries for selected Sahel countries edge-matched and derived from respective COD-AB datasets.
P-codes match source datasets.
Updated
15 November 2021
| Dataset date: June 01, 2021-December 31, 2021
In the humanitarian context / humanitarian profiling, it demonstrates a strong evidence base, positive impact on resource allocation, and forms the basis and reference point of any relief operation aiming to deliver aid according to the population’s needs.
This data gives the total size of population for Borno, Adamawa, and Yobe states (BAY) and disaggregated by sex and age (SADD) for each population category.
The population category is grouped into:
• Internally displaced people (IDP)
• Returnees
• Host community
• Inaccessible areas
Updated
7 November 2021
| Dataset date: June 01, 2020-July 16, 2020
Further the emergence of COVID-19 and the perceived socioeconomic hardship imposed by the measures put in place to curtail the spread of the virus, the United High Commissioner for Refugees (UNHCR) in conjunction with several partners in Nigeria carried out a study to understand the socioeconomic impact of COVID-19 among Persons of Concern to UNHCR including refugees, internally displaced persons, returnees, asylum-seekers, stateless persons and community members hosting displaced populations. The study examines several dimensions including the impact of the pandemic on economic, social, cultural, civil, and political rights.
Updated
27 October 2021
| Dataset date: January 01, 2016-September 30, 2021
This dataset includes the latest available information on COVID-19 developments impacting the security of aid and health work and operations to help aid agencies meet duty of care obligations to staff and reach people in need.
Updated
21 October 2021
| Dataset date: November 30, 2019-August 31, 2021
The Who Does What Where is a core humanitarian dataset for coordination. This data contains operational presence of humanitarian partners in Nigeria at admin 3 (ward) level by cluster.
Updated
19 October 2021
| Dataset date: September 12, 2018-September 12, 2018
The regional INFORM Sahel model was initiated by Emergency Response and Preparedness Group of regional Inter-Agency Standing Committee (IASC) and is managed by OCHA. The INFORM model is being used to support the Humanitarian Programme Cycle and coordinated preparedness actions. Partners hope to use the model to improve cooperation between humanitarian and development actors in managing risk and building resilience across the region.
Updated
17 October 2021
| Dataset date: January 01, 2020-December 31, 2020
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
Updated
28 September 2021
| Dataset date: September 24, 2021-September 24, 2021
Hospitals and Clinics with registration status and Location in Nigeria. This dataset has been publicly provided by the Nigeria Federal Ministry of Health on the NIGERIA Health Facility Registry (HFR) website
