Data Grid Completeness
17/21 Core Data 19 Datasets 11 Organisations Show legend
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.
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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
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Affected People
3 Datasets
Internally-Displaced Persons
Refugees & Persons of Concern
Returnees
Humanitarian Needs
Coordination & Context
5 Datasets
3w - Who is doing what where
International Aid Transparency Initiative
Conflict Events
Transportation Status
Food Security & Nutrition
3 Datasets
Food security
Integrated Food Security Phase Classification (IPC)
Acute Malnutrition
Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
Populated Places
Roads
Humanitarian OpenStreetMap Team (HOT)
Airports
Humanitarian OpenStreetMap Team (HOT)
Health & Education
2 Datasets
Health Facilities
Education Facilities
OCHA Afghanistan
Population & Socio-economy
2 Datasets
Baseline Population
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 2000+ Downloads
    Updated 9 May 2021 | Dataset date: January 01, 2020-December 27, 2020
    This dataset updates: As needed
    1) Natural disaster events include avalanches, earthquakes, flooding, heavy rainfall & snowfall, and landslides & mudflows as recorded by OCHA field offices based on assessments in the field. 2) A natural disaster incident is defined as an event that has affected (i.e. impacted) people, who may or may not require humanitarian assistance. 3) The information includes assessment figures from OCHA, ANDMA, IOM, Red Crescent Societies, national NGOs, international NGOs, and ERM. 4) The number of affected people and houses damaged or destroyed are based on the reports received. These figures may change as updates are received.
  • 60+ Downloads
    Updated 8 May 2021 | Dataset date: May 19, 2020-May 19, 2020
    This dataset updates: As needed
    Pool fund Extended allocation Details
  • 300+ Downloads
    Updated 6 May 2021 | Dataset date: January 01, 2016-December 31, 2020
    This dataset updates: As needed
    This dataset contains events where air- and ground-launched explosive weapons affected health facilities between 2016 and 2020.
  • 400+ Downloads
    Updated 4 May 2021 | Dataset date: January 01, 1990-December 31, 2030
    This dataset updates: Every year
    The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities. The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.
  • 10+ Downloads
    Updated 4 May 2021 | Dataset date: May 05, 2014-May 05, 2014
    This dataset updates: Never
    This is "Flood vectors - Komsat-2 (05 May 2014)" of the Flood analysis for Afghanistan which began on 30 April 2014. It includes 536 satellite detected water bodies with a spatial extent of 3.52 square kilometers derived from the Komsat-2 image acquired o...
  • 7600+ Downloads
    Updated 30 April 2021 | Dataset date: January 01, 2016-December 31, 2020
    This dataset updates: As needed
    The Safeguarding Health in Conflict Coalition (SHCC) is made up of 40 health provider organizations, humanitarian groups, human rights organizations, NGOs, and academic programs to take action to protect health workers and end attacks against them. This page is managed by SHCC member Insecurity Insight.
  • 1000+ Downloads
    Updated 20 April 2021 | Dataset date: April 01, 2016-June 30, 2016
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 700+ Downloads
    Updated 20 April 2021 | Dataset date: April 01, 2017-June 30, 2017
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 900+ Downloads
    Updated 20 April 2021 | Dataset date: January 01, 2017-March 31, 2017
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 900+ Downloads
    Updated 20 April 2021 | Dataset date: January 01, 2016-March 31, 2016
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 400+ Downloads
    Updated 20 April 2021 | Dataset date: January 01, 2021-December 31, 2021
    This dataset updates: Every year
    Afghanistan administrative levels 0 (country), and 1 (province) population statistics. REFERENCE YEAR: 2021 estimates based on 2017 study conducted by Flowminder/UNFPA. Dataset updated by OCHA in 2021. The gazetteer is compatible with the Afghanistan - Subnational Administrative Boundaries gazetteer. (COD-AB boundaries are unavailable.)
  • 200+ Downloads
    Updated 18 April 2021 | Dataset date: October 01, 2020-December 31, 2020
    This dataset updates: Every three months
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 500+ Downloads
    Updated 18 April 2021 | Dataset date: January 01, 2020-March 31, 2020
    This dataset updates: Every three months
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 200+ Downloads
    Updated 18 April 2021 | Dataset date: April 01, 2020-June 30, 2020
    This dataset updates: Never
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 300+ Downloads
    Updated 18 April 2021 | Dataset date: July 01, 2020-September 30, 2020
    This dataset updates: Every three months
    The Who does What Where (3W) is a core humanitarian coordination dataset. It is critical to know where humanitarian organizations are working, what they are doing and their capability in order to identify gaps, avoid duplication of efforts, and plan for future humanitarian response (if needed). The data includes a list of humanitarian organizations by district and cluster, as well as a unique count of organizations. An interactive map of the 3W data can be accessed here.
  • 100+ Downloads
    Updated 15 April 2021 | Dataset date: March 01, 2020-December 31, 2020
    This dataset updates: Every three months
    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.
  • Updated 11 April 2021 | Dataset date: January 01, 2019-December 31, 2019
    This dataset updates: Never
    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
  • 100+ Downloads
    Updated 7 April 2021 | Dataset date: March 12, 2021-March 12, 2021
    This dataset updates: As needed
    Compilation of international financial institution and economic data
  • 2300+ Downloads
    Updated 30 March 2021 | Dataset date: January 01, 2020-December 30, 2020
    This dataset updates: As needed
    Newly displaced population due to conflict between 01 January 2020 and 30 December 2020, compiled by OCHA sub offices based on inter-agency assessment results. This data is a snapshot as of 30 Mar 2021 and the numbers are expected to change as new assessment figures become available.
  • 90+ Downloads
    Updated 22 March 2021 | Dataset date: May 01, 2017-March 31, 2022
    This dataset updates: As needed
    The IPC Acute Food Insecurity (IPC AFI) classification provides strategically relevant information to decision makers that focuses on short-term objectives to prevent, mitigate or decrease severe food insecurity that threatens lives or livelihoods. This data has been produced by the National IPC Technical Working Groups for IPC population estimates since 2017. All national population figures are based on official country population estimates. IPC estimates are those published in country IPC reports.
  • 30+ Downloads
    Updated 9 March 2021 | Dataset date: May 05, 2020-May 05, 2020
    This dataset updates: Never
    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
  • 100+ Downloads
    Updated Live | Dataset date: February 08, 2021-December 08, 2021
    This dataset updates: Live
    Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country
  • 200+ Downloads
    Updated 4 March 2021 | Dataset date: November 20, 2020-November 20, 2020
    This dataset updates: As needed
    Data on access constraints, aid workers security, % of affected CERF and CBPF projects combined with the status of Polio vaccination in the HRP countries.
  • 500+ Downloads
    Updated 22 February 2021 | Dataset date: December 01, 2020-February 19, 2021
    This dataset updates: As needed
    The dataset contains 93 harmonized indicators on 14 topics (demographic, food security, education, labor, health..) on households and individuals in 44 countries across all developing regions.
  • Updated 21 February 2021 | Dataset date: January 01, 2017-December 31, 2017
    This dataset updates: Never
    At the end of 2015, Herat Province was among the highest IDP hosting provinces in Afghanistan, accounting for approximately 10% of the country's IDP population. In order to obtain reliable information on the socio-economic conditions of IDPs and returnees in Herat Province, a comprehensive sample survey was carried out among 11,264 households in the 5 most populated IDP/returnee settlements (Shagofan, Jebraiel, Maslakh, Now Abad and Kahdistan) in 2017.