Data Grid Completeness
85% 
18/21 Core Data 20 Datasets 12 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.
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
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Affected People
3 Datasets
100% 
Internally-Displaced Persons
International Organization for Migration (IOM)
Refugees & Persons of Concern
Returnees
International Organization for Migration (IOM)
Humanitarian Needs
Coordination & Context
6 Datasets
50%  33%  16% 
3w - Who is doing what where
International Aid Transparency Initiative
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Transportation Status
Food Security & Nutrition
3 Datasets
100% 
Food security
Integrated Food Security Phase Classification (IPC)
Acute Malnutrition
Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
100% 
Populated Places
Roads
Humanitarian OpenStreetMap Team (HOT)
Airports
Humanitarian OpenStreetMap Team (HOT)
Health & Education
2 Datasets
100% 
Health Facilities
Education Facilities
OCHA Afghanistan
Population & Socio-economy
2 Datasets
100% 
Baseline Population
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 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-January 25, 2022
    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.
  • 600+ 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.
  • 10+ Downloads
    Updated 21 February 2021 | Dataset date: May 11, 2017-May 29, 2017
    This dataset updates: Never
    Afghanistan hosts a protracted population of Pakistani refugees, who fled North Waziristan Agency in 2014 as a result of a joint military offensive by Pakistani government forces against non-state armed groups. As of May 2017, UNHCR has biometrically registered over 50,000 refugees in Khost province and 36,000 refugees in Paktika province, where access remains a challenge. Over 16,000 of these refugees receive shelter and essential services in the Gulan camp in Khost province, while most of the others live among the host population in various urban and rural locations. To better understand the needs of the refugees and the host communities, UNHCR and WFP agreed to conduct a joint assessment of Pakistani refugees in Khost and Paktika. The data collection commenced in May 2017 and covered 2,638 refugee households (2,198 in Khost and 440 in Paktika).
  • Updated 7 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.
  • Updated 7 February 2021 | Dataset date: May 11, 2017-May 29, 2017
    This dataset updates: Never
    Afghanistan hosts a protracted population of Pakistani refugees, who fled North Waziristan Agency in 2014 as a result of a joint military offensive by Pakistani government forces against non-state armed groups. As of May 2017, UNHCR has biometrically registered over 50,000 refugees in Khost province and 36,000 refugees in Paktika province, where access remains a challenge. Over 16,000 of these refugees receive shelter and essential services in the Gulan camp in Khost province, while most of the others live among the host population in various urban and rural locations. To better understand the needs of the refugees and the host communities, UNHCR and WFP agreed to conduct a joint assessment of Pakistani refugees in Khost and Paktika. The data collection commenced in May 2017 and covered 2,638 refugee households (2,198 in Khost and 440 in Paktika).
  • 1000+ Downloads
    Updated 27 January 2021 | Dataset date: January 01, 2020-December 31, 2020
    This dataset updates: Every month
    Number of Refugees returning to Afghanistan for the period of 01 January 2020 to 31 December 2020 by district of destination and origin.
  • 1600+ Downloads
    Updated 27 January 2021 | Dataset date: January 01, 2019-January 31, 2019
    This dataset updates: Every day
    Number of Refugees returning to Afghanistan for the period of 01 January 2019 to 31 December 2019 by district of destination and origin.
  • 20+ Downloads
    Updated Live | Dataset date: November 16, 2015-January 25, 2022
    This dataset updates: Live
    List of aid activities by InterAction members in Afghanistan. Source: http://ngoaidmap.org/location/gn_1149361
  • 100+ Downloads
    Updated 23 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    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
  • 300+ Downloads
    Updated 23 November 2020 | Dataset date: January 01, 2000-December 31, 2020
    This dataset updates: Every year
    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
  • 70+ Downloads
    Updated 12 October 2020 | Dataset date: March 19, 2020-March 19, 2020
    This dataset updates: Every six months
  • 200+ Downloads
    Updated 5 October 2020 | Dataset date: January 01, 2019-December 31, 2019
    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.
  • 1500+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2015-December 31, 2017
    This dataset updates: As needed
    This dataset contains agency- and publicly-reported data on sexual violence and abuse against aid workers between January 2015 and December 2017.
  • 500+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: As needed
    This dataset is compiled from two categories of sources: (a) verified security events submitted to Insecurity Insight by 30 Aid in Danger partner agencies; and (b) publicly reported events identified by Insecurity Insight and published in the Aid in Danger Monthly News Brief. Events are categorised by date, country, type of organisation affected and event category, based on standard definitions.
  • 800+ Downloads
    Updated 9 September 2020 | Dataset date: January 01, 2018-December 31, 2018
    This dataset updates: As needed
    This dataset contains events in which an aid worker was involved in a road safety accident (RSA). Categorized by country.
  • 300+ Downloads
    Updated 4 September 2020 | Dataset date: August 31, 2020-August 31, 2020
    This dataset updates: As needed
    The new and emerging access constraints that people are currently experiencing because of the COVID-19 outbreak.
  • 100+ Downloads
    Updated 2 September 2020 | Dataset date: August 31, 2020-August 31, 2020
    This dataset updates: Every two weeks
    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
  • 392000+ Downloads
    Updated Live | Dataset date: January 22, 2020-January 24, 2022
    This dataset updates: Live
    Novel Corona Virus (COVID-19) epidemiological data since 22 January 2020. The data is compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) from various sources including the World Health Organization (WHO), DXY.cn, BNO News, National Health Commission of the People’s Republic of China (NHC), China CDC (CCDC), Hong Kong Department of Health, Macau Government, Taiwan CDC, US CDC, Government of Canada, Australia Government Department of Health, European Centre for Disease Prevention and Control (ECDC), Ministry of Health Singapore (MOH), and others. JHU CCSE maintains the data on the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository on Github. Fields available in the data include Province/State, Country/Region, Last Update, Confirmed, Suspected, Recovered, Deaths. On 23/03/2020, a new data structure was released. The current resources for the latest time series data are: time_series_covid19_confirmed_global.csv time_series_covid19_deaths_global.csv time_series_covid19_recovered_global.csv ---DEPRECATION WARNING--- The resources below ceased being updated on 22/03/2020 and were removed on 26/03/2020: time_series_19-covid-Confirmed.csv time_series_19-covid-Deaths.csv time_series_19-covid-Recovered.csv
  • 50+ Downloads
    Updated 21 July 2020 | Dataset date: December 23, 2021-December 23, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity = 'ferry_terminal' OR building = 'ferry_terminal' OR port IS NOT NULL Features may have these attributes: addr:full operator:type name building port addr:city amenity source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 10+ Downloads
    Updated 21 July 2020 | Dataset date: December 23, 2021-December 23, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IN ('mobile_money_agent','bureau_de_change','bank','microfinance','atm','sacco','money_transfer','post_office') Features may have these attributes: addr:full name network operator addr:city amenity source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 100+ Downloads
    Updated 21 July 2020 | Dataset date: December 23, 2021-December 23, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: aeroway IS NOT NULL OR building = 'aerodrome' OR emergency:helipad IS NOT NULL OR emergency = 'landing_site' Features may have these attributes: addr:full capacity:persons name building operator:type aeroway emergency:helipad addr:city emergency source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 90+ Downloads
    Updated 21 July 2020 | Dataset date: December 23, 2021-December 23, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IN ('kindergarten','school','college','university') OR building IN ('kindergarten','school','college','university') Features may have these attributes: addr:full capacity:persons operator:type name building addr:city amenity source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.