Data Grid Completeness
14/20 Core Data 16 Datasets 7 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
Not applicable
Coordination & Context
6 Datasets
3w - Who is doing what where
International Aid Transparency Initiative
Conflict Events
Humanitarian Access
Food Security & Nutrition
2 Datasets
Acute Malnutrition
Food Prices
WFP - World Food Programme
Health & Education
0 Datasets
Health Facilities
Education Facilities
Population & Socio-economy
2 Datasets
Poverty Rate
Oxford Poverty & Human Development Initiative
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  • 20+ Downloads
    Updated 24 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
  • 100+ Downloads
    Updated 24 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
  • 200+ Downloads
    Updated 16 October 2020 | Dataset date: January 01, 2018-December 31, 2019
    This dataset updates: Never
    The data describes financial transactions from OCHA to their implementing partners in IRQ and oPT, and then onwards to sub-implementing partners. The data is a combination of data from OCHA GMS and data collected from OCHA implementing parters. The data from Implementing partners complement OCHA:s data with information on when funds were recieved and if/when funds were sent on to sub-implementing partners. This allows for analysis of how long and costly financial transactions are.
  • 60+ Downloads
    Updated 14 September 2020 | Dataset date: July 08, 2020-July 10, 2021
    This dataset updates: Every year
    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 2020 methodology is detailed in Alkire, Kanagaratnam & Suppa (2020).
  • 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
  • 385000+ Downloads
    Updated Live | Dataset date: January 22, 2020-December 02, 2021
    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
  • 30+ Downloads
    Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 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:city name amenity port operator:type addr:full source building This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 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:city name amenity addr:full source network operator This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 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:city source aeroway name emergency operator:type addr:full emergency:helipad building capacity:persons This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 60+ Downloads
    Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: place IN ('isolated_dwelling','town','village','hamlet','city') Features may have these attributes: population place name source is_in This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 20+ Downloads
    Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: railway IN ('rail','subway','station') Features may have these attributes: addr:city railway name operator:type addr:full source ele layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 30+ Downloads
    Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: healthcare IS NOT NULL OR amenity IN ('doctors','dentist','clinic','hospital','pharmacy') Features may have these attributes: addr:city healthcare:speciality healthcare name amenity operator:type addr:full source building capacity:persons This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 30+ Downloads
    Updated 15 July 2020 | Dataset date: September 01, 2021-September 01, 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:city name amenity operator:type addr:full source building capacity:persons This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 100+ Downloads
    Updated 10 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: highway IS NOT NULL Features may have these attributes: bridge smoothness source oneway surface highway name width lanes layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 100+ Downloads
    Updated 10 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: waterway IS NOT NULL OR water IS NOT NULL OR natural IN ('water','wetland','bay') Features may have these attributes: covered natural source water name width blockage tunnel depth waterway layer This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 90+ Downloads
    Updated 8 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: amenity IS NOT NULL OR man_made IS NOT NULL OR shop IS NOT NULL OR tourism IS NOT NULL Features may have these attributes: beds addr:city addr:street man_made opening_hours addr:housenumber name amenity shop rooms addr:full source tourism This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 100+ Downloads
    Updated 8 July 2020 | Dataset date: September 01, 2021-September 01, 2021
    This dataset updates: Every month
    OpenStreetMap exports for use in GIS applications. This theme includes all OpenStreetMap features in this area matching: building IS NOT NULL Features may have these attributes: addr:city addr:street building building:levels source addr:housenumber name addr:full office building:materials This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
  • 10+ Downloads
    Updated 29 June 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. A description of the modelling methods used for age and sex structures can be found in Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here. Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020. The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping. 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/WP00646
  • Updated 29 June 2020 | Dataset date: January 01, 2015-December 31, 2018
    This dataset updates: Every year
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. State of Palestine 1km Pregnancies. Version 2.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00630
  • 10+ Downloads
    Updated 29 June 2020 | Dataset date: January 01, 2015-December 31, 2018
    This dataset updates: Every year
    The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al.. Data for earlier dates is available directly from WorldPop. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. State of Palestine 1km Births. Version 2.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00579
  • 1100+ Downloads
    Updated 6 May 2020 | Dataset date: January 01, 2020-December 31, 2020
    This dataset updates: Every year
    This data contains the number of people in need, internally displaced persons (IDPs), returnees and refugees for 25 countries.
  • 1100+ Downloads
    Updated 6 May 2020 | Dataset date: March 26, 2020-March 26, 2020
    This dataset updates: As needed
    Data on unmitigated(no intervention) COVID-19 scenarios for OCHA HRP countries. Simulation done by Imperial College London.