Data Grid Completeness
16/27 Core Data 38 Datasets 13 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
6 Datasets
Internally-Displaced Persons
International Organization for Migration
Refugees & Persons of Concern
Returnees
International Organization for Migration
Humanitarian Profile Locations
Humanitarian Needs
Casualties
Coordination & Context
10 Datasets
Food Security & Nutrition
4 Datasets
Food security
Integrated Food Security Phase Classification (IPC)
Severe Acute Malnutrition Rate
Food Prices
WFP - World Food Programme
Geography & Infrastructure
9 Datasets
Administrative Divisions
Populated Places
Humanitarian OpenStreetMap Team (HOT)
Roads
Humanitarian OpenStreetMap Team (HOT)
OCHA Sudan
Airports
Humanitarian OpenStreetMap Team (HOT)
Health & Education
7 Datasets
Health Facilities
Global Healthsites Mapping Project
Humanitarian OpenStreetMap Team (HOT)
Affected Schools
Population & Socio-economy
3 Datasets
Baseline Population by Age & Sex
Poverty Rate
Oxford Poverty & Human Development Initiative
Data Datasets [260] | Archived Datasets[0] [?] Show filter:
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  • 2500+ Downloads
    Updated 2 February 2021 | Dataset date: January 01, 2020-December 31, 2020
    This dataset updates: As needed
    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.
  • 400+ Downloads
    Updated 22 January 2021 | Dataset date: July 31, 2021-July 31, 2021
    This dataset updates: Every year
    This dataset shows the number of people in need(PiN), funds required and funds received by country and over the years, from 2010 to 2021.
  • 60+ Downloads
    Updated 18 January 2021 | Dataset date: January 11, 2021-September 16, 2021
    This dataset updates: As needed
    The data shows the refugee camps in Sudan
  • 50+ Downloads
    Updated 18 January 2021 | Dataset date: January 11, 2021-September 16, 2021
    This dataset updates: As needed
    This shapefile shows the Refugee camps in Sudan
  • 20+ Downloads
    Updated Live | Dataset date: November 16, 2015-September 16, 2021
    This dataset updates: Live
    List of aid activities by InterAction members in Sudan. Source: http://ngoaidmap.org/location/gn_366755
  • 90+ Downloads
    Updated 10 December 2020 | Dataset date: December 01, 2020-December 01, 2020
    This dataset updates: Every six months
    The data shows Who is doing What and Where by locality in Sudan
  • 30+ Downloads
    Updated 9 December 2020 | Dataset date: November 22, 2020-November 22, 2020
    This dataset updates: Every six months
    Sudan 3Ws data for November 2020
  • 90+ 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. 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
  • 200+ 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. 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
  • 90+ Downloads
    Updated 17 November 2020 | Dataset date: July 26, 2020-July 26, 2020
    This dataset updates: As needed
    Sudan Settlement 26 July 2020
  • 100+ Downloads
    Updated 12 November 2020 | Dataset date: November 10, 2020-November 10, 2020
    This dataset updates: As needed
    This data is showing the number of affected people by floods per year from 2013 to 2020
  • 50+ Downloads
    Updated 21 October 2020 | Dataset date: May 01, 2018-July 31, 2018
    This dataset updates: As needed
    Sudan-El Fasher profiling exercise of urban/out-of-camp IDPs and host communities with data collected July 2018 (report published December 2019). The exercise included a household survey administered to a sample of 3,000 households in the urban and peri urban areas of El Fasher, Abu Shouk Camp and El Salam Camp. Data was processed and anonymized with recoding and local suppressions.
  • 200+ Downloads
    Updated 20 October 2020 | Dataset date: October 06, 2020-October 06, 2020
    This dataset updates: As needed
    The data shows the number of people, Household, houses damaged and destroyed by floods and was shared by the government of Sudan (HAC)
  • 80+ 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.
  • 700+ 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.
  • 5500+ Downloads
    Updated 3 September 2020 | Dataset date: September 03, 2020-September 16, 2021
    This dataset updates: Every year
    Sudan administrative level 0 (country), 1 (state), and 2 (district) boundary files REFERENCE YEAR: 2020 Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.
  • 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
  • Updated Live | Dataset date: January 22, 2020-September 15, 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
  • 20+ Downloads
    Updated 9 July 2020 | Dataset date: June 01, 2019-February 28, 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.
  • 60+ Downloads
    Updated 9 July 2020 | Dataset date: March 20, 2020-March 20, 2020
    This dataset updates: As needed
    Sudan International line shapefile
  • 60+ 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.
  • 60+ 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.
  • 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: 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.