Sudan

Data Grid Completeness
70% 
14/20 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.
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
Affected People
3 Datasets
75%  25% 
Internally-Displaced Persons
Sudan Displacement Situation - IDPs [IOM DTM]
International Organization for Migration (IOM)
Refugees & Persons of Concern
Sudan - Data on forcibly displaced populations and stateless persons
UNHCR - The UN Refugee Agency
Returnees
Humanitarian Needs
Sudan: Humanitarian Needs Overview
OCHA Sudan
Coordination & Context
5 Datasets
100% 
3w - Who is doing what where
Sudan: Operational Presence
OCHA Sudan
Funding
Sudan - Requirements and Funding Data
OCHA Financial Tracking System (FTS)
Conflict Events
Sudan - Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Humanitarian Access
Sudan - Humanitarian Access
OCHA Sudan
Climate Impact
Sudan: People Affected by Floods
OCHA Sudan
Food Security & Nutrition
3 Datasets
66%  33% 
Food security
Sudan: Acute Food Insecurity Country Data
Integrated Food Security Phase Classification (IPC)
Acute Malnutrition
Sudan: GAM (MAM and SAM) based on MUAC measurements
OCHA Sudan
Food Prices
Sudan - Food Prices
WFP - World Food Programme
Geography & Infrastructure
4 Datasets
50%  50% 
Administrative Divisions
Sudan - Subnational Administrative Boundaries
OCHA Regional Office for Southern and Eastern Africa (ROSEA)
Populated Places
Sudan: Settlements
OCHA Sudan
Roads
Sudan - Roads
OCHA Sudan
Airports
Sudan: UNHAS Destination Points
OCHA Sudan
Health & Education
2 Datasets
100% 
Health Facilities
Health Facilities in Sub-Saharan Africa
HDX
Education Facilities
Sudan - Schools
OCHA Sudan
Population & Socio-economy
2 Datasets
100% 
Baseline Population
Sudan - Subnational Population Statistics
UNFPA
Poverty Rate
Sudan: subnational poverty
Oxford Poverty & Human Development Initiative
Data Datasets [249] | Archived Datasets[102] [?]
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  • Sudan: Projected COVID-19 Sub-national Cases
    Johns Hopkins Applied Physics Lab
    70+ Downloads
    Time Period of the Dataset [?]: July 29, 2020-November 30, 2020 ... More
    Modified [?]: 4 March 2021
    Dataset Added on HDX [?]: 5 August 2020
    Less
    This dataset updates: As needed
    This dataset is part of the data series [?]: Johns Hopkins Applied Physics Lab - Projected COVID-19 subnational cases
    The COVID-19 pandemic has brought into stark focus the need for data and the value of models to inform response strategies. Since March, the Centre has been working with the Johns Hopkins University Applied Physics Laboratory (APL) to develop a COVID-19 model adapted for use in humanitarian contexts. Access the - code repository , including all the source code scripts necessary to run the model. View the - technical documentation and - FAQs explaining how to configure and run the source code in the repository. Download the - methodology paper providing details on model assumptions and the main equations. Access - [biweekly reports] (https://drive.google.com/drive/u/1/folders/16FR8owccpfIm-tspdAa4YTEwPoZKHtvI) for six countries. Download the - OCHA-Bucky model card created according to the Centre’s Peer Review Framework. The result is a model, named OCHA-Bucky, that forecasts the number of cases, hospitalizations, and deaths over two or four weeks, at the subnational and national levels.
  • Humanitarian Access Indicators
    HDX
    400+ Downloads
    Time Period of the Dataset [?]: November 20, 2020-November 20, 2020 ... More
    Modified [?]: 4 March 2021
    Dataset Added on HDX [?]: 20 November 2020
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    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.
  • 2020 Multi-Sectoral Needs Assessment, Analysis results of household data, Sudan
    REACH Initiative
    100+ Downloads
    Time Period of the Dataset [?]: August 16, 2020-November 26, 2020 ... More
    Modified [?]: 24 February 2021
    Dataset Added on HDX [?]: 24 February 2021
    Less
    This dataset updates: Never
    This inaugural round of Sudan's Multi-Sector Needs Assessment (MSNA), conducted by REACH and OCHA in close collaboration with the Inter-Sectoral Coordination Group (ISCG), seeks to understand multi-sectoral priority humanitarian needs of populations across the whole of Sudan. The findings from this assessment are presented in this document and are intended to provide timely updates on key sectoral needs and priorities in order to inform humanitarian response and strategic programming for non-displaced, IDP and refugee households across the country.
  • Sudan - UNHCR Refugee camps
    OCHA Sudan
    200+ Downloads
    Time Period of the Dataset [?]: January 11, 2021-January 11, 2021 ... More
    Modified [?]: 18 January 2021
    Dataset Added on HDX [?]: 18 January 2021
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    This dataset updates: As needed
    This shapefile shows the Refugee camps in Sudan
  • Who is doing What and Where in Sudan, November 2020
    OCHA Sudan
    50+ Downloads
    Time Period of the Dataset [?]: December 01, 2020-December 01, 2020 ... More
    Modified [?]: 10 December 2020
    Dataset Added on HDX [?]: 10 December 2020
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    This dataset updates: Every six months
    The data shows Who is doing What and Where by locality in Sudan
  • Sudan Who does What & Where November 2020
    OCHA Sudan
    40+ Downloads
    Time Period of the Dataset [?]: November 22, 2020-November 22, 2020 ... More
    Modified [?]: 9 December 2020
    Dataset Added on HDX [?]: 9 December 2020
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    This dataset updates: Every six months
    Sudan 3Ws data for November 2020
  • Sudan: Settlements
    OCHA Sudan
    300+ Downloads
    Time Period of the Dataset [?]: July 26, 2020-July 26, 2020 ... More
    Modified [?]: 17 November 2020
    Dataset Added on HDX [?]: 17 November 2020
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    This dataset updates: Every year
    The settlements dataset contains the location of cities, towns and villages in Sudan.
  • Sudan - Flood Affected People from 2013 to 2020
    OCHA Sudan
    100+ Downloads
    Time Period of the Dataset [?]: November 10, 2020-November 10, 2020 ... More
    Modified [?]: 12 November 2020
    Dataset Added on HDX [?]: 12 November 2020
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    This dataset updates: As needed
    This data is showing the number of affected people by floods per year from 2013 to 2020
  • Sudan People Affected by Floods
    OCHA Regional Office for Southern and Eastern Africa (ROSEA)
    100+ Downloads
    Time Period of the Dataset [?]: October 06, 2020-October 06, 2020 ... More
    Modified [?]: 20 October 2020
    Dataset Added on HDX [?]: 18 October 2020
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    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)
  • Sudan - Population Counts
    WorldPop
    200+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 12 September 2020
    Dataset Added on HDX [?]: 20 July 2017
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    This dataset updates: Every year
    This dataset is part of the data series [?]: World Pop - Population Counts
    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
  • Humanitarian Access Constraints due to COVID-19 Pandemic
    OCHA HQ
    400+ Downloads
    Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More
    Modified [?]: 4 September 2020
    Dataset Added on HDX [?]: 26 May 2020
    Less
    This dataset updates: As needed
    The new and emerging access constraints that people are currently experiencing because of the COVID-19 outbreak.
  • COVID19 Humanitarian Access Constraints, Impacts and Mitigation
    OCHA HQ
    100+ Downloads
    Time Period of the Dataset [?]: August 31, 2020-August 31, 2020 ... More
    Modified [?]: 2 September 2020
    Dataset Added on HDX [?]: 22 July 2020
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    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
  • Novel Coronavirus (COVID-19) Cases Data
    Johns Hopkins University Center for Systems Science and Engineering
    433000+ Downloads
    Time Period of the Dataset [?]: January 22, 2020-March 09, 2023 ... More
    Modified [?]: 28 July 2020
    Dataset Added on HDX [?]: 7 February 2020
    Less
    This dataset updates: As needed
    JHU Has Stopped Collecting Data As Of 03/10/2023 After three years of around-the-clock tracking of COVID-19 data from around the world, Johns Hopkins has discontinued the Coronavirus Resource Center’s operations. The site’s two raw data repositories will remain accessible for information collected from 1/22/20 to 3/10/23 on cases, deaths, vaccines, testing and demographics. 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
  • Sudan Administrative boundary level 0
    OCHA Sudan
    100+ Downloads
    Time Period of the Dataset [?]: March 20, 2020-March 20, 2020 ... More
    Modified [?]: 9 July 2020
    Dataset Added on HDX [?]: 9 July 2020
    Less
    This dataset updates: As needed
    Sudan International line shapefile
  • Sudan - Population Density
    WorldPop
    200+ Downloads
    Time Period of the Dataset [?]: January 01, 2000-December 31, 2020 ... More
    Modified [?]: 22 June 2020
    Dataset Added on HDX [?]: 24 November 2020
    Less
    This dataset updates: Every year
    This dataset is part of the data series [?]: WorldPop - Population Density
    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
  • Sudan: Number of Health Specialists per category in Sudan
    OCHA Sudan
    70+ Downloads
    Time Period of the Dataset [?]: December 31, 2018-December 31, 2018 ... More
    Modified [?]: 3 June 2020
    Dataset Added on HDX [?]: 3 June 2020
    Less
    This dataset updates: As needed
    Number of Health Specialists per category in Sudan
  • Sudan: Prevalence of diseases in outpatient clinics per state
    OCHA Sudan
    60+ Downloads
    Time Period of the Dataset [?]: December 31, 2018-December 31, 2018 ... More
    Modified [?]: 3 June 2020
    Dataset Added on HDX [?]: 3 June 2020
    Less
    This dataset updates: As needed
    Prevalence of diseases in outpatient clinics per state in Sudan for the year 2018
  • Sudan: COVID-19 Cases High Risk Population Arrivals by State
    OCHA Sudan
    70+ Downloads
    Time Period of the Dataset [?]: May 25, 2020-May 25, 2020 ... More
    Modified [?]: 29 May 2020
    Dataset Added on HDX [?]: 29 May 2020
    Less
    This dataset updates: As needed
    COVID-19 cases high risk population arrivals by state_25 May 2020
  • Regional Intention Survey of South Sudanese Refugees in Central African...
    UNHCR - The UN Refugee Agency
    20+ Downloads
    Time Period of the Dataset [?]: April 01, 2019-May 30, 2019 ... More
    Modified [?]: 20 May 2020
    Dataset Added on HDX [?]: 27 May 2021
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    This dataset updates: Never
    This dataset is part of the data series [?]: UNHCR - Intention to return survey
    The South Sudan situation is currently the largest refugee situation on the African continent. There are over 2.2 million refugees spread across Sudan, Uganda, Ethiopia, Kenya, the Democratic Republic of the Congo (DRC), and the Central African Republic (CAR) a further 1.8 million people are displaced internally in South Sudan. An estimated 140,000 South Sudanese spontaneously returnees are reported to have returned to South Sudan from November 2018 to date. The South Sudan situation continues to be characterized as a children's tragedy with children constituting over 65 percent of the refugee population. The Revitalised Agreement for the Resolution of the Conflict in the Republic in South Sudan (R-ARCSS) foresees the formation of a Government of National Unity (GNU) with all the parties in agreement including the leader of the SPLA IO and first vice president by May 2019. In November 2018, it was agreed during the Kampala Representatives meeting that intention surveys should be conducted for South Sudanese refugees in all countries of asylum. This was further concretized in March 2019, during the EHA/GLR planning meeting; here it was decided that UNHCR country representations of CAR, Kenya, Uganda, DRC, Sudan, Ethiopia would ensure that a rapid intention survey of South Sudanese refugees in their respective asylum countries is carried out before May 2019, in line with the agreed calendar of the R-ARCSS The Intention Survey was a cross-sectional survey conducted among the over 2.2 million South Sudanese refugees living in six countries of asylum using a stratified random sampling approach to survey 6,964 refugees (heads of households) in 15 camps selected across the region. In each location, sample size estimation assumed a 95 per cent confidence level, and a margin of error of 7 per cent; sample was drawn taking into account the location, place of origin, ethnicity, year of arrival to the country of asylum and gender of the head of household. The confidence intervals were taken into consideration in all the tables and analysis. Security, access and logistical constraints restricted sampling in some locations, therefore weighting was applied to adjust for unequal selection probabilities in each of the 15 locations. The findings of this report are representative of the return intentions of refugee households in these 15 camps. Data was collected through in-person interviews using a harmonised survey that was conducted concurrently in the six countries in May 2019 with a mobile data collection tool (KoBo Toolkit). Questionnaires were administered to consenting refugees aged 12 years and above. Children below 12 years of age were excluded from the survey.
  • Sudan: PIN and Severity 2020
    OCHA Sudan
    100+ Downloads
    Time Period of the Dataset [?]: May 10, 2020-May 10, 2020 ... More
    Modified [?]: 10 May 2020
    Dataset Added on HDX [?]: 10 May 2020
    Less
    This dataset updates: As needed
    This data set contains people in need figures for Sudan by locality (Admin level 2) and sector
  • Population & Socio-economy: Baseline Population by Age and Sex
    OCHA Sudan
    100+ Downloads
    Time Period of the Dataset [?]: January 01, 2018-January 01, 2018 ... More
    Modified [?]: 10 May 2020
    Dataset Added on HDX [?]: 10 May 2020
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    This dataset updates: As needed
    Population figures provided by Sudan's Central Bureau of Statistics. More information can be found on the website: http://cbs.gov.sd/index.php/en/
  • People in Need, IDPs, Refugees and Returnees figures in 2020
    OCHA HQ
    500+ Downloads
    Time Period of the Dataset [?]: January 01, 2020-December 31, 2020 ... More
    Modified [?]: 6 May 2020
    Confirmed [?]: 6 May 2020
    Dataset Added on HDX [?]: 6 May 2020
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    This dataset updates: Every year
    This data contains the number of people in need, internally displaced persons (IDPs), returnees and refugees for 25 countries.
  • Imperial College COVID-19 Projections
    HDX
    300+ Downloads
    Time Period of the Dataset [?]: March 26, 2020-March 26, 2020 ... More
    Modified [?]: 6 May 2020
    Dataset Added on HDX [?]: 6 May 2020
    Less
    This dataset updates: As needed
    Data on unmitigated(no intervention) COVID-19 scenarios for OCHA HRP countries. Simulation done by Imperial College London.
  • LSHTM COVID-19 Projections
    HDX
    300+ Downloads
    Time Period of the Dataset [?]: May 05, 2020-May 05, 2020 ... More
    Modified [?]: 6 May 2020
    Dataset Added on HDX [?]: 6 May 2020
    Less
    This dataset updates: As needed
    This dataset contains simulation ­based estimates for COVID­-19 epidemic scenarios in OCHA HRP countries. Simulation is done by London School of Hygiene & Tropical Medicine(LSHTM).
  • Sudan : Refugee population
    OCHA Sudan
    100+ Downloads
    Time Period of the Dataset [?]: February 29, 2020-February 29, 2020 ... More
    Modified [?]: 9 April 2020
    Dataset Added on HDX [?]: 9 April 2020
    Less
    This dataset updates: Every year
    Refugee population of Sudan by UNHCR