Democratic Republic of the Congo

Data Grid Completeness
75% 
15/20 Core Data 20 Datasets 14 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
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Affected People
4 Datasets
100% 
Internally-Displaced Persons
Humanitarian Needs
OCHA Democratic Republic of the Congo (DRC)
Coordination & Context
5 Datasets
40%  40%  19% 
3w - Who is doing what where
OCHA Democratic Republic of the Congo (DRC)
Conflict Events
Armed Conflict Location & Event Data Project (ACLED)
Climatic Hazards
Food Security & Nutrition
3 Datasets
100% 
Food security
Integrated Food Security Phase Classification (IPC)
Acute Malnutrition
Food Prices
Geography & Infrastructure
4 Datasets
75%  25% 
Administrative Divisions
Roads
Health & Education
2 Datasets
50%  50% 
Population & Socio-economy
2 Datasets
100% 
Baseline Population
OCHA Democratic Republic of the Congo (DRC)
Poverty Rate
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  • 8500+ Downloads
    Updated 1 July 2022 | Dataset date: July 01, 2022-July 01, 2022
    This dataset updates: Every day
    FTS publishes data on humanitarian funding flows as reported by donors and recipient organizations. It presents all humanitarian funding to a country and funding that is specifically reported or that can be specifically mapped against funding requirements stated in humanitarian response plans. The data comes from OCHA's Financial Tracking Service, is encoded as utf-8 and the second row of the CSV contains HXL tags.
  • Updated 30 June 2022 | Dataset date: June 30, 2022-June 30, 2022
    This dataset updates: As needed
    Democratic Republic of the Congo population density for 400m H3 hexagons. Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution. Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand (LINZ Data Service) NZ Building Outlines and OpenStreetMap data. Gobal version of population dataset: Kontur Population: Global Population Density for 400m H3 Hexagons
  • Updated 30 June 2022 | Dataset date: January 31, 2017-July 01, 2022
    This dataset updates: Every week
    Congo, The Democratic Republic of the Weekly staple food price data collected by FEWS NET since 2017.
  • The "GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of settlement points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: settlement point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_settlements_names_V01.gdb The following layers are included in the gdb: codebook__settlements_names GRID3_DRC_settlements_names_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/pvdz-4x94. Accessed DAY MONTH YEAR.
  • The "GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of school points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work. the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS and Novel-T. GRID3 Mapping for Health in DRC is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: schools point data and a table with the field descriptions for the layer. File name: GRID3_DRC_schools_V01.gdb The following layers are included in the gdb: codebook_schools GRID3_DRC_schools_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces- Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/a3d6-m921. Accessed DAY MONTH YEAR
  • The "GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of religious centre points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). This dataset is one of five (5) datasets (along with the Settlements, Health Facilities, Health Catchment Area Boundaries, and Schools datasets)included in this Version 01 release. To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one geospatial layer: religious centre point data and a table with the field descriptions for the layer. File name: GRID3_DRC_religious_centers_V01.gdb The following layers are included in the gdb: codebook__religious_centers GRID3_DRC_religious_center_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces - Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/z4vq-h095. Accessed DAY MONTH YEAR
  • 10+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-July 01, 2022
    This dataset updates: As needed
    The "GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health facility points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of four layers: health facility point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_health_facilities_V01.gdb The following layers are included in the gdb: codebook_health_facilities GRID3_DRC_bcz_5_prov_V01 (The “BCZ” refers to the Bureau central de la Zone de Santé (Central Office of the Health Zone), which constitutes the framework structure for the organization and operation of the health zone. It is located either within the Hôpital Général de Référence (General Reference Hospital), or outside it but inside the health zone. The BCZ is the operational level of the DRC Health System and level of implementation of strategies from the Ministry of Health.) GRID3_DRC_health_facilities_5_prov_V01 (Government, NGO, or private health facilities that offer vaccination or public health services.) GRID3_DRC_KN_secondary_health_facilities_1_prov_V01 (The main goal of data collection conducted for the EPI was to identify health facilities (public and private) that provided services for public health and routine immunisations. However, at the demand of the DSNIS, all the facilities, public or private, were also geo-referenced. The healthcare services density is such in Kinshasa (with various facilities for private services, specialists, and faith healers opening and closing quite frequently) that GRID3 created a secondary health facilities layer to be able to differentiate the main public structures from others.) Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/0bvp-kp75. Accessed DAY MONTH YEAR.
  • 10+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-July 01, 2022
    This dataset updates: As needed
    The "GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health area boundary polygons with names and attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative delivered in partnership with Flowminder and CIESIN (Columbia University), in collaboration with WorldPop at the University of Southampton, the Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: health catchment area polygon data and a table with the field descriptions for the layers. Filename: GRID3_DRC_health_catchment_area_boundaries_V01.gdb The following layers are included in the gdb: GRID3_DRC_health_catchment_zone_boundaries_5_prov_V01 GRID3_DRC_health_catchment_area_boundaries_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/hzrd-yq54. Accessed DAY MONTH YEAR.
  • 200+ Downloads
    Updated 29 June 2022 | Dataset date: January 01, 1997-June 24, 2022
    This dataset updates: Every week
    A weekly dataset providing the total number of reported political violence, civilian-targeting, and demonstration events in Democratic Republic of Congo. Note: These are aggregated data files organized by country-year and country-month. To access full event data, please register to use the Data Export Tool and API on the ACLED website.
  • 500+ Downloads
    Updated 28 June 2022 | Dataset date: February 17, 2021-March 03, 2021
    This dataset updates: Every year
    In partnership with Yale, Meta launched a climate change opinion survey that explores public climate change knowledge, attitudes, policy preferences, and behaviors. The 2022 survey includes respondents from nearly 200 countries and territories. We are sharing country level data from this survey, providing policymakers, research institutions, and nonprofits with an international view of public climate change opinion. For more information please see https://dataforgood.facebook.com/dfg/tools/climate-change-opinion-survey If you're interested in becoming a research partner and accessing record level data, please email dataforgood@fb.com.
  • Updated 28 June 2022 | Dataset date: August 01, 2021-July 01, 2022
    This data is by request only
    The Food and Agriculture Organization of the United Nations (FAO) has developed a monitoring system in 25 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every four months, depending on seasonality). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. As the system is developed, the information collected and analyzed is being used to guide strategic decisions, to design programmes and to inform analytical processes such as the Integrated Phase Classification (IPC) and the Humanitarian Needs Overview (HNO). At the core of the system is a standardized household questionnaire administered to around 100,000 households across the 25 countries. Standardization permits comparisons across time and space, considerably enhancing the utility of the data for decision makers. At minimum the household data are representative at Admin 1 level (e.g. province, or region) and in some cases at Admin 2 level (e.g. district). Core funding for this initiative comes from the United States Agency for International Development (USAID). The initiative also benefits from support from the European Union and FAO’s Special Fund for Emergency and Rehabilitation (SFERA). The contents of the work are the sole responsibility of FAO and do not necessarily reflect the views of USAID, the United States Government or the European Union. On the Hub Homepage ( https://data-in-emergencies.fao.org/ ) it is possible to create an account and explore/download aggregated data related to the following thematic areas: 1) Incomes and shocks 2) Crop Production 3) Livestock Production 4) Food Security 5) Needs Aggregated datasets are generated from household interviews performed after August 2021. At every new survey data release, after cleaning and validation phases, aggregated data is appended to the present datasets. In each aggregated field, the values indicate the frequencies of the different responses, expressed as a weighted percentage of the total sample.
  • 1600+ Downloads
    Updated Live | Dataset date: December 15, 2020-July 01, 2022
    This dataset updates: Live
    This dataset contains data obtained from a variety of sources and transformed into a form suitable for driving the Covid-19 Data Explorer. The visual itself is driven by a JSON file which contains the same data as the resources in this dataset which point to published csvs from a Google spreadsheet.
  • 1300+ Downloads
    Updated Live | Dataset date: February 19, 2021-July 01, 2022
    This dataset updates: Live
    This dataset contains COVID-19 vaccine dose availability forecasts as well as actual deliveries for countries with Humanitarian Response Plans. The data on vaccine availability forecasts was manually extracted from the COVAX Facility Interim Distribution Forecast as announced by COVAX on 3 February 2021. Figures for actual deliveries through channels other than COVAX are compiled by OCHA from press reports. The source(s) press releases, official announcements or articles for each such vaccine delivery are included in the dataset.
  • 1200+ Downloads
    Updated Live | Dataset date: December 14, 2020-June 17, 2022
    This dataset updates: Live
    Immunization campaigns impacted due to COVID-19
  • 100+ Downloads
    Updated Live | Dataset date: February 08, 2021-July 01, 2022
    This dataset updates: Live
    Number of children 6-59 months admitted for TREATMENT OF SEVERE ACUTE MALNUTRITION (SAM) by country
  • 400+ Downloads
    Updated 28 June 2022 | Dataset date: January 01, 2021-July 01, 2022
    This dataset updates: Every month
    At the time of the Global Humanitarian Overview 2022 launch in December 2021, 274 million people need humanitarian assistance and protection. This number means that 1 in 29 people worldwide needs humanitarian assistance – a significant increase from 1 in 33 in 2020 and 1 in 45 in 2019, which were already the highest figures in decades. The UN and partner organizations aim to assist 183 million people most in need across 30 countries and 7 regions and require a total of $ 41 billion to do so.
  • 60+ Downloads
    Updated 28 June 2022 | Dataset date: June 01, 2017-June 30, 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.
  • 18000+ Downloads
    Updated 27 June 2022 | Dataset date: January 01, 2011-December 31, 2021
    This dataset updates: Every month
    Data used to update country toplines in HDX. Contains data from World Bank's data portal.
  • 500+ Downloads
    Updated 26 June 2022 | Dataset date: January 01, 1970-December 31, 2020
    This dataset updates: Every year
    Prices for Democratic Republic of the Congo. Contains data from the FAOSTAT bulk data service covering the following categories: Deflators, Exchange rates
  • 2100+ Downloads
    Updated 26 June 2022 | Dataset date: January 15, 2007-March 15, 2022
    This dataset updates: Every week
    This dataset contains Food Prices data for Democratic Republic of the Congo, sourced from the World Food Programme Price Database. The World Food Programme Price Database covers foods such as maize, rice, beans, fish, and sugar for 98 countries and some 3000 markets. It is updated weekly but contains to a large extent monthly data. The data goes back as far as 1992 for a few countries, although many countries started reporting from 2003 or thereafter.
  • 2300+ Downloads
    Updated 22 June 2022 | Dataset date: January 01, 2018-April 26, 2022
    This dataset updates: Every two weeks
    The file provides information on the cases, deaths, ... of the various pathologies on the extent of the national territory. Le fichier renseigne sur les cas, décès, ... des différentes pathologies sur l'étendue du territoire national.
  • 200+ Downloads
    Updated 21 June 2022 | Dataset date: June 21, 2022-November 21, 2022
    This dataset updates: Every six months
    Priorisation du cluster nutrition qui se base sur plusieurs facteurs aggravants pour permettre de mettre en avant les zones de santé les plus sensibles à la malnutrition alors que les données provenant des enquêtes nutritionnelles sont vieillissantes pour certaine Zone de santé.
  • 10000+ Downloads
    Updated Live | Dataset date: January 01, 2015-June 08, 2022
    This dataset updates: Live
    This dataset contains agency- and publicly-reported data for events in which an aid worker was killed, kidnapped, or arrested. Categorized by country.
  • 3600+ Downloads
    Updated 20 June 2022 | Dataset date: June 01, 2015-March 31, 2022
    This dataset updates: Every three months
    Projets en cours d'execution en RD Congo, ainsi que le nombre de personnes ciblées durant la période aggrégées par zone de santé et par secteur. Seuls les projets humanitaires sont repris dans ce fichier.
  • 700+ Downloads
    Updated 19 June 2022 | Dataset date: January 01, 2008-December 31, 2021
    This dataset updates: Every year
    Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. "People Displaced" refers to the number of people living in displacement as of the end of each year. "New Displacement" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once. Contains data from IDMC's Global Internal Displacement Database.